Green Car Congress - 記事一覧
Terberg introduces new generation of electric terminal tractor; hydrogen fuel-cell version possible
The Netherlands-based Terberg is introducing a new generation of electric vehicles with new EV technology, including the YT203-EV terminal tractor (which replaces the older YT202-EV) and the BC202-EV body carrier. New generation YT203-EV The performance of the new electric drive system is comparable with that of diesel engines and the large battery option offers a significantly greater operating range. Additionally, the new battery technology has an extended temperature range and can be used worldwide in both very cold and warm climates. The first BC202-EV body carrier will be delivered in April 2020 and the new generation YT203-EV terminal tractor will become available at the end of 2020. With the new technology Terberg delivers significant improvements. Customers can choose from a number of battery capacity combinations so they can select the option best suited to their operations. Applications with high vehicle usage will benefit from the battery with the increased capacity, resulting in a longer range. Customers with operations involving lower vehicle usage and with more opportunities to charge the vehicle during the day can opt for a smaller battery pack, at a lower price. The new electric drive system has fewer moving parts than a diesel engine and the previous EV generation, resulting in lower maintenance costs. The new EV drive supports regenerative braking, reducing energy consumption. Finally, the vehicles can operate indoors, with zero emissions and a lower noise level, which is particularly relevant for terminal tractors. The vehicles use DC chargers and can therefore be charged at standard charging stations. The new batteries comply with the ECE-R100 rev. 2 regulation and withstand both very high and very low temperatures. This means the new Terberg YT203-EV can be deployed anywhere in the world. Additionally, the new charger connector complies with the CCS2.0 automotive standard. This charger technology is also available in the United States. The Terberg Connect telematics system provides remote monitoring of the status and performance of each vehicle, including the charge cycle and remaining battery capacity. This enables operators to charge their vehicles at just the right time, and avoid unscheduled downtime. Terberg developed the new generation electric drive as a multifunctional, modular concept. This makes it easier to adapt the EV-technology to a range of vehicles, such as the new YT203-EV terminal tractor and the BC202-EV body carrier. The design also allows for the use of hydrogen fuel cells in future. Proof-of-concept hydrogen fuel-cell-powered yard tractor YT203-H2. In January 2019, Terberg Special Vehicles and Zepp.solutions unveiled a proof-of-concept hydrogen fuel cell yard tractor. The YT203-H2 specification covers all the operational requirements for different applications such as logistics, distribution and ports for the global market. This project was supported by the DKTI-Transport regulation of the Dutch Ministry of Infrastructure and Water Management.
SwRI motion prediction system enhances pedestrian detection for automated vehicles
Southwest Research Institute (SwRI) has developed a motion prediction system that enhances pedestrian detection for automated vehicles. The computer vision tool uses a novel deep learning algorithm to predict motion by observing real-time biomechanical movements with the pelvic area being a key indicator for changes. SwRI’s human motion prediction system overlays sparse skeletal features on pedestrians to predict movement. The blue dot in this image predicts the future direction of pedestrian on right. Deep learning algorithms predict motion based on pelvic biomechanical movement. Credit: Courtesy of Southwest Research Institute For instance, if a pedestrian is walking west, the system can predict if that person will suddenly turn south. As the push for automated vehicles accelerates, this research offers several important safety features to help protect pedestrians.—SwRI’s Samuel E. Slocum, a senior research analyst who led the internally funded project Recent accidents involving automated vehicles have heightened the call for improved detection of pedestrians and other moving obstacles. Although previous technologies could track and predict movements in a straight line, they were unable to anticipate sudden changes. Motion prediction often uses “optical flow” algorithms to predict direction and speed based on lateral motion. Optical flow, a type of computer vision, pairs algorithms with cameras to track dynamic objects. The accuracy of optical flow diminishes, however, when people move in unexpected directions. To improve accuracy, SwRI compared optical flow to other deep learning methods, including temporal convolutional networks (TCNs) and long short-term memory (LSTM). After testing several configurations, researchers optimized a novel TCN that outperformed competing algorithms, predicting sudden changes in motion within milliseconds with a high level of accuracy. The temporal design uses a convolutional neural network to process video data. SwRI’s novel approach optimizes dilation in network layers to learn and predict trends at a higher level. Dilated convolutions are structures that store and access video data for spatial observations. People draw on experience and inference when driving near pedestrians and cyclists. SwRI’s research is a small step for autonomous systems to react more like human drivers. If we see a pedestrian, we might prepare to slow down or change lanes in anticipation of someone crossing the street. We take it for granted, but it’s incredibly complex for a computer to process this scene and predict scenarios.—Dr. Douglas Brooks, a manager in SwRI’s Applied Sensing Department The research team leveraged SwRI’s markerless motion capture system, which automates biomechanical analysis in sports science. Using camera vision and perception algorithms, the system provides deep insights into kinematics and joint movement. Applications for the project, titled “Motion Prediction from Sparse Skeletal Features,” include human performance, automated vehicles and manufacturing robotics. The algorithms can work with a variety of camera-based systems, and datasets are also available to SwRI clients.
Northwestern team develops decentralized swarming algorithm for autonomous vehicles
Self-driving vehicles need to navigate safely and flawlessly without crashing into others or causing unnecessary traffic jams. To make this possible, Northwestern University researchers have now developed the first decentralized algorithm with a collision-free, deadlock-free guarantee. The researchers tested the swarming algorithm in a simulation of 1,024 robots and on a swarm of 100 real robots in the laboratory. The robots reliably, safely and efficiently converged to form a pre-determined shape in less than a minute. If you have many autonomous vehicles on the road, you don’t want them to collide with one another or get stuck in a deadlock. By understanding how to control our swarm robots to form shapes, we can understand how to control fleets of autonomous vehicles as they interact with each other.—Northwestern Engineering’s Michael Rubenstein, who led the study A paper on the work is published in the journal IEEE Transactions on Robotics. Rubenstein is the Lisa Wissner-Slivka and Benjamin Slivka Professor in Computer Science and Mechanical Engineering in Northwestern’s McCormick School of Engineering. He’s also a member of Northwestern’s Center for Robotics and Biosystems. The advantage of a swarm of small robots—versus one large robot or a swarm with one lead robot—is the lack of a centralized control, which can quickly become a central point of failure. Rubenstein’s decentralized algorithm acts as a fail-safe. If the system is centralized and a robot stops working, then the entire system fails. In a decentralized system, there is no leader telling all the other robots what to do. Each robot makes its own decisions. If one robot fails in a swarm, the swarm can still accomplish the task.—Michael Rubenstein Still, the robots need to coordinate in order to avoid collisions and deadlock. To do this, the algorithm views the ground beneath the robots as a grid. By using technology similar to GPS, each robot is aware of where it sits on the grid. Before making a decision about where to move, each robot uses sensors to communicate with its neighbors, determining whether or not nearby spaces within the grid are vacant or occupied. The robots refuse to move to a spot until that spot is free and until they know that no other robots are moving to that same spot. They are careful and reserve a space ahead of time.—Michael Rubenstein Even with all this careful coordination, the robots are still able to communicate and move swiftly to form a shape. Rubenstein accomplishes this by keeping the robots near-sighted. Each robot can only sense three or four of its closest neighbors. They can’t see across the whole swarm, which makes it easier to scale the system. The robots interact locally to make decisions without global information.—Michael Rubenstein In Rubenstein’s swarm, for example, 100 robots can coordinate to form a shape within a minute. In some previous approaches, it could take a full hour. Rubenstein imagines that his algorithm could be used in fleets of driverless cars and in automated warehouses. Large companies have warehouses with hundreds of robots doing tasks similar to what our robots do in the lab. They need to make sure their robots don’t collide but do move as quickly as possible to reach the spot where they eventually give an object to a human.—Michael Rubenstein Resources H. Wang and M. Rubenstein (2020) “Shape Formation in Homogeneous Swarms Using Local Task Swapping,” in IEEE Transactions on Robotics doi: 10.1109/TRO.2020.2967656
CNCDA: registration of electrified vehicles up 3.6% in California in 2019, while total car reg down 5.5%
Registrations of new electrified light-duty vehicles (HEVS, PHEVs and EVs) in California rose 3.6% to 250,566 units in 2019, up from 241,970 units, according to the California New Car Dealers Association (CNCDA), using data from IHS. Overall, the California new light-duty vehicle market declined 5.5% from 2018 to 2019 (2,002,047 to 1,892,672 units), while the total US market fell 1.1% (17,115,072 units to 16,931,012 units). The California new vehicle market recorded its 11th consecutive year-over-year quarterly decline in the Fourth Quarter of 2019. New vehicle registrations in the state fell 7.0% in 4Q19 vs. the 3.8% drop in 3Q19. The electrified vehicle market put in a strong showing due partly to a resurgence in demand for conventional hybrids. After annual declines for several years, registrations of new HEVs in 2019 jumped 24.2% to 104,702 units, according to CNCDA, even outpacing the strong California EV market. Registrations of new light-duty EVs in California climbed only 5% in 2019, to 99,704 units from 94,801 the year before. PHEVs, which have been outsold by both HEVs and EVs since 2014, saw their registrations drop to 46,160 units in 2019, a decline of 26.6%. Data: IHS, CNCDA Overall, according to CNCDA, registrations of new plug-in vehicles (PHEVs and EVs) dropped 7.5% from 2018 to 2019, from 157,648 to 145,864 units, with the result driven by the slowing rate of increased EV sales not able to offset the drop in PHEV sales. Market share. As a result, HEVs hels a 5.5% market share in California in 2019, EVs held a 5.3% marketshare and PHEVs held a 2.4% marketshare, for a combined hybrid/electric vehicle market share in 2019 of 13.2%. Tesla by itself took a 3.8% market share in 2019 in California, up 0.3 percentage points from the year before. However, 4Q19 California new vehicle registrations for Tesla were down 46.1% from 4Q18—from 25,961 units to 13,999 units. Tesla holds a 1.1% market share in the US. Overall, the California light truck share was up 3.2 percentage points in 2019 to 58.4%. US light truck share was up 3.1 percentage points to 71.9% in 2019.
Bosch and Human Horizons partner on Battery in the Cloud service
At the Bosch Connected World 2020 (BCW) conference in Berlin, Human Horizons initiated an agreement with Bosch Connected Mobility Solutions for further cooperation on Bosch’s Battery in the Cloud technology. (Earlier post.) This technology connects electric-vehicle batteries with the cloud to extend battery life, substantially improve the battery’s performance and service. The Battery in the Cloud is based on three key steps: Current battery data is collected and pre-filtered by the telematics control unit (TCU) in the vehicles and is then transmitted to a server—generally the Bosch cloud. The data in the cloud is analyzed using software algorithms based on electrochemical, physical, and statistical models. Artificial intelligence methods are then used to calculate predictions about the condition of the respective vehicle battery and to determine its optimal parameter configuration. Additional external cloud data, such as weather and traffic conditions, map data, and available charging stations, is also factored into these calculations. The results that have been determined for the individual vehicle battery (e.g. recommendations, condition reports, new operating parameters) are transmitted from the cloud to the vehicle, and the new parameter configuration is subsequently implemented in the battery. rvice models are also an option depending on the customer’s wishes. At each of these steps, the Bosch cloud provides a maximum in security during data transmission through a sophisticated security architecture involving end-to-end encryption. In April 2019, Human Horizons and Bosch entered into strategic cooperation on Firmware Over-the-Air (FOTA) solutions for broader collaboration in addition to many technologies such as remote diagnostics, which will be applied to the HiPhi 1. HiPhi is a premium brand created by Human Horizons; HiPhi 1 is a premium EV with a lightweight hybrid-aluminum construction. Human Horizons is an innovative technology company committed to future intelligent mobility with its 3-Smart strategy of Smart Vehicle, Smart Transportation and Smart City. Over the past years, Human Horizons has embraced collaboration with Bosch Connected Mobility Solutions to bring smart vehicle technologies to Human Horizons’ smart vehicle. Today, the power of such collaboration is further strengthened. Bosch and Human Horizons will work together to connect the system and services inside and outside vehicles, transforming them into intelligent mobility solutions. Including FOTA and Battery in the Cloud, and in the near future, this close relationship will play an important role in the cooperation in remote diagnostics, and other intelligent and connected mobility solutions.—Dr. Elmar Pritsch, President of Bosch Connected Mobility Solutions In this agreement, Bosch and Human Horizons plan to cooperate on Battery in the Cloud service. This technology intends to improve the performance of EVs in the areas of HV battery life, charging efficiency, EV user experience and prediction of battery failures and downtime. EV battery life is expected enhanced by up to 20%, or charging speed increased by up to 20%. Very precise State of Health (SOH) calculations and forecasts can be used to further strengthen early detection of battery-related malfunctions, and establish the foundation for predictive maintenance to avoid downtime and enhance the user experience.
SuperTurbo Technologies Inc. appoints Ricardo to support product industrialization
SuperTurbo Technologies Inc. (formerly VanDyne SuperTurbo) has appointed Ricardo Performance Products to support the first phase of commercial industrialization of the SuperTurbo system—a novel planetary traction drive that enables high speed power transfer to and from a turbocharger shaft, offering significant driveability and fuel efficiency benefits for large trucks. The SuperTurbo features a novel mechanical transmission that links the turbo shaft to the engine drive. This enables power transfer to and from the turbo shaft that is not possible with a normal turbocharger. Instead of relying on direct contact of gear teeth, the traction drive utilizes a NASA-developed technology of smooth rollers that transmit torque through a special traction fluid and can operate at very high rotational speeds. The rollers are pushed together to generate high pressures that causes a pseudo-phase change of the traction fluid so it will resist shear forces and transmit higher levels of torque. The added complexity of the traction drive transmission is offset somewhat, in that special designs of the traction drive eliminate the need for any sort of bearings directly supporting the high-speed turbo shaft. These extremely high-speed bearings are a major failure point in conventional turbochargers, but are not needed in the SuperTurbo. In addition to the high-speed planetary traction drive, a continuously variable transmission is used in most applications to enable precise control over the speed of the turbo shaft to provide desired air flow and boost pressure levels for the engine. The reduction in turbo lag also reduces the design requirement for low-inertia turbine and compressor wheels, enabling more flexibility in the design for the turbo-machinery for higher efficiency. During transient operation, the SuperTurbo will behave like a supercharger and draw mechanical energy to accelerate the turbomachinery for improved engine response. Unlike a traditional supercharger, the SuperTurbo also receives transient power from its turbine. The net effect is both a fast transient response and a more efficient power draw for supercharging. The system also provides efficiency benefits to the engine. During operation at higher engine power levels, the turbine of the SuperTurbo captures any excess energy from the exhaust above that needed to drive the compressor to provide boost pressure to the engine. In this operating condition, the system operates in turbo-compound mode, providing surplus power to the engine crankshaft, thus improving fuel efficiency. The precise control over air flow allows the engine manufacturer to tune and control the optimal combustion parameters and reduce particulate emissions. Likewise, NOx emission reduction is enhanced through bypass enabled higher aftertreatment temperatures and improved transient and steady state EGR control. Under the new contract, Ricardo will support SuperTurbo Technologies by providing product industrialization expertise to help in planning the route to commercial manufacture of the SuperTurbo system.
Lucid Motors announces long-term partnership with LG Chem for batteries for Lucid Air EV
Lucid Motors announced a long-term partnership with leading EV battery supplier LG Chem for the Lucid Air electric sedan. Lucid Motors said that it selected LG Chem for a long-term partnership because its batteries provide the ideal level of efficiency, with those batteries further optimized by Lucid to meet or exceed all target goals for range, energy density, and recharge/discharge rates. Full production of the Lucid Air is expected to start lathe this year in Lucid’s factory in Casa Grande, AZ, with LG Chem battery cells exclusively powering standard versions of this luxury EV through 2023. The advanced battery cells provided by LG Chem effectively allow Lucid to lock in core volume production forecasts for the Lucid Air for the next several years, with additional agreements to be announced in the future for special versions of the EV. Lucid selects the best battery cell for each version of the Lucid Air based on data collected during comprehensive and proprietary performance tests, with the cells from LG Chem selected because they provide the ideal level of efficiency for standard versions of the Lucid Air. In conjunction with its proprietary battery architecture and flexible manufacturing technique, Lucid will optimize the LG Chem cells to meet or exceed all target goals for range, energy density, recharge/discharge rates, and more. In this way, Lucid will leverage the specific cell chemistry of LG Chem’s batteries to develop the most compact, yet energy dense, battery pack form possible. Lucid will unveil the production version of the Air in New York in April. In addition to the vehicle's final interior and exterior designs, new details on production specifications, available configurations, and pricing information will also be shared. Lucid is manufacturing 80 beta prototypes at the company’s Silicon Valley headquarters, which will be used for comprehensive testing and validation for key vehicle dynamics, as well as crash testing to confirm exhaustive simulations.
NACFE to focus on electric trucks in regional haul
The North American Council for Freight Efficiency (NACFE)—a non-profit organization dedicated to doubling the freight efficiency of North American goods movement—has determined that regional trucking operations are well suited to be early adopters of electric trucks. It is also a rather large segment of the market with sufficient scale to have a big impact on the industry. As a result, NACFE will focus much of its attention on electric trucks in regional haul. Early workstreams include: Identifying high-potential regional trucking routes in concert with changes to freight movement; Supporting the implementation of initial and future deployments outside of California; Scaling best practices in infrastructure development for fleets and communities; and Increasing confidence in the value of electrification. Our research has shown us that regional haul is an important segment of the trucking industry and also one that makes sense for electrification, given its short-haul nature and return-to-base operation. We are embarking on a three-year project to gain a better understanding of how commercial battery electric vehicles will best fit into the regional haul market.—Mike Roeth, Executive Director, NACFE Specific activities for 2020 will include data analysis, interviews with key stakeholders, collaboration workshops and publishing findings in order to share learnings with all interested stakeholders. This work will build on NACFE’s existing work in this area, including Run on Less Regional, its thought-leadership piece on regional haul, and its Guidance Report series on electric trucks. NACFE is being aided in its efforts by funding from Hewlett Foundation, a non-profit, private charitable foundation that advances ideas and supports institutions to promote a better world; and ClimateWorks Foundation, a non-governmental organization that is committed to climate action.
Hyliion delivers first of three hybrid Class 8 trucks to Penske Truck Leasing
Hyliion Inc. will be providing three vehicles to Penske Truck Leasing, all of which will incorporate its 6X4HE Class 8 hybrid system. (Earlier post.) The solution was developed in partnership with Dana Inc., whose Spicer Electrified components are part of the e-Powertrain solution. The Hyliion 6X4HE’s modular design allows for easy installation and simple servicing. Brand- and engine-agnostic, the 6X4HE can be installed on any Class 8 vehicle from any manufacturer. Components include: The battery pack; control unit; thermal management system; electric axle (up to 1,500 lb-ft (2,000 N·m) and 115 hp); co-pilot display, allowing the driver to monitor the 6X4HE; and an aerodyanmics package to reduce air resistance at speed, with up to 3% fuel and emissions savings. The remaining vehicles will be delivered throughout the year, allowing Penske to complement its fleet with the combined Hyliion-Dana Class 8 electrified solution. As part of the program, Penske will provide ongoing assessments on current and next-generation products.
Chinese team uses light to convert fatty acids into alkanes with up to 95% yield; photocatalytic decarboxylation
Researchers led by Prof. WANG Feng at the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences have reported that photocatalytic decarboxylation is an efficient alternate pathway for converting biomass-derived fatty acids into alkanes under mild conditions of ambient temperature and pressure. This finding was published in Nature Catalysis. Schematic representation of photocatalytic decarboxylation strategy for alkane production from biomass-derived fatty acids. (Image by HUANG Zhipeng). Long-chain alkanes are the major component of diesel and jet fuel. Production of these alkanes from renewable biomass—such as biomass-derived fatty acids instead of fossil resources—could contribute significantly toward developing a sustainable energy supply. However, most established catalytic systems require harsh operating conditions (i.e., high temperature and pressure) and excessive hydrogen consumption. The researchers found that under illumination, the decarboxylation of fatty acids could be easily induced by photo-generated holes on the semiconductor TiO2, subsequently generating alkyl radical intermediates. However, due to the uncontrollable reactivity of alkyl radicals, the production of desired alkanes was characterized by low selectivity. Rationally controlling the conversion of radical intermediates for preferential hydrogen termination is the key to high selectivity in obtaining alkane products.—Prof. WANG The scientists discovered that when exposing the catalyst Pt/TiO2 to H2 atmosphere with light, the interaction between the catalyst and H2 generated a hydrogen-rich surface, so photo-generated radicals could be rapidly terminated by surface hydrogen species, thus greatly inhibiting oligomerization. These results show that Cn-1 alkanes can be obtained from biomass-derived C12-C18 fatty acids in high yields (greater than or equal to 90%) under mild conditions (30 °C, H2 pressure less than or equal to 0.2 MPa) with 365 nm LED irradiation. Moreover, the average production rates are comparable to those of thermocatalytic systems operating under harsh reaction conditions. Tall oil and soybean fatty acids are the low-value byproducts of the pulp and soybean oil refining industries, respectively. The researchers conducted conversion of these two industrial fatty acid mixtures, obtaining alkane products in high yields (up to 95%). Such a green and environmentally friendly process is promising. It bridges photosynthetic chemistry and industrial catalysis, and extends the photoenergy utilization chain. It is particularly promising considering the abundant available low-quality fatty acids in China.—Prof. WANG Resources Huang, Z., Zhao, Z., Zhang, C. et al. (2020) “Enhanced photocatalytic alkane production from fatty acid decarboxylation via inhibition of radical oligomerization.” Nat Catal 3, 170–178 doi: 10.1038/s41929-020-0423-3
Virginia Tech team developing intelligent wearable analyzer for pollutants in transportation-related workplaces
With a $2.3-million award from the National Institute for Occupational Safety and Health (NIOSH), an interdisciplinary team of Virginia Tech researchers led by Masoud Agah, the Virginia Microelectronics Consortium Professor in the Bradley Department of Electrical and Computer Engineering, is developing an intelligent wearable analyzer for vapor exposure, called iWAVE, that can be used to measure hazardous air pollutants in real-time in transportation-related and other workplaces. According to Agah, a renowned researcher in chip-scale gas chromatography and Office of the Vice President for Research and Innovation Faculty Fellow, the development of effective strategies for reducing occupational exposure to pollutants requires accurate, time-resolved measurement of exposure. Current practice typically requires collection of an air sample using specialized equipment, transport of the sample to the lab, and time-consuming analysis using expensive equipment to identify and quantify the pollutants present in the environment. The results are not available for several days, and they only provide an average measure of a worker’s exposure. Truck drivers have a higher risk of lung cancer that is associated with exposure to diesel exhaust. Diesel exhaust is a complex mixture of particles and gases and the specific component responsible for health effects has not been identified. Some of the gaseous compounds are known or suspected carcinogens. We are focusing on measuring some of these compounds.—Linsey Marr, the Charles P. Lunsford Professor in the Via Department of Civil and Environmental Engineering and a co-investigator on this project The small, unobtrusive, wearable, direct-read iWAVE device will provide a time resolution for exposure assessment in five minutes. iWAVE will employ microelectromechanical systems (MEMS) technology, advanced microelectronics components and systems, and state-of-the-art micro gas chromatography (GC) and telecommunication techniques. The low-power, low-cost micro gas analyzer with its embedded system can replace cumbersome sampling methods that must be followed by costly analysis in a laboratory and is programmable through smartphone apps and can send alarms in case of high levels of exposures beyond the predefined set point.—Leyla Nazhandali, an associate professor in the Bradley Department of Electrical and Computer Engineering and co-investigator on this project The team will evaluate the performance of iWAVE and compare it to that of conventional industrial hygiene sampling train and analytical methods during experiments in which participants perform two transportation work tasks at VTTI: heavy-truck refueling and fuel-injection mechanical maintenance. Other co-investigators of this award include Andrew Miller, research associate at the Center for Truck and Bus Safety at the Virginia Tech Transportation Institute; Andrew Alden, executive director of the I-81 Coalition at Virginia Tech Transportation Institute; Julia Gohlke, associate professor of environmental health in the Virginia-Maryland College of Veterinary Medicine; and Inyoung Kim, associate professor of statistics in the College of Science.
Topsoe launches TITAN steam reforming catalyst series with boosted reliability and efficiency
By investing in R&D and performing fundamental studies of the different carrier systems and their properties, Topsoe has developed a new and more robust carrier system. This system forms the basis for the new TITAN series of steam reforming catalysts. The series, launched earlier this month at the Nitrogen+Syngas Conference 2020, consists of RC-67 TITAN and RK-500 TITAN catalysts. The catalysts will be used in processes including the production of ammonia, dimethyl ether, formaldehyde, hydrogen, methanol and syngas. The advanced TITAN series of calcium aluminate catalysts is hibonite-rich and promoted with titanium having exceptional mechanical strength for boosting reliability and efficiency. The TITAN series offers improved performance and longer catalyst lifetime due to their hibonite-rich composition. Hibonite is a mineral with a hardness of 7.5–8.0 and a hexagonal crystal structure found in high-grade metamorphic rocks on Madagascar. Prior to the launch, 20 selected customers got to experience the excellent properties and high performance of the TITAN series, including 8% reduction in pressure drop, and 25% higher catalytic activity when compared to conventional catalysts available on the market. The hibonite-rich composition of the catalysts provides a performance boost which becomes especially evident after long operation. The seven-hole cylindrical shape yields both a very low pressure drop and a high surface area. Sudden pressure drop build-ups in syngas plants can cause unscheduled downtime and cost millions of dollars. Moreover, thermal instability during operation can lead to operational risk and reduce plant lifetime. Topsoe says that the TITAN series of steam reforming catalysts can mitigate these risks. With improved performance and better stability, the series guarantees a longer catalyst lifetime and trouble-free operation. The catalysts have high activity and low pressure drop, which ensures lower operating costs, increased profit margins, and reduced energy usage.
ADEME selects two Air Liquide hydrogen mobility projects for funding
Two hydrogen mobility projects led by Air Liquide—Hype and HyAMMED—were selected in January 2020 by ADEME (French Environment & Energy Management Agency) as part of the second closing of its “Hydrogen Mobility Ecosystems” call for proposals. Hype is developing the world’s first fleet of hydrogen-powered taxis. Launched during the 2015 United Nations Climate Change Conference (COP21) in Paris, it now has around 100 vehicles. The “2020 HYPE 600” project aims to reach the 600-taxi mark by the end of 2020. Toyota will deliver 500 additional Mirai, which will supplement the existing fleet. At the same time, HysetCo, which includes Air Liquide, Idex, Kouros, the Société du Taxi Électrique Parisien (STEP) and Toyota, will invest in local hydrogen production facilities based on electrolysis, which will make it possible to supply 3 new hydrogen stations (HRS) in addition of those already in operation. Through this project, the partners wish to demonstrate the relevance of hydrogen mobility for intensive applications such as passenger transport. HyAMMED (Hydrogen in Aix-Marseille for an Ecological and Sustainable Mobility) aims to operate hydrogen trucks for long-distance transport of goods in the South-East of France. The partners thus intend to test this heavy transport solution by using low-carbon hydrogen co-produced in the Marseille-Fos port area. The challenge of this project is to validate the maturity and reliability of this logistics transport solution. It will reduce emissions by more than 2,000 metric tons of CO2 per year, the equivalent of the annual emissions of more than 700 sedan cars. ADEME selected a total of 10 initiatives. The “Hydrogen Mobility Ecosystems” call for proposals, the first wave of which was launched by ADEME in October 2018, is part of the Hydrogen Deployment Plan for Energy Transition and aims to deploy territorial hydrogen mobility ecosystems based on fleets of commercial vehicles. According to the Ministry of Ecological and Solidarity Transition, all of the projects selected by ADEME will lead to the deployment of more than 43 hydrogen stations and 158 heavy duty vehicles.
New USGS methodology identifies 23 mineral commodities the supply of which poses greatest risk to manufacturing
Researchers at the US Geological Survey (USGS) and its partners have developed a new methodology to identify which mineral commodities important to US manufacturing are at greatest risk to supply disruption. The risk tool identified 23 mineral commodities posing the greatest risk. The methodology evaluated the global supply of and US demand for 52 mineral commodities for the years 2007 to 2016. Twenty-three mineral commodities—including some rare earth elements, cobalt, niobium and tungsten—pose the greatest supply risk for the US manufacturing sector. These commodities are vital for mobile devices, renewable energy, aerospace and defense applications, among others. Assessment of supply risk (SR) for year 2016. DP (horizontal axis), EV (vertical axis), TE (point size), and SR (point shade) are shown. For some commodities, indicator scores are rounded to avoid disclosing company proprietary data. Nassar et al. Manufacturers of new and emerging technologies depend on mineral commodities that are currently sourced largely from other countries. It’s important to understand which commodities pose the greatest risks for which industries within the manufacturing sector.— USGS scientist Nedal Nassar, lead author of the methodology The supply risk of mineral commodities to US manufacturers is greatest under the following three circumstances: US manufacturers rely primarily on foreign countries for the commodities; the countries in question might be unable or unwilling to continue to supply US manufacturers with the minerals; and US manufacturers are less able to handle a price shock or from a disruption in supply. Supply chains can be interrupted for any number of reasons. International trade tensions and conflict are well-known reasons, but there are many other possibilities. Disease outbreaks, natural disasters, and even domestic civil strife can affect a country’s mineral industry and its ability to export mineral commodities to the US.—Nedal Nassar Risk is not set in stone; it changes based on global market conditions that are specific to each individual mineral commodity and to the industries that use them. However, the analysis indicates that risk typically does not change drastically over short periods, but instead remains relatively constant or changes steadily. One thing that struck us as we were evaluating the results was how consistent the mineral commodities with the highest risk of supply disruption have been over the past decade. This is important for policymakers and industries whose plans extend beyond year-to-year changes.—Nedal Nassar For example, between 2007 and 2016, the risk for rare earth elements peaked in 2011 and 2012 when China halted exports during a dispute with Japan. However, the supply of rare earth elements consistently remained among the highest risk commodities throughout the entire study period. Heat map displaying the SR for all commodities examined for years 2007–2016. Warmer (i.e., orange to red) shades indicate a greater degree of SR. Commodities are listed in descending order of their 2007–2016 average SR and identified by cluster based on a hierarchical cluster analysis. Leading producing countries, based on primary production, are identified, and their share of world production from 2007 to 2016 is displayed in the stacked blue bars. The most vulnerable applications in 2016 are identified, and their contribution and the contribution of all other applications to a commodity’s overall EV are depicted in the stacked teal and dark teal bars, respectively. Nassar et al. In 2019, the US Department of Commerce, in coordination with the Department of the Interior and other federal agencies, published the interagency report entitled “A Federal Strategy to Ensure a Reliable Supply of Critical Minerals,” in response to President Trump’s Executive Order 13817. Among other things, the strategy commits the US Department of the Interior to improve the geophysical, geologic, and topographic mapping of the US; make the resulting data and metadata electronically accessible; support private mineral exploration of critical minerals; make recommendations to streamline permitting and review processes enhancing access to critical mineral resources. The USGS National Minerals Information Center is the source of supply and demand data for more than 90 minerals and mineral materials essential to the US economy and national security. Resources Nedal T. Nassar, Jamie Brainard, Andrew Gulley, Ross Manley, Grecia Matos, Graham Lederer, Laurence R. Bird, David Pineault, Elisa Alonso, Joseph Gambogi, Steven M. Fortier (2020) “Evaluating the mineral commodity supply risk of the U.S. manufacturing sector” Science Advances doi: 10.1126/sciadv.aay8647 (open access)
ORNL researchers use stop-light cameras to reduce fuel consumption of less-efficient vehicles via traffic management
Approximately 6 billion gallons of fuel are wasted in the US each year as vehicles wait at stop lights or sit in dense traffic with engines idling, according to US Department of Energy estimates. The least efficient of these vehicles are the large, heavy trucks used for hauling goods—they burn much more fuel than passenger cars consume when not moving. Now, researchers at Oak Ridge National Laboratory (ORNL) have designed a computer vision system—using the preexisting stop-light cameras of GRIDSMART, a Tennessee-based company that specializes in traffic-management services—that can visually identify vehicles at intersections, determine their gas mileage estimates, and then direct traffic lights to keep less-efficient vehicles moving to reduce their fuel consumption. Examples from the ORNL Overhead Vehicle Dataset, generated with images captured by GRIDSMART cameras. Image: Thomas Karnowski/ORNL The ORNL project is a first-year seed project funded by HPC4Mobility, the DOE Vehicle Technologies Office’s program for exploring energy efficiency increases in mobility systems. Proving such a system could work with current technology was a complicated puzzle that required fitting together a lot of different pieces: high-tech cameras, vehicle datasets, artificial neural networks, and computerized traffic simulations. To make such a camera-based control system work in the first place requires smart cameras placed at high-traffic intersections, able to capture images of vehicles and equipped to transmit the data. Such camera systems do exist—including one produced by GRIDSMART, a company located just a few miles from the ORNL campus in East Tennessee. GRIDSMART’s camera systems are installed in 1,200 cities globally, replacing traditional ground sensors with overhead fisheye cameras that provide horizon-to-horizon vision tracking for optimal traffic-light actuation. The bell-shaped cameras connect to processor units running GRIDSMART client software that provides municipal traffic engineers with very detailed information, from traffic metrics to unobstructed views of accidents. In addition to detecting vehicles, bicycles, and pedestrians for intersection actuation, the GRIDSMART processor counts vehicles and bicycles moving underneath the camera. For each vehicle count, we determine a length-based classification and what type of turn the vehicle made as it went through the intersection.—Tim Gee, principal computer vision engineer at GRIDSMART This data can be used to adjust intersection timings to improve the flow of traffic. Additionally, the vehicle counts can be taken into consideration when planning for construction or lane changes, as well as helping measure the effects of traffic-control changes. The team’s first step in February 2018 was to use GRIDSMART cameras to create an image dataset of vehicle classes. With GRIDSMART cameras conveniently installed on the ORNL campus, the team also employed a ground-based roadside sensor system being developed at ORNL, allowing them to combine the overhead images with high-resolution ground-level views. Once vehicle-classification labels were applied using commercial software, and DOE fuel-economy estimates added, the team had a unique dataset to train a convolutional neural network for vehicle identification. The resulting ORNL Overhead Vehicle Dataset showed that GRIDSMART cameras could indeed successfully capture useful vehicle data, gathering images of approximately 12,600 vehicles by the end of September 2018, with “ground truth” labels (makes, models, and MPG estimates) spanning 474 classifications. However, R&D staff member Thomas Karnowski of ORNL’s Imaging, Signals, and Machine Learning Group determined that these classifications weren’t numerous enough to effectively train a deep learning network—and the team didn’t have sufficient time left in their year-long project to gather more. So, where to find a larger, fine-grained vehicle dataset? Karnowski recalled a vehicle-image project by Stanford University researcher Timnit Gebru that identified 22 million cars from Google Street View images, classifying them into more than 2,600 categories (such as make and model) and then correlating them with demographic data. With Gebru’s permission, Karnowski downloaded the dataset, and the team was ready to create a neural network as the second step in the project. Gebru had used the AlexNet convolutional neural network for her project, so the team decided to try adapting it, too. We got the same neural network and retrained it on her data and got very similar results to what she got—the difference is that we then used it to estimate fuel consumption by substituting vehicle types with their average fuel consumption, using DOE’s tables. That was a bit of an effort, too, but that’s what it’s all about.—Thomas Karnowski The team produced another neural network for comparison using the Multinode Evolutionary Neural Networks for Deep Learning (MENNDL), a high-performance computing software stack developed by ORNL’s Computational Data Analytics Group. A 2018 finalist for the Association for Computing Machinery’s Gordon Bell Prize and a 2018 R&D 100 Award winner, MENNDL uses an evolutionary algorithm that not only creates deep learning networks but also evolves network design on the fly. By automatically combining and testing millions of “parent” networks to produce higher-performing “children,” MENNDL breeds optimized neural networks. Using Gebru’s training dataset, Karnowski’s team ran MENNDL on the now-decommissioned Cray XK7 Titan—once rated as the most powerful supercomputer in the world at 27 petaflops—at the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility at ORNL. Karnowski said that while MENNDL produced some novel architectures, its network’s classification results didn’t supersede the accuracy of the team’s AlexNet-derived network. With additional time and image data for training, Karnowski believes MENNDL could have produced a more optimal network, but the team was nearing its deadline. Lacking an available city-wide grid of intersections equipped with GRIDSMART traffic lights, Karnowski’s team instead turned to computer simulations to test their system. Simulation of Urban MObility (SUMO) is an open-source simulation suite that enables researchers to model traffic systems, including vehicles, public transportation, and even pedestrians. SUMO allows for custom models, so Karnowski’s team was able to adapt it to their project. Adding a “visual sensor model” to the SUMO simulation environment, the team used reinforcement learning to guide a grid of traffic-light controllers to reduce wait times for larger vehicles. In a real GRIDSMART system, they just send vehicle data to a controller, and it says, ‘I’ve got cars waiting, so it’s time to change the light.’ In our proof-of-concept system, that information would then be fed to a controller that can look at multiple intersections and try to say, ‘We’ve got high-consumption vehicles coming in this direction, and lower-consumption vehicles in this other direction—let’s change the light timing so we favor the direction where there’s more fuel consumption.’—Thomas Karnowski The method was tested under a variety of traffic scenarios designed to evaluate the potential for fuel savings with visual sensing. In particular, some scenarios with heavy truck usage suggested savings of up to 25% in fuel consumption with minimal impact on wait times. In other scenarios, the simulated system was trained with heavy truck usage but evaluated on more balanced test-traffic conditions. The savings are not quantified, but the trained reinforcement learning control easily adapted to the new conditions. All these test cases were limited to establish proof-of-concept, and more work is needed to accurately assess the impact of this approach. Karnowski hopes to continue developing the system with larger datasets, improved classifiers, and more expansive simulations. GRIDSMART considers the project’s results to foreshadow promising new services for their customers. Work was funded by the Vehicle Technologies Office’s HPC4Mobility seed project program of the US Department of Energy’s Office of Energy Efficiency and Renewable Energy. Resources Karnowski, R. Tokola, S. Oesch, M. Eicholtz, J. Price, and T. Gee, “Estimating Vehicle Fuel Economy from Overhead Camera Imagery and Application for Traffic Control.” Paper presented at IS&T International Symposium on Electronic Imaging Science and Technology, Burlingame, CA, 26-30 January 2020 doi: 10.2352/ISSN.2470-1173.2020.6.IRIACV-070 (open access)
Porsche opens Europe’s most powerful rapid-charging park in Leipzig; 7MW, all renewable energy
Porsche Leipzig is expanding the charging infrastructure for electric vehicles in central Germany with a new charging park called Porsche Turbo Charging. The total capacity of the facility, which includes six internal quick charging points, is 7 MW. Porsche Leipzig currently has Europe’s most powerful rapid-charging park, which is operated entirely with electricity from renewable energy sources. Porsche Turbo Charging, Rapid-charging park, Leipzig Twelve rapid charging points with 350 kW (direct current) and four charging points with 22 kW (alternating current) are now in operation at the customer center, running seven days a week, around the clock and for customers of all vehicle brands. During a pilot phase that is running until the end of March, rapid charging will be free of charge for all users. After that, payment will be made using the mobility providers’ standard charging cards, according to their respective conditions. The new charging park between the number 9, 14 and 38 motorways will significantly enrich the charging infrastructure in central Germany. Electric and hybrid vehicles of all brands are welcome. We are pleased that with the new charging park we can offer an attractive charging option for electric vehicle owners in Leipzig and the surrounding area, as well as transit passengers.—Gerd Rupp, Chairman of the Board of Management of Porsche Leipzig GmbH The rapid Porsche Turbo Charger charging point was developed by Porsche Engineering and sets new standards in terms of charging time: depending on the vehicle model, up to 100 kilometers can be charged in just five minutes. All vehicles with a Combined Charging System connection (CCS2) can use the fast charging function. Visitors who want to charge their vehicle at Porsche can reach the charging station at the customer center via the visitor gate in Porschestraße near the Leipzig-Nord motorway exit. During waiting times, charging customers can use the services of the Porsche Customer Center, including a historical vehicle exhibition and shop. They can also book a range of driving experiences available at the Leipzig circuit. The Porsche plant in Leipzig is currently getting ready for electric mobility. Among other things, a further body shop for the next generation of the Macan is being built at the plant, which will roll off the production line as a purely electrically powered model series. Electric drives are already playing a role at Leipzig: the Panamera hybrid models are produced there and Taycan customers can collect their car in person from Leipzig and enjoy tailored instruction on the FIA-certified circuit.
Eurasian Resources Group plans NCM material plant for EV batteries
Eurasian Resources Group (ERG), a leading diversified natural resources group, is assessing the construction of a battery material plant to produce nickel-cobalt-manganese (NCM) precursor materials for batteries for electric vehicles (EVs). The Group is evaluating technical solutions offered by engineering firms BGRIMM Technology Group from China and Outotec from Finland, which will allow for the production of both NCM 6:2:2 and NCM 8:1:1 precursors depending on market conditions. The Group is planning to develop the plant in two phases. The first phase is expected to produce 90,000 tonnes of NCM annually following a two-year construction period. The expansion will be defined depending on market conditions. Our vision for a green economy is at the core of our continued commitment to supply the most critical materials for the global battery sector and we are leading industry efforts to ensure the sustainable, traceable cobalt sourcing in supply chains across Europe, North America, South Korea and Japan. Together with our partners we are currently considering multiple locations for the development of the precursor plant.—Benedikt Sobotka, CEO of Eurasian Resources Group The precursor plant will be exclusively supplied with cobalt hydroxide from ERG’s Metalkol RTR in the Democratic Republic of the Congo (DRC), whose operations are in accordance with recognized responsible and sustainable practices as set out in the ERG Clean Cobalt Framework. Metalkol RTR is a historic tailings reclamation and environmental restoration facility producing high quality copper cathode and cobalt in hydroxide. It is positioned to become one of the largest producers of cobalt globally upon completion of its Phase II expansion. For the precursor plant the Group plans to source nickel sulfate from third parties or produce it itself using nickel raw materials Mixed Hydroxide Precipitate (MHP) or Mixed Sulfide Precipitate (MSP).
AXYARD, Lab1886 and Daimler Trucks automate the operation of commercial vehicles
The automated snow removal by two self-driving Mercedes-Benz Arocs in Immendingen shows a successful application for automated commercial vehicles in closed areas. The joint project of Lab1886, the innovation unit for new business models within Mercedes-Benz AG, and Daimler Truck AG has now become a product that can be used as a solution for various customer requirements in sectors such as on-site logistics and agriculture. Lab1886 and Daimler Trucks, together with Fraport AG, demonstrated the operation of self-driving snow-clearing vehicles in non-public closed areas for the first time in October 2017 as part of a pilot project on the site of the former Pferdsfeld air base. The in-house operation in Immendingen, which has now been started, is based on the findings of this project. A self-driving Mercedes-Benz Aroc in use at the automated snow removal in Immendingen. For this purpose, the approximately 20 hectares (49 acres) of test areas must always be free of snow, ice and water. To ensure this every day at the start of the tests in the morning, two self-driving Mercedes-Benz Arocs are in use overnight. Trained specialists supervise the trucks on site. Depending on the snow conditions, the vehicle’s lane is determined and adhered to with centimeter-level precision. In this way, the roadway is precisely cleared along gravel beds. The automated control of the clearing devices as well as the clearing strategies were developed in cooperation with the device manufacturer Aebi-Schmidt. Automated snow removal is one of many applications of AXYARD, the technology product jointly developed by Lab1886 and Daimler Trucks. AXYARD stands for automated solutions (A=automated) that are used in various use cases (X) in closed terrain (YARD). AXYARD’s approach is to automate Mercedes-Benz trucks by equipping them with sensors and ECUs. This allows them to complete predefined routes on closed terrain and be digitally conducted, monitored and orchestrated in a central control system—completely driverless. At the heart of AXYARD technology is Remote Truck Interface (RTI). With RTI, vehicle functions can be operated remotely and data can be exchanged. This also works in a network of several vehicles. The vehicles are equipped with a high-precision GPS location (DGPS, differential GPS) and have state-of-the-art vehicle-to-vehicle communication (V2V). Due to the interaction of the innovative interface RTI as well as the control and remote control unit, an extremely fast and not least secure data exchange between vehicles and the infrastructure of the test site takes place. To make this work in real time, a complete data exchange takes place every 0.1 seconds between the vehicles and the main control unit of the RTI. We focus on two specific use cases for automated driving: regular use of the highway and motorway, as well as on journeys in cordoned-off areas, such as “gated areas”, e.g. with automated snow clearing vehicles on the site of the former Pferdsfeld air base and now on the test track in Immendingen or at the Brazilian sugar cane harvest.—Dr. Christian Ballarin, Head of Advanced Engineering for Driver Assistance Systems, Autonomous Driving and Connectivity at Daimler Trucks With regard to automated driving in regular motorway traffic, Daimler Trucks offers the Mercedes-Benz Actros, the Freightliner Cascadia and the FUSO Super Great as the world’s first manufacturer of semi-automated vehicles (SAE Level 2) ex-factory. At the same time, the Autonomous Technology Group at Daimler Trucks is driving the development of highly automated trucks (SAE Level 4). The aim is to bring this technology into the series by the end of the decade. The testing on public highways in the US, which started in autumn 2019, is an important step in this direction. In addition to the use in the snow in Immendingen, automated trucks from Mercedes-Benz have also been reliably helping to harvest sugar cane in everyday use in the Brazilian sugar cane harvest since 2018.
Volvo 48V MHEV powertrain now available on all models
In a broad portfolio upgrade, Volvo Cars announced that its 48-volt mild-hybrid powertrain options are now available on every Volvo model, further boosting the company’s electrified offerings. Introduced on the XC90 and XC60 SUVs last year, the mild hybrids are now also available on all other 90- and 60-series cars, as well as on the XC40. The mild-hybrid powertrain options on the V90 Cross Country represent the first electrified variants in the history of the Cross Country range. Volvo Cars’ mild hybrids offer drivers up to 15% fuel savings and emission reductions in real-world driving. The brake-by-wire system interacts with the energy recovery system and reduces fuel consumption and emissions by recovering kinetic energy under braking. Volvo Cars also introduced refreshed versions of the S90 and V90 estate, including a refined exterior design and a brand-new, state-of-the-art sound system by Bowers & Wilkins. In terms of exterior design, Volvo designers have introduced a number of refinements on both the front and rear of the S90 and V90, including new foglights, a new spoiler design and a new lower front bumper. On the V90, the most striking feature is a brand-new rear light design, including full LED-powered signature lighting and a sequential turn indicator. Another new feature inside is an Advanced Air Cleaner with a PM2.5 particle sensor. First developed for the Chinese market and now rolled out globally, it allows drivers to monitor interior air quality via the centre screen. If desired, the Advanced Air Cleaner can clean the cabin air of almost all tiny particles within a few minutes. Both the new Bowers & Wilkins audio system and the Advanced Air Cleaner technology are now available on all 90 and 60 series models based on the Scalable Product Architecture (SPA) platform. All models in the 90 and 60 series now also come with double USB-C charging points in the rear, replacing the 12-volt outlet. The wireless charging functionality for smartphones, first introduced on the XC40 compact SUV, is now also available on most variants in the 90 and 60 series.
USDA Ag Innovation Agenda targets biofuel blend rates of 15% in 2030, 30% in 2050
US Secretary of Agriculture Sonny Perdue announced the Agriculture Innovation Agenda, a department-wide initiative to align resources, programs, and research to position American agriculture to better meet future global demands. Specifically, the US Department of Agriculture (USDA) will stimulate innovation so that American agriculture can achieve the goal of increasing production by 40% while cutting the environmental footprint of US agriculture in half by 2050. The first component of the Ag Innovation Agenda is to develop a US ag-innovation strategy that aligns and synchronizes public and private sector research. Research areas of focus include genome design; digitalization and automation; prescriptive intervention; and systems-based farm management. The second component is to align the work of USDA customer-facing agencies and integrate innovative technologies and practices into USDA programs. The third component is to conduct a review of USDA productivity and conservation data. USDA already closely tracks data on yield, but on the environmental side, there’s some catching up to do. Finally, USDA has set benchmarks; these targets will help measure progress toward meeting the food, fiber, fuel, feed, and climate demands of the future. The benchmarks include: Food loss and waste: Advance our work toward the United States’ goal to reduce food loss and waste by 50% in the United States by the year 2030. Carbon Sequestration and Greenhouse Gas: Enhance carbon sequestration through soil health and forestry, leverage the agricultural sector’s renewable energy benefits for the economy, and capitalize on innovative technologies and practices to achieve net reduction of the agricultural sector’s current carbon footprint by 2050 without regulatory overreach. Water Quality: Reduce nutrient loss by 30 percent nationally by 2050. Renewable Energy: Increase the production of renewable energy feedstocks and increase biofuel production efficiency and competitiveness to achieve market-driven blend rates of 15% of transportation fuels in 2030 and 30% of transportation fuels by 2050. Growth Energy CEO Emily Skor praised USDA’s initiative and its recognition of the role that homegrown biofuels have in achieving the department’s goals: We applaud USDA for setting these clear goals for E15 and E30, and Growth Energy’s members are ready to deliver ahead of their timetable. Biofuels are a critical piece of meeting the demands of our future transportation needs while lowering our carbon footprint. Today’s recognition by USDA and Secretary Purdue’s unwavering support will help drive biofuel innovation in the coming years and decades. We look forward to continuing our longstanding working relationship with USDA to ensure that Americans across the country have expanded access to cleaner fuels like E15 and E30 at the pump.
Researchers develop organic semiconductor photocatalyst with enhanced hydrogen evolution
Currently, most hydrogen evolution photocatalysts (HEPs) are made from single-component inorganic semiconductors. These can only absorb light at ultraviolet wavelengths—constituting less than 5% of the solar spectrum—which limits their efficiency. However, photocatalysts formed from a single organic semiconductor typically suffer from inefficient intrinsic charge generation, which leads to low photocatalytic activities. Now, a team led by Iain McCulloch from the KAUST Solar Center, in partnership with researchers from the United States and the United Kingdom, has developed HEPs made from two different semiconducting materials. They incorporated these materials into organic nanoparticles that can be tuned to absorb more of the visible light spectrum. The resulting photocatalysts display an unprecedentedly high hydrogen evolution rate of more than 60,000 μmol h−1 g−1 under 350 to 800 nm illumination, and external quantum efficiencies more than 6% in the region of maximum solar photon flux. A paper on their work appears in Nature Materials. The team first used a method called miniemulsion, in which a solution of the organic semiconductors is emulsified in water with the aid of a stabilizing surfactant. Next, they heated the emulsion to drive off the solvent, leaving behind surfactant-stabilized organic semiconductor nanoparticles. By varying the surfactant, they were able to control the structure of the nanoparticles, transforming them from a core-shell structure to a mixed donor/acceptor structure. The blended structure allowed them to introduce a heterojunction between the layers of the donor polymer and nonfullerene acceptor. Both structures absorb light at the same rate, but in the core-shell structure, only photogenerated holes reach the surface; however, in the mixed structure, both holes and electrons reach the surface of the nanoparticles, resulting in enhanced generation of hydrogen.—Jan Kosco, first an co-corresponding author The HEPs exhibited hydrogen evolution rates an order of magnitude beyond what is currently achievable with single-component inorganic HEPs. We are currently studying the performance of nanoparticles formed from different blends of semiconductors to better understand their structure-activity relationships. We are looking to design nanoparticle photocatalysts for other photocatalytic reactions, such as oxygen evolution or carbon dioxide reduction.—Iain McCulloch, senior and co-corresponding author Resources Kosco, J., Bidwell, M, Hyojung, C., Tyler, M., Howells, C.T., Sachs, M., Anjum, D.H., Lopez, S.G., Zou, L., Zhan, L., Tellam, J., Sougrat, R., Laquai, F., Delongchamp, D.M., Durrant, J.R. & McCulloch, I. (2020) “Enhanced photocatalytic hydrogen evolution from organic semiconductor heterojunction nanoparticles.” Nature Materials doi: 10.1038/s41563-019-0591-1
Si-dominant Li-ion company Enevate targeting power tool market
Enevate, a pioneer in advanced silicon-dominant lithium-ion (Li-ion) battery technology capable of high energy density and fast charging for electric vehicles (EV), is applying its battery solutions to advanced power cells for the power tool market and other high power applications. For example, in a 21700 cylindrical power cell, 5.9Ah can be achieved utilizing Enevate technology, far exceeding the capacity of other power cells in the market, which today averages 4Ah. Enevate developed the power cell to be capable of high energy density, low temperature operation, and both high discharge and charge rates, allowing very short recharge times of depleted batteries which power cells today cannot achieve. Battery powered power tools are an important and large market segment, and Enevate’s battery technology is extremely well-suited to serve this market. Power tool users, especially in areas such as the home, industrial, and business construction, need portable power tools with longer battery runtimes and the ability to work in cold temperatures. The Li-ion battery technology we’ve developed is especially well-suited for fast discharge and longer runtimes through increased energy density, enabling power tool users more and longer productive work time between charges. We have developed cylindrical cell designs that use the fundamental nature of our inexpensive and scalable silicon-dominant battery chemistry.—Dr. Benjamin Park, Enevate Founder and Chief Technology Officer Park noted that opportunities to serve the power tool market will happen sooner—in the next year or two—than the longer-lead electrical vehicle (EV) battery market, in which Enevate is preparing its pioneering technology for 2024-2025 EV model years. Enevate’s power cell has been tested at up to 10C sustained discharge rates. Also, power tools must have the ability to operate in cold climates outdoors; Enevate’s power tool cell is able to operate down to -20 °C and has excellent low temperature cycle life. The vast majority of the power cells on the market are cylindrical cells, which can be supported by Enevate technology. Power cells using Enevate’s technology can be wound as cylindrical cells, or made as pouch or prismatic can cells. Enevate’s fourth-generation XFC-Energy battery technology (earlier post) can charge 75% of the total cell capacity in five minutes at 10C charge rates. Typical power cells today can only charge at about one-sixth of the rate of Enevate cells, resulting in a charge time that is six times longer. Other highlights of the fourth-generation XFC-Energy technology include: Cell technology scalable for large-format pouch, prismatic and cylindrical EV cells suitable for various battery module and pack architectures. Achieves 800 Wh/L and 340 Wh/kg in large-format EV cells. Pure silicon-dominant anode technology tunable with 10-60µm thickness and 1000-2000mAh/g that can be paired with NCA, NCM811, NCMA, low-cobalt, or other advanced cathode technologies. Continuous roll-to-roll anode manufacturing processes designed and capable of achieving more than 80 meters per minute electrode production, more than 10 GWh per electrode production line, with pure silicon anode rolls greater than 1 meter wide and longer than 5 kilometers in length sufficient for high volume gigafactory production, among other features. Lower anode material cost (dollar per kWh) than conventional and synthetic graphite. The Irvine, California-based company has raised more than $110 million from investors including Renault-Nissan-Mitsubishi (Alliance Ventures), LG Chem, Samsung, Mission Ventures, Draper Fisher Jurvetson, Tsing Capital, Infinite Potential Technologies, Presidio Ventures – a Sumitomo Corporation company, Lenovo, CEC Capital and Bangchak.
Plug Power partners with Lightning Systems on hydrogen fuel-cell-powered Class 6 trucks for logistics industry; “middle-mile” solution
Plug Power Inc. is partnering with Colorado-based Lightning Systems, a global developer of zero-emission drivetrains. This collaboration enables both companies to offer the first electric, fuel-cell-powered Class 6 trucks (up to 12.5 tons) capable of supporting middle-mile delivery logistics between warehouses and distribution centers. The electric commercial trucks produced by the partnership will be powered by an integrated hybrid-electric drivetrain consisting of Plug Power’s ProGen fuel cell engines coupled with Lightning Systems’ electric vehicle drivetrain and batteries. Lightning Systems also will offer customers advanced diagnostics and analytics powered by its artificial neural network technology. This technology enables customers easily to track vehicle and fuel cell system data for analysis, driver training, and route optimization. Plug Power provides the world’s largest service and support network of certified fuel-cell service technicians deployed throughout North America. Final production and testing of the new vehicles will be completed at Plug Power’s headquarters in Latham, New York, before they are made commercially available to the public in the third quarter of 2020. Plug Power and Lightning Systems will deliver both standard and long-range Class 6 trucks through their partnership, taking full advantage of the value that fuel cells offer in commercial fleets where high utilization, long range, fast fueling, and maximization of cargo volume and payload are important. Plug Power’s ProGen engines provide 90 kW of fuel cell power and utilize the latest generation of the company’s proprietary MEA and metal plate stack technology, which delivers industry-leading power density. The standard vehicle offering includes 20kg of on-board hydrogen storage, delivering average range (for typical route profiles) in excess of 200 miles. An extended range option is also available, effectively doubling the standard average range to 400 miles. Lightning’s modular powertrains were designed to support both battery-electric and fuel cell-electric vehicle configurations, so this is a natural next product for us. Plug Power’s hydrogen fuel cell system dovetails elegantly with our existing technology.—Tim Reeser, CEO for Lightning Systems
Chevrolet launches Menlo EV in China
Chevrolet has launched the Menlo, the brand’s first fully electric vehicle in China. (Earlier post.) Initially being offered in Beijing, the Chevrolet Menlo is available in four variants priced from RMB 159,900 (US$22,800) to RMB 179,900 (US$25,600) after national subsidies for new energy vehicles. The Chevrolet Menlo incorporates GM’s class-leading battery technology and a new-generation highly efficient pure electric drive system that generates 110 kW of maximum power and 350 N·m of maximum torque, with electricity consumption of 13.1 kWh/100 km. The vehicle has a constant-speed range of up to 410 km (255 miles) under New European Driving Cycle (NEDC) conditions on a single charge. Its battery can be fully charged to 80% of capacity within 40 minutes using a direct current (DC) fast charger. The Chevrolet Menlo has three driving modes and three energy recovery modes. The economical, normal and sporty driving modes support base acceleration, standard acceleration and enhanced acceleration depending on users’ preferences. The energy recovery modes of light free recovery, medium efficient recovery and strong energy recovery likewise support personal preferences for a balance between driving performance and energy consumption. In addition, the Chevrolet Menlo received certification for meeting Automotive Safety Integrity Level (ASIL) D—the highest integrity requirement for vehicles. Advanced Connectivity and Safety. The Chevrolet Menlo features the new-generation MyLink+ infotainment system with OnStar. It not only supports over-the-air (OTA) updates, Apple CarPlay and Baidu CarLife, but also offers functions such as virtual car key, remote control and intelligent voice recognition. Menlo’s advanced technologies include Bosch’s 9.3 Electronic Stability Program (ESP), Forward Collision Alert (FCA), Lane Departure Warning (LDW), Side Blind Zone Alert (SBZA), Automatic Parking Assist (APA), Following Distance Indicator (FDI) and the Tire Pressure Monitoring System (TPMS). Customers are entitled to 100G of free OnStar 4G LTE data service every year and a quality assurance warranty of eight years or 160,000 km for the battery, motor and electric control systems. The warranty remains effective if the vehicle’s ownership changes, ensuring high residual value.
GM enhancing Energy Assist app for EVs
General Motors is making enhancements to Energy Assist, a standard feature available in the myChevrolet mobile app for Bolt EV owners. Energy Assist, first available for customers in 2017, currently enables Bolt EV owners to plan and manage their routes more effectively, locate available charging stations both along their route and in the area, monitor their route, and receive real-time alerts if their range projections change dramatically. Energy Assist is integrated with data from the vehicle, which enables intelligent planning and precise charge time predictions. Energy Assist enhancements include: Dynamic Data Integration. GM is now displaying dynamic data from charging networks EVgo and ChargePoint within Energy Assist, so Bolt EV owners can have a more seamless charging experience with their GM vehicles. Information provided by charging networks includes real-time data on charge station status to indicate if a charging station is available. GM will integrate dynamic data from additional charging providers throughout 2020, which will include EV Connect continuing to enhance the customer experience. Start-to-Charge. At eligible charging stations, owners can now link their EVgo account to activate and pay for charging sessions right from the myChevrolet mobile app, eliminating the need to toggle between apps and streamline the payment process. Eligible charging stations are noted within the myChevrolet mobile app. GM will continue to add eligible charging stations throughout 2020. More Than 40,000 Stations. Energy Assist provides Bolt EV owners access to all Bolt EV-compatible charging station locations, regardless of the charge point operator. EV owners can now view more than 40,000 charging stations in North America, with access to 30 percent more DC Fast Chargers compared to 2019. Review and Rate. With crowdsourcing on the rise, GM is implementing a new feedback feature for Bolt EV owners. Coming in early 2020, Bolt EV owners will be able to review and rate charging stations within the myChevrolet app. Similar to other popular crowdsourcing technologies, this feature will rely on Bolt EV owners to share their valuable insights about charging stations by providing a star rating and leaving comments about the station. Original purchasers of new Bolt EVs have access to the Energy Assist features in the myChevrolet mobile app at no additional cost for five years from the vehicle delivery date, after they accept the myChevrolet mobile app terms. Energy Assist is available for Bolt EV owners in the US, Canada and Mexico. Earlier this year, GM announced that the Detroit-Hamtramck assembly plant will be GM’s first plant 100% devoted to electric vehicles, and will build the new GMC HUMMER EV with initial availability in fall 2021. In 2019, GM announced a collaboration with LG Chem to mass produce battery cells for future battery-electric vehicles, and with Qmerit to create a more accessible at-home charging solution.
Workhorse Group to unveil new C650 electric step van at NTEA Work Truck Show
Workhorse Group will display its newly-designed C650 all-electric step van at the NTEA Work Truck Show, 4-6 March in Indianapolis, Indiana. The company‘s new C650 and C1000 step vans will are 650 ft3 and 1000 ft3 vehicles both weighing approximately 12,500 lbs (5,670 kg) when fully loaded. Through a lightweight, composite, monocoque construction method, Workhorse has significantly decreased their vehicles’ curb weights when compared to legacy company models, while still providing the same cargo volume capacity. Workhorse C Series vehicles are powered by a modular battery pack system, which provides between 35 kilowatt hours (kWh) when equipped with two battery packs and 70 kWh in its standard four pack configuration, empowering customers to choose the right energy requirement for specific duty cycles. Depending on the size of battery pack installation, range is expected to be between 100 and 150 miles (161 to 241 km) on a single charge, while achieving approximately 53 miles per gallon gasoline equivalent (MPGe). Workhorse also currently has the only patent approved for a delivery-truck-mounted drone system, which has been shown to further increase last mile efficiency. A combination of lightweight design, modular battery pack, and a 4-wheel independent suspension system with rear air shocks makes our new C650 unlike any electric vehicle on the market.—Duane Hughes, Workhorse CEO
Toyota and Toyota Industries announce new battery for hybrid electric vehicles
Toyota Motor Corporation and Toyota Industries Corporation announced that they have jointly developed a new battery for hybrid electric vehicles (HEV) in anticipation of the further development and market introduction of HEVs, which are forecasted to expand rapidly in the future. The companies said they will release information such as target vehicle models as well as battery specifications and performanc prior to equipping Toyota HEVs with the new batteries. To meet the demand for increased production of Toyota HEVs, the production of the new batteries will take place at Toyota Industries’ Kyowa Plant (Obu-shi, Aichi Prefecture) and at a site on company property located adjacent to their Higashiura Plant (Higashiura-cho, Chita-gun, Aichi Prefecture). In the future, Toyota Industries will work with Toyota to build and strengthen the supply structure.
Study finds cobalt supply can meet demand for EVs and electronics batteries through 2030
A study by a team from MIT, with colleagues from Alfred University, UC Berkeley, and RIT, has found that supplies of cobalt—a critical material in some battery chemistries—is adequate in the short-term (up to 2030), but that the industry needs to invest in additional efficient refining and recycling capacity, so it can continue to meet demand. The paper is published in the ACS journal Environmental Science & Technology. Roughly 60% of mined cobalt is sourced from the Democratic Republic of Congo (DRC). The element is often recovered as a byproduct from mining copper and nickel, meaning that demand and pricing for those other metals affects the availability of cobalt. Half of the current supply of cobalt is incorporated into cathodes for lithium-ion batteries, and many of those batteries are used in consumer electronics and electric vehicles. Demand for these vehicles and their batteries is growing swiftly: In 2018, the global electric car fleet numbered in excess of 5.1 million, up 2 million from the prior year, according to the International Energy Agency. To determine potential cobalt supply and demand through 2030, the researchers analyzed variables, including electric vehicle demand; cobalt mining, refining and recycling capacity; battery chemistry trends; socioeconomic and political trends; and the feasibility of substituting other materials for cobalt. These variables could be affected by political instability in DRC, policy decisions favoring electric vehicles, disruptions in China (which refines around half of the cobalt supply), and fluctuations in copper and nickel prices. They found that cobalt demand is estimated to range from 235 to 430 ktonnes in 2030. This upper bound on cobalt demand corresponds to 280% of world refinery capacity in 2016. They estimated supply from scheduled and unscheduled production as well as secondary production to range from 320 to 460 ktonnes. Their analysis suggests: The price of cobalt will remain relatively stable in the short term, given that the range suggests even a supply surplus; Future cobalt supply will become more diversified geographically and mined more as a byproduct of nickel (Ni) over this period; and For future demand to be met, attention should be paid to sustained investments in refined supply of cobalt and secondary recovery. The authors received funding from the National Science Foundation and the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under the US Department of Energy. Resources Xinkai Fu, Danielle N. Beatty, Gabrielle G. Gaustad, Gerbrand Ceder, Richard Roth, Randolph E. Kirchain, Michele Bustamante, Callie Babbitt, and Elsa A. Olivetti (2020) “Perspectives on Cobalt Supply through 2030 in the Face of Changing Demand” Environmental Science & Technology doi: 10.1021/acs.est.9b04975
New machine learning method from Stanford, with Toyota researchers, could accelerate battery development for EVs
At every stage of the battery development process, new technologies must be tested for months or even years to determine how long they will last. Now, a team led by Stanford professors Stefano Ermon and William Chueh has developed a machine learning-based method that slashes these testing times by 98%. The study is published in the journal Nature. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. —Attia et al. Schematic of the closed-loop optimization (CLO) system. First, batteries are tested. The cycling data from the first 100 cycles (specifically, electrochemical measurements such as voltage and capacity) are used as input for an early outcome prediction of cycle life. These cycle life predictions from a machine learning (ML) model are subsequently sent to a BO algorithm, which recommends the next protocols to test by balancing the competing demands of exploration (testing protocols with high uncertainty in estimated cycle life) and exploitation (testing protocols with high estimated cycle life). This process iterates until the testing budget is exhausted. In this approach, early prediction reduces the number of cycles required per tested battery, while optimal experimental design reduces the number of experiments required. A small training dataset of batteries cycled to failure is used both to train the early outcome predictor and to set BO hyperparameters. In future work, design of battery materials and processes could also be integrated into this closed-loop system. Attia et al. The study was part of a larger collaboration among scientists from Stanford, MIT and the Toyota Research Institute that bridges foundational academic research and real-world industry applications. The goal: finding the best method for charging an EV battery in 10 minutes that maximizes the battery’s overall lifetime. The researchers wrote a program that, based on only a few charging cycles, predicted how batteries would respond to different charging approaches. The software also decided in real time what charging approaches to focus on or ignore. By reducing both the length and number of trials, the researchers cut the testing process from almost two years to 16 days. Although the researchers focused on the testing process for extreme fast charging, the method can be applied to many other problems that are holding back battery development for months or years, said Peter Attia, who co-led the study while he was a graduate student. Designing ultra-fast-charging batteries is a major challenge, mainly because it is difficult to make them last. The intensity of the faster charge puts greater strain on the battery, which often causes it to fail early. To prevent this damage to the battery pack—a component that accounts for a large chunk of an electric car’s total cost—battery engineers must test an exhaustive series of charging methods to find the ones that work best. The new research sought to optimize this process. At the outset, the team saw that fast-charging optimization amounted to many trial-and-error tests—something that is inefficient for humans, but the perfect problem for a machine. The team used this power to their advantage in two key ways. First, they used it to reduce the time per cycling experiment. In a previous study, the researchers found that instead of charging and recharging every battery until it failed—the usual way of testing a battery’s lifetime—they could predict how long a battery would last after only its first 100 charging cycles. This is because the machine learning system, after being trained on a few batteries cycled to failure, could find patterns in the early data that presaged how long a battery would last. Second, machine learning reduced the number of methods they had to test. Instead of testing every possible charging method equally, or relying on intuition, the computer learned from its experiences to quickly find the best protocols to test. By testing fewer methods for fewer cycles, the study’s authors quickly found an optimal ultra-fast-charging protocol for their battery. In addition to significantly speeding up the testing process, the computer’s solution was also better—and much more unusual—than what a battery scientist would likely have devised, said Ermon. Instead of charging at the highest current at the beginning of the charge, the algorithm’s solution uses the highest current in the middle of the charge. The researchers said their approach could accelerate nearly every piece of the battery development pipeline: from designing the chemistry of a battery to determining its size and shape, to finding better systems for manufacturing and storage. This would have broad implications not only for electric vehicles but for other types of energy storage, a key requirement for making the switch to wind and solar power on a global scale. This is a new way of doing battery development. Having data that you can share among a large number of people in academia and industry, and that is automatically analyzed, enables much faster innovation.—Patrick Herring, co-author and a scientist at the Toyota Research Institute The study’s machine learning and data collection system will be made available for future battery scientists to freely use, Herring added. By using this system to optimize other parts of the process with machine learning, battery development—and the arrival of newer, better technologies—could accelerate by an order of magnitude or more, he said. This work was supported by Stanford, the Toyota Research Institute, the National Science Foundation, the US Department of Energy and Microsoft. Resources Attia, P.M., Grover, A., Jin, N. et al. (2020) “Closed-loop optimization of fast-charging protocols for batteries with machine learning.” Nature 578, 397–402 doi: 10.1038/s41586-020-1994-5
US DOE to award up to $100M over five years for solar fuels research
The US Department of Energy (DOE) plans to provide up to $100 million over five years for research on artificial photosynthesis for the production of fuels from sunlight. (DE-FOA-0002254) The funding will support the establishment of one large or possibly two smaller DOE Energy Innovation Hubs: integrated multidisciplinary, multi-institutional research teams aimed at accelerating the fundamental scientific breakthroughs needed to enable solar fuel production. While several approaches could potentially enable fuel production using sunlight as the only energy input, the new FOA focuses solely on artificial photosynthesis approaches: the direct use of sunlight, water, and abundant feedstocks for liquid fuel production. Sunlight is our most basic energy source, and the ability to generate fuels directly from sunlight has the potential to transform our energy economy and vastly enhance US energy security.—Under Secretary for Science Paul Dabbar Plants use photosynthesis to convert energy from the sun into energy-rich chemical fuels using water and carbon dioxide. The goal of the research is to develop an artificial photosynthesis system that, like natural photosynthesis, would generate usable fuels directly from sunlight, carbon dioxide, and water. However, significant scientific barriers remain to the development of such a system, requiring new discoveries and fundamental breakthroughs. The Department’s planned investment in the Fuels from Sunlight Hub program represents a continuing large-scale commitment of US scientific and technological resources to this competitive and promising area of investigation. Proposed research is expected to build on the capabilities and accomplishments developed to date by the solar fuels research community, including work by the DOE Office of Science-supported Joint Center for Artificial Photosynthesis, Energy Frontier Research Centers, and core research programs. Applications are asked to focus on research priorities identified by the Roundtable on Liquid Solar Fuels held in August 2019 by the Office of Basic Energy Sciences within DOE’s Office of Science. These priorities include: Understand the mechanisms that underpin constituent durability and performance. A current impediment to producing solar fuels is the limited lifetime of components. Significant opportunities exist to design, discover, and develop highly performing and durable components, including robust light absorbers with sufficient photovoltages; efficient, stable catalysts with high selectivity; and tailored materials such as membranes and electrolytes to control transport and permeability. A detailed understanding of the thermodynamics, kinetics, and mechanisms of degradation will enable predictive science for durability at the molecular, material, and component levels. New science will also advance strategies to circumvent or counteract processes that reduce component lifetime and performance. Control the catalyst microenvironment to promote selective and efficient fuel production. High selectivity and high activity in the light-driven production of energy-rich fuels present considerable challenges because of the complexity of chemically reducing CO2 and N2 as well as oxidizing H2O. Advances require molecular-level understanding and control of the microenvironment around catalytic sites to direct reactions for key bond-making and bond-breaking steps. Research is needed to probe and control the interactions of catalysts with supports, light absorbers, electrolytes, and other components. It is also critical to understand how the microenvironment can mediate the transport of reactants, products, electrons, protons, and inhibitors to direct reaction pathways determining efficiency, selectivity, and degradation. Bridge the time and length scales of light excitation and chemical transformations. Most approaches to solar fuels generation decouple light absorption and chemical transformations. Significant opportunities exist to capitalize on the direct coupling of light-driven phenomena and chemical processes to enhance overall system performance. Exploiting light–matter interactions could open up new mechanisms to enable selectivity or efficiency that outperform conventional electrochemical reactions or utilize more of the solar spectrum. Fundamental research can realize advantages unique to light-driven fuels generation such as strong electronic coupling or light-induced structural changes. Tailor interactions of complex phenomena to achieve integrated multicomponent systems. Integration of individual molecular and material components presents challenges for generating solar fuels because individual elements may not perform the way they do in integrated systems. Fundamental research is needed to provide a mechanistic understanding of how individual multiscale processes interact and affect the function of integrated components. The resulting knowledge of how integration impacts performance, including durability, will guide the development of predictive models and enable the co-design of components for efficient, selective, and durable systems. Applications are expected to take the form of multi-institutional proposals submitted by a single lead institution. Eligible lead and partner institutions include universities, nonprofits, DOE national laboratories, and other federal laboratories and agencies. Total planned funding will be up to $100 million for awards beginning in Fiscal Year 2020 and up to five years in duration, with outyear funding contingent on congressional appropriations. Selections will be made based on peer review and may result in the establishment of one or two DOE Energy Innovation Hubs, depending on the scope of the selected proposals.