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DOE to award $68.5M for advanced vehicle technologies research

The US Department of Energy (DOE) will award up to $68.5 million for early-stage research of advanced vehicle technologies. (DE-FOA-0001919) This new funding opportunity announcement (FOA) seeks research projects to address priorities in the following areas: batteries and electrification; materials; technology integration and energy efficient mobility systems; energy-efficient commercial off-road vehicle technologies; and co-optimized advanced engine and fuel technologies to improve fuel economy.

Topic areas for this funding opportunity include the following:

Topic 1: Batteries and Electrification (up to $27 million)

  • Low cobalt active cathode materials for next-generation electric vehicle batteries. The price of cobalt, a key element within an lithium-ion batteries (LiB) for stability, has nearly tripled over the past few years due to increased demand from the cell phone industry, a current materials shortage, and speculation for a future global shortage.

    The objective of this are of interest (AOI) is to research, develop, and test next generation LiBs capable of achieving more than 600 Wh/kg usable specific energy @ C/3 at the cathode level; 15-year calendar life; 1,000 cycles at C/3 deep discharge; a cobalt loading of ≤ 50 mg/Wh; and a cost of ≤$100/kWh.

  • Plug-in electric drive vehicle extreme fast charging research. The objective of this AOI is to develop and demonstrate innovative approaches to reduce the impact on the grid from multiple vehicles charging at extreme fast charging (XFC) rates. Power levels for XFC 350 KW or higher are substantial, especially considering that multiple vehicles could be charging simultaneously at a charging station.

    Effectively controlling these high and variable loads that fall outside of traditional vehicle charging will require novel solutions to avoid significant negative impacts to the nation’s electric grid. Solutions may incorporate localized energy storage or electricity generation schemes, but should strive to keep both installation and operations costs low.

  • Electric vehicle charging infrastructure cybersecurity. Plug-in electric vehicles (EVs) present a new cybersecurity vulnerability to the US transportation sector and the electricity grid. Vulnerability is created by the need for data sharing between the EV, the recharging or Electric Vehicle Supply Equipment (EVSE), and the electric grid. Although much work has been done by government and industry to address cybersecurity issues associated with conventional and autonomous vehicles, little has been done to address cybersecurity issues associated with charging EVs. With charging power levels that will reach 350 KW or higher in the next few years, the potential for negative grid impacts resulting from compromised EV charging will become even more critical.

    The objective of this AOI is to research, develop, and test technologies and approaches that identify, minimize, or eliminate critical cybersecurity vulnerabilities resulting from the transition of EV charging to power levels above 200 kW.

Topic 2: Materials (up to $6 million)

  • Predictive modeling of corrosion in dissimilar material joints. Multi-material systems (specifically, joints between dissimilar materials) used for lightweighting represent a significant challenge for corrosion prevention. Atmospheric corrosion becomes more severe in tight spaces, and materials with different galvanic potentials can form an electrical circuit when in contact, which greatly accelerates corrosion of the less noble material.

    Although protective coatings provide some protection, joining processes such as resistance spot welding, friction stir welding, and fasteners pierce through or degrade the coatings, eliminating their effectiveness. Additionally, the amount of time spent by the automobile industry to validate that corrosion has been successfully mitigated is extensive, making the use of lightweight materials less attractive. Computational methods for predicting corrosion, processing effects from joining, and failure mechanisms can provide information that will eliminate barriers to the use of these materials in vehicle mass production.

    The objective of this AOI is to develop and validate computational models capable of predicting the location and extent of corrosion, and the resulting mechanical performance of dissimilar lightweight material joints when exposed to typical vehicle moisture, temperature, and salt environments. The model should be able to predict joint strength and fatigue life after corrosion within ≤10% of experimental measurements.

  • Modeling of corrosion/oxidation of materials in high-temperature engines. The existing materials used for high temperature applications, such as engine components (pistons, exhaust valves, exhaust valve seats, turbocharger turbines, and turbocharger housings), are near their operational limit with the primary failure mechanisms being loss of strength, oxidation fatigue cracking, and corrosion. Physical testing of oxidation/corrosion resistance of new alloys in realistic exhaust gas chemistries and temperatures requires specialized equipment and takes weeks to complete, hindering the adoption of high efficiency technologies.

    The objective of this AOI is to develop and validate computational models capable of predicting the location and extent of high temperature corrosion/oxidation of materials in Advanced Combustion Engine and Emission Control (ACEC) gas compositions (Stoichiometric Gasoline, Lean Gasoline, Clean Diesel, and Low Temperature Combustion). The model should be able to predict the corrosion/oxidation performance of materials exposed to high temperatures and realistic combustion gasses to within 10% of experimental measurements.

Topic 3. Technology Integration (up to $20 million)

  • High performance computing for transportation hubs. The objective of this AOI is to conduct research that uses data and high-performance computing (HPC) to optimize the mobility service provided, the energy needed, and the costs required to move people and goods at and around transportation hubs. Projects will use HPC to analyze mobility data—including data from service providers such as shared mobility partners, transportation network companies (TNCs), taxi companies, freight providers, transit agencies, transportation hub operators, airlines, shipping companies, rental car companies, or other organizations—tFo optimize efficiency and reduce the cost of both passenger and freight movement.

  • First/last mile for people/goods movement. The objective of this AOI is to research how data and technology can be used to improve the mobility, energy impact, and affordability of new first/last mile solutions for people and/or goods movement.

  • System-level data for energy efficient mobility. The objective of this AOI is to conduct research to accelerate the understanding of how communities can use system-level data for energy efficient mobility.

  • Fuel-efficient platooning. The objective of this AOI is to execute field evaluations of multi-truck platoon proof of concepts that assess both the potential fuel savings and barriers that need to be overcome for platooning to be effective. Projects should focus on connected and/or partially automated platooning of class 7/8 tractors and trailers. Projects should research factors such as vehicle weight, aerodynamics, road/environment variability, the impact of non-platooning vehicles on the platoon, issues with forming and leaving a platoon, and distances between trucks and other vehicles on the road.

  • Multi-unit dwelling and curbside residential charging infrastructure innovations. The objective of this AOI is to conduct research that will identify new software, hardware technology, or other innovative solutions to expand access to multi-unit dwelling and curbside residential EV charging infrastructure. Projects will demonstrate, validate, and collect data on innovative models and technologies such as mobile charging, pairing charging with street lighting, or residential charging hubs.

  • Open topic. The objective of this AOI is to allow for maximum innovation from stakeholders and identify innovative technologies or approaches and data sets that can significantly improve domestic energy security and efficiency, provide mobility gains, and/or enable more widespread access to affordable advanced fuels, highly efficient vehicles and mobility systems.

    This includes high-impact, specialized applications or end-user groups that may be underserved by these new technologies.

Engines/Fuels: Off-road Applications (up to $3.5 million)

  • Energy efficient commercial off-road vehicles. The objective of this AOI is to research, develop, and evaluate technologies that can significantly improve the energy efficiency of commercial off-road vehicles and are cost-effective, meet emissions standards, and maintain the durability needed for these vehicles. This may be accomplished by reducing engine-out emissions to decrease the cost and energy penalty associated with emission control.

    Technologies may include, but are not limited to, advanced engine and emission control technologies, waste heat recovery, and hybridization. Teams should consider the use of liquid and gaseous fuels that are widely available in today’s marketplace. Technologies should address common sources of inefficiencies that can curb fuel consumption across the entire sector to the greatest extent possible. Teams are encouraged to include a manufacturer of off-road vehicles with engines sized >75 hp.

Topic 5. Co-optimization of engines and fuels (up to $12 million)

The Co-Optima initiative, a joint effort between the Office of Energy Efficiency and Renewable Energy’s (EERE’s) Vehicle Technologies Office and Bioenergy Technologies Office, supports research of fuel and engine innovations that work together to maximize vehicle performance and fuel efficiency.

  • Multi-mode optimized fuel/engine system development. The objective of this AOI is to develop a co-optimized (engine and fuel) prototype light- duty, multi-cylinder reciprocating engine (minimum 150 hp). The engine should operate in a spark-ignition/compression ignition multimode combustion regime over a broad range of engine operating conditions with a suitable co-optimized liquid fuel.

    The engine and fuel combination should demonstrate an ability to meet Tier 3/LEV III emissions standards. The goal is to achieve a 10% improvement in modeled vehicle fuel economy by co-optimizing the engine and fuel, relative to a comparable engine operating on 87 AKI gasoline, over the FTP-75 cycle.

    If the co-optimized fuel does not include a bio-component, the application shall include a preliminary techno-economic analysis for producing a relevant biomass component and a plan to demonstrate chemical equivalence to a biomass pathway-derived product through a fuel property analysis.

  • Bioblendstocks to optimize mixing controlled compression ignition engines. For medium- and heavy-duty vehicles, the Co-Optima approach is to focus on reducing engine-out emissions while maintaining or improving efficiency in MCCI engines and potentially advanced compression ignition engines. The objective of this AOI is to develop and demonstrate single component or multicomponent liquid bioblendstocks for use in medium- and heavy-duty mixing controlled, compression ignition engines blended into a base diesel fuel at no less than 5% by volume. The bioblendstock must achieve lifecycle greenhouse gas reductions of at least 50% compared to conventional petroleum-derived diesel.

    The bioblendstocks should improve at least two of the following properties of the finished fuel: energy density; sooting propensity; cetane number; and cold weather behavior (pourpoint, cloudpoint).

Concept papers for this funding opportunity are due 29 May 2018, and full applications will be due 13 July 2018.



All good goals and projects but why not convince/entice private industries (like Apple, Google, Facebook, Microsoft, Intel, Amazone, Oil and Gas and the 1000+ local billionaires) with loads of $$$$$$ to do it?

Providers of R&D funds (used locally) could get more (over 100%) tax credits?

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