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The disparate characteristics between conventional (CVs) and battery electric vehicles (BEVs) in terms of driving range, refill/recharge time, and availability of refuel/recharge infrastructure inherently limit the relative utility of BEVs when benchmarked against traditional driver travel patterns. However, given a high penetration of high-power public charging combined with driver tolerance for rerouting travel to facilitate charging on long-distance trips, the difference in utility between CVs and BEVs could be marginalized. We quantify the relationships between BEV utility, the deployment of fast chargers, and driver tolerance for rerouting travel and extending travel durations by simulating BEVs operated over real-world travel patterns using the National Renewable Energy Laboratory's Battery Lifetime Analysis and Simulation Tool for Vehicles (BLAST-V). With support from the U.S.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles.

Applying nanotechnology to thermal engineering, ANL has addressed the interesting and timely topic of nanofluids. We have developed methods for producing both oxide and metal nanofluids, studied their thermal conductivity, and obtained promising results: (1) Stable suspensions of nanoparticles can be achieved. (2) Nanofluids have significantly higher thermal conductivities than their base liquids. (3) Measured thermal conductivities of nanofluids are much greater than predicted. For these reasons, nanofluids show promise for improving the design and performance of vehicle thermal management systems. However, critical barriers to further development and application of nanofluid technology are agglomeration of nanoparticles and oxidation of metallic nanoparticles. Therefore, methods to prevent particle agglomeration and degradation are required.

This paper outlines the development and progress of implementing the SAE J2931, J2847/2 and J1772 communication standards to accomplish off-board DC charging. Communication between the off-board DC Electric Vehicle Supply Equipment (EVSE) and Plug-in Electric Vehicle (PEV) occurs on the pilot wire of the SAE J1772 connector via HomePlug Green PHY power line communication (PLC). An Electric Vehicle Communication Controller (EVCC) was developed to interface with the PEV's Battery Energy Control Module (BECM). A Supply Equipment Communication Controller (SECC) was also developed to interface with the DC EVSE's Power Control Module (PCM). Firmware was developed to implement the SAE J2931/1 communication stack, which is harmonized with the ISO/IEC DIS 15118-2 and DIN 70121 standards for DC charging communication.

This research focuses on the technical issues that are critical to the adoption of high-energy-producing lithium Ion batteries. In addition to high energy density / high power density, this publication considers performance requirements that are necessary to assure lithium ion technology as the battery format of choice for electrified vehicles. Presentation of prime topics includes: • Long calendar life (greater than 10 years) • Sufficient cycle life • Reliable operation under hot and cold temperatures • Safe performance under extreme conditions • End-of-life recycling To achieve aggressive fuel economy standards, carmakers are developing technologies to reduce fuel consumption, including hybridization and electrification. Cost and affordability factors will be determined by these relevant technical issues which will provide for the successful implementation of lithium ion batteries for application in future generations of electrified vehicles.

The Battery Performance and Cost Model (BatPaC), developed by Argonne National Laboratory, is a versatile tool designed for lithium-ion battery (LIB) pack engineering. It accommodates user-defined specifications, generating detailed bill-of-materials calculations and insights into cell dimensions and pack characteristics. Pre-loaded with default data sets, BatPaC aids in estimating production costs for battery packs produced at scale (5 to 50 GWh annually). Acknowledging inherent uncertainties in parameters, the tool remains accessible and valuable for designers and engineers. BatPaC plays a crucial role in National Highway Transportation Traffic Safety Administration (NHTSA) regulatory assessments, providing estimated battery pack manufacturing costs and weight metrics for electric vehicles. Integrated with Argonne's Autonomie simulations, BatPaC streamlines large-scale processes, replacing traditional models with lookup tables.