Energy Efficiency Technologies of Connected and Automated Vehicles: Findings from ARPA-E’s NEXTCAR Program 2024-01-1990

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet. This study summarizes the results from Phases I and II of the NEXTCAR program, highlighting the contributions of four teams that participated in both phases: Southwest Research Institute, Michigan Technical University, Ohio State University, and the University of California, Berkeley. The study details the technologies developed by each team, including eco-routing, power-split optimization, cooperative driving, blended mode, speed harmonization, predictive cruise control, charge-sustaining engine on/off optimizer, and eco-approach and departure, among other innovative solutions. It outlines the energy savings achieved by these innovations. These technologies have experimentally demonstrated significant energy savings, ranging from 10-30%, while maintaining travel times.

Additionally, the paper examines the challenges in commercializing these technologies and highlights ARPA-E's envisioned actions to provide a unified testing environment for all teams. This environment will allow for the assessment of all developed technologies under similar conditions, aiming to overcome the limitations of standardized Environmental Protection Agency EPA testing cycles and more accurately reflect real-world driving conditions. This approach validates the effectiveness of CAV technologies and supports their commercialization.