Scenario-Based Drive Cycle Analysis Framework for Zero Emission Vehicles with Cooperative Driving Automation
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Scenario-Based Drive Cycle Analysis Framework for Zero Emission Vehicles with Cooperative Driving Automation

Abstract

The next evolution of vehicle mobility is anticipated to include, along with zero-emission vehicles (ZEVs), the introduction of cooperative driving automation (CDA) encompassing both autonomous vehicles (AV) and connected infrastructure. CDA offers enhanced comfort and safety for the passengers and, potentially, an improvement in fuel economy. For example, on urban roadways, communication to the vehicle from smart traffic signals can adjust and smooth vehicle speed and reduce fuel use. Additionally, communication between vehicles allows for group coordination that can improve aerodynamics and reduce fuel consumption. This thesis explores the role of the vehicle drivetrain in responding to CDA communication. With the growing population of zero-emission battery electric vehicles (BEV) and hydrogen fuel cell electric vehicles (FCEV), the focus of the thesis is directed to electric drivetrains with the goal to project the fuel savings from connected and autonomous mobility. The results reveal that the addition of CDA to ZEVs result in an increase in city fuel economy of 6% to 12% with a infrastructure to vehicle connectivity range not exceeding 250 meters to 450 meters respectively. As the connectivity range increases above 350 meters, the fuel efficiency gains diminish. The addition of CDA increases highway fuel economy by 6% to 32% due to reduced drag from vehicle platoons. Future vehicle technology improvements that increase the efficiency of individual powertrain components are found to decrease the amount of fuel economy improvements when adding CDA. Resulting fuel economy improvements from equipping vehicles with CDA are projected to reduce the fuel cost to consumers by 6%.

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