Research Supports that Wireless Charging-Enabled Shared Autonomous EVs have the Potential to Increase Utility of the Vehicle Fleet by 50 Percent Compared to Manually-Driven, Plug-in Charged EVs.

Study by Argonne and Oak Ridge National Laboratories and the University of Michigan Used Deterministic Systems-Level Lifecycle Modeling to Understand Transportation System-Wide Effects of Wireless Charging and Shared Autonomous Battery Electric Vehicles (W+SABEV) Penetration.

Made Public Date

02/26/2021

Nationwide, United States

Nationwide,

United States

Identifier

2021-B01539

Wireless Charging and Shared Autonomous Battery Electric Vehicles (W+SABEV): Synergies that Accelerate Sustainable Mobility and Greenhouse Gas Emission Reduction

Summary Information

The world’s largest economies are facing significant “energy and environmental burdens” from the transportation sector. Recent dramatic modal shifts, the emergence of clean vehicle technologies and the implementation of sustainable mobility systems have prompted the need to study how current trends impact mobility systems. The trends are driven primarily by the shared vehicle economy, connected and autonomous vehicles and vehicle electrification.

The study seeks to evaluate the interlocking relationships between these current trends and the subsequent impacts on transportation system utility, lifecycle greenhouse gas (GHG) emissions and vehicle technology adoption. This simulation analysis evaluated the transportation system-wide effects of widespread W+SABEV adoption in terms of impacts on GHG payback time, mobility and deployment burdens. Four key emerging technologies are therefore evaluated: wireless charging (W+), shared mobility, autonomous driving, and battery electric vehicles (BEVs).

Methodology

A qualitative analysis focusing on the subsequent impacts of these four emerging technologies on transportation system dynamics and a quantitative analysis focusing on system design and GHG payback time, were performed using a deterministic, life-cycle simulation model. The analysis is not for one particular metropolitan area, but rather summarizes an example fleet based on the literature, historical data and model parameter ranges based on current and future technical capabilities.

Findings

The simulation analyses showed that adoption of wireless charging-enabled shared autonomous BEVs (W+SABEVs) into a transportation system can improve system-wide performance when compared to a fleet of manually-driven, plug-in charged EVs as follows:

Up to 50 percent reduction in required number of vehicles while serving the same travel demand – resulting in increased utility of the vehicle fleet.
En-route wireless charging deployment can effectively increase EV adoption while reducing needed battery size – lowering cost, mass, and energy consumption.
GHG payback time can be improved from 30 years to less than 5 years at full deployment and high utilization. Static and dynamic in-pavement wireless charging combined with shared mobility reduces infrastructure burden – providing additional lot space and reducing the need to deploy charging stations.
Wide-scale deployment of W+SABEV increases utility of existing charging infrastructure and reduces labor costs through automated charging.
Synergistic effects of adopting all four emerging technologies: some pros of one technology offset some cons of another, resulting in fewer adoption barriers.