SBIR/STTR Research Award

Development of a Connected and Automated EV with 4 In-Wheel Motors

Award identifier 414933a6ead8c830669b12029cff4acffe292c9b6ebef5a12d2d87f13d892049Awarding agency Department of Energy

Award amount

$150,000

Program and phase

STTR · Phase I

Award year

2018

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
Local Motors, Inc.
Proposal award date
2018-07-02
Contract end date
2019-05-01
UEI
Not reported
Solicitation number
DE-FOA-0001771
Topic code
13c

Research abstract

Local Motors (https://localmotors.com/) is an automotive OEM that is currently developing a connected and automated vehicle for various shuttle bus applications. The OlliTM vehicle is intended to be an electric vehicle driven by four in-wheel electric motors that allow for independent actuation and control for increased traction stability and operation efficiency. This electric vehicle shuttle design is novel and presents a promising architecture because of the flexibility in vehicle control, especially as a connected and automated vehicle. With the actuation redundancy and information from environment sensors, other vehicles, and infrastructure, the Olli vehicle is anticipated to increase the operation efficiency up to 20% for the same local driving scenario, compared with to human-drive mode with a centralized powertrain architecture. The objective of this project will be to use the redundant control degrees of freedom enabled by the independent, in-wheel motors and the information obtained from the vehicle connectivity, specifically Vehicle-To-Everything information such as Signal Phase and Timing information from the traffic signals, and Vehicle-To-Vehicle information from surrounding vehicles to optimize the control algorithm for maximum energy efficiency. The Vehicle-To-Vehicle connectivity will include road topography information used in a calculation of upcoming vehicle pitch and roll angles. The maximum vehicle operation efficiency will be achieved by simultaneously realizing the high-level vehicle (speed, acceleration and deceleration, and path selection) efficiency optimization and the component-level motor (torque allocation and distribution) efficiency optimization. The Research Institution partner, Arizona State University, is already developing the connected and automated, electric vehicle that will serve as the testbed for Olli automated driving control strategies. In Phase I of the project, Local Motors and Arizona State University will formulate and develop the joint high- level and low-level optimization problem to be used in for the control algorithm with a goal of maximizing vehicle efficiency. After testing at Local Motors and Arizona State University, the vehicle’s operation will be tested in Anthem, Arizona, a residential area within the Maricopa County Department of Transportation purview – in collaboration with the Maricopa County Department of Transportation. Maricopa County Department of Transportation has equipped several intersections of the Anthem testbed with connectivity equipment that provide Signal Phase and Timing information and has vehicles that can provide the upcoming topography information. The combination of testbed and test area will allow for rapid control strategy development. The intent will be to employ a developed control algorithm in the Olli vehicle by the end of Phase 1 that shows 10% improvement in energy efficiency from the baseline vehicle. If applications for Phase II and III are awarded, the energy efficiency increase achieved through optimization of the vehicle control strategy will allow for a longer range and/or smaller energy storage system that will improve the performance and commercial prospects of the developing Olli shuttle bus. More electric shuttle buses can reduce city congestion and local pollution by providing an alternative to vehicles and can increase mobility for older and disabled citizens. High-occupancy vehicles reduce energy consumption, especially for highly efficient electric vehicles. Finally, a connected and automated electric shuttle will significantly reduce traffic accidents that lead to many injuries and deaths.

Technology keywords

Not reported

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Agency intelligence

Department of Energy

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