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Front/Rear Axle Torque Vectoring Control for Electric Vehicles

Ruiz Diez, David, Velenis, Efstathios, Tavernini, Davide, Smith, Edward N., Siampis, Efstathios and Soltani, Amir (2019) Front/Rear Axle Torque Vectoring Control for Electric Vehicles Journal of Dynamic Systems, Measurement, and Control, 141 (6), 061002.

Front Rear axle TV Control for Electric Vehicles - ACCEPTEDMANUSCRIPT.pdf - Accepted version Manuscript

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Vehicles equipped with multiple electric machines allow variable distribution of propulsive and regenerative braking torques between axles or even individual wheels of the car. Left/right torque vectoring (i.e., a torque shift between wheels of the same axle) has been treated extensively in the literature; however, fewer studies focus on the torque shift between the front and rear axles, namely, front/rear torque vectoring, a drivetrain topology more suitable for mass production since it reduces complexity and cost. In this paper, we propose an online control strategy that can enhance vehicle agility and “fun-to-drive” for such a topology or, if necessary, mitigate oversteer during sublimit handling conditions. It includes a front/rear torque control allocation (CA) strategy that is formulated in terms of physical quantities that are directly connected to the vehicle dynamic behavior such as torques and forces, instead of nonphysical control signals. Hence, it is possible to easily incorporate the limitations of the electric machines and tires into the computation of the control action. Aside from the online implementation, this publication includes an offline study to assess the effectiveness of the proposed CA strategy, which illustrates the theoretical capability of affecting yaw moment that the front/rear torque vectoring strategy has for a given set of vehicle and road conditions and considering physical limitations of the tires and actuators. The development of the complete strategy is presented together with the results from hardware-in-the-loop (HiL) simulations, using a high fidelity vehicle model and covering various use cases.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
Ruiz Diez, David
Velenis, Efstathios
Smith, Edward N.
Siampis, Efstathios
Soltani, Amir
Date : June 2019
DOI : 10.1115/1.4042062
Copyright Disclaimer : Copyright © 2019 by ASME
Depositing User : Clive Harris
Date Deposited : 08 Mar 2019 10:53
Last Modified : 19 Feb 2020 02:08

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