An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

MANGIA, Andrea, LENZO, Basilio and SABBIONI, Edoardo (2021). An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver. Meccanica, 56 (5), 991-1010.

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Abstract

A key feature achievable by electric vehicles with multiple motors is torque-vectoring. Many control techniques have been developed to harness torque-vectoring in order to improve vehicle safety and energy efficiency. The majority of the existing contributions only deal with specific aspects of torque-vectoring. This paper presents an integrated approach allowing a smooth coordination among the main blocks that constitute a torque-vectoring control framework: (1) a reference generator, that defines target yaw rate and sideslip angle; (2) a high level controller, that works out the required total torque and yaw moment at the vehicle level; (3) a low level controller, that maps the required force and yaw moment into individual wheel torque demands. In this framework, the driver can select one among a number of driving modes that allow to change the vehicle cornering response and, as a second priority, maximise energy efficiency. For the first time, the selectable driving modes include an “Energy efficiency” mode that uses torque-vectoring to prioritise the maximisation of the vehicle energy efficiency, thus further increasing the vehicle driving range. Simulation results show the effectiveness of the proposed framework on an experimentally validated 14 degrees of freedom vehicle model.

Item Type:	Article
Uncontrolled Keywords:	0102 Applied Mathematics; 0915 Interdisciplinary Engineering; Mechanical Engineering & Transports
Identification Number:	https://doi.org/10.1007/s11012-021-01317-3
Page Range:	991-1010
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	19 Mar 2021 11:36
Last Modified:	31 Mar 2021 15:45
URI:	https://shura.shu.ac.uk/id/eprint/28417

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