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research-article

Torque Distribution Strategies for Energy-Efficient Electric Vehicles with Multiple Drivetrains

[+] Author and Article Information
Basilio Lenzo

Centre for Automotive Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, United KingdomDepartment of Engineering and Mathematics, Sheffield Hallam University, United Kingdom
b.lenzo@surrey.ac.uk

Giovanni De Filippis

Centre for Automotive Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, United Kingdom
g.defilippis@surrey.ac.uk

Arash M. Dizqah

Centre for Mobility and Transport, Coventry University, United KingdomCentre for Automotive Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, United Kingdom
ac1103@coventry.ac.uk

Aldo Sorniotti

Centre for Automotive Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, United Kingdom
a.sorniotti@surrey.ac.uk

Patrick Gruber

Centre for Automotive Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, United Kingdom
p.gruber@surrey.ac.uk

Saber Fallah

Centre for Automotive Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, United Kingdom
s.fallah@surrey.ac.uk

Wouter De Nijs

Flanders MAKE, Belgium
wouter.denijs@flandersmake.be

1Corresponding author.

ASME doi:10.1115/1.4037003 History: Received August 16, 2016; Revised April 21, 2017

Abstract

The paper discusses novel computationally efficient torque distribution strategies for electric vehicles with individually controlled drivetrains, aimed at minimizing the overall power losses while providing the required level of wheel torque and yaw moment. Analytical solutions of the torque control allocation problem are derived and effects of load transfers due to moderate driving/braking and cornering conditions are studied and discussed in detail. Influences of different drivetrain characteristics on the front and rear axles are described. The results of the analytically-derived algorithm are contrasted with those from two other control allocation strategies, based on the off-line numerical solution of more detailed formulations of the control allocation problem (i.e., a multi-parametric non-linear programming problem). The solutions of the control allocation problem are experimentally validated along multiple driving cycles and in steady-state cornering, on an electric vehicle with four identical drivetrains. The experiments show that the computationally efficient algorithms represent a very good compromise between low energy consumption and controller complexity.

Copyright (c) 2017 by ASME
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