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Research Papers

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

[+] Author and Article Information
B. Lenzo

Centre for Automotive Engineering,
Department of Mechanical Engineering Sciences,
Faculty of Engineering and
Physical Sciences (FEPS),
University of Surrey,
Guildford GU2 7XH, UK;
Department of Engineering and Mathematics,
Sheffield Hallam University,
Sheffield S1 1WB, UK

G. De Filippis, P. Gruber, S. Fallah

Centre for Automotive Engineering,
Department of Mechanical Engineering Sciences,
Faculty of Engineering and
Physical Sciences (FEPS),
University of Surrey,
Guildford GU2 7XH, UK

A. M. Dizqah

Centre for Mobility and Transport,
Coventry University,
Coventry CV1 5FB, UK;
Centre for Automotive Engineering,
Department of Mechanical Engineering Sciences,
Faculty of Engineering and
Physical Sciences (FEPS),
University of Surrey,
Guildford GU2 7XH, UK

A. Sorniotti

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

W. De Nijs

Flanders MAKE,
Lommel 3920, Belgium

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 16, 2016; final manuscript received April 21, 2017; published online August 9, 2017. Assoc. Editor: Beshah Ayalew.

J. Dyn. Sys., Meas., Control 139(12), 121004 (Aug 09, 2017) (13 pages) Paper No: DS-16-1402; doi: 10.1115/1.4037003 History: Received August 16, 2016; Revised April 21, 2017

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 driving/braking and cornering are studied and discussed in detail. Influences of different drivetrain characteristics on the front and rear axles are described. The results of an analytically derived algorithm are contrasted with those from two other control allocation strategies, based on the offline numerical solution of more detailed formulations of the control allocation problem (i.e., a multiparametric nonlinear programming (mp-NLP) problem). The control allocation algorithms are experimentally validated with an electric vehicle with four identical drivetrains along multiple driving cycles and in steady-state cornering. The experiments show that the computationally efficient algorithms represent a very good compromise between low energy consumption and controller complexity.

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References

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Figures

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Fig. 1

Simplified schematic of the vehicle control system

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Fig. 2

The vehicle demonstrator setup on the rolling road facility

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Fig. 3

Experimental power loss characteristics for the left front electric drivetrain for different vehicle speeds

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Fig. 4

Vehicle schematic with some of the geometric parameters affecting the vertical load transfer caused by longitudinal and lateral acceleration

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Fig. 5

Power loss characteristics at each vehicle corner (i=1…4) at 90 km/h with ax=6 m/s2 and ay=2.5 m/s2

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Fig. 6

Power loss characteristics of the original drivetrains at the front axle (1,2) and the drivetrains scaled with β=0.5 at the rear axle (3,4) at 90 km/h

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Fig. 7

Overlap of the experimentally measured power loss characteristic of the left front drivetrain at 90 km/h and the three investigated fitting functions

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Fig. 8

I-CA: map of {r}* as a function of vehicle speed and demanded drivetrain output torque on the vehicle side; the white star represents the point experimentally investigated in steady-state conditions in Sec. 6

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Fig. 9

E-CA at 90 km/h with ax=6 m/s2 and ay=2.5 m/s2: (a) optimal front-to-total torque ratio {r}*, (b) optimal torque shift {ε}*, and (c) optimal torque shift {εw}*

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Fig. 10

E-CA: optimal front-to-total torque ratio (in percentage, {r}*) as a function of the demanded drivetrain output torque on a vehicle side (τd,s), at 90 km/h with β=0.5

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Fig. 11

Estimated power losses on a vehicle side at 90 km/h for different torque allocation strategies: single axle (SA), even distribution (ED) and I-CA

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Fig. 12

Estimated power losses on a vehicle side at 90 km/h for different torque allocation strategies: I-CA, E-CA, and H-CA

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Fig. 13

Speed profile of the Surrey Designed Driving Cycle (SDDC)

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Fig. 14

Experimental points of the SDDC and switching torques for E-CA and H-CA

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