Research Papers

Equitable Multi-Objective Optimization Applied to the Design of a Hybrid Electric Vehicle Battery

[+] Author and Article Information
Brian Dandurand

Ph.D. Candidate
e-mail: bdandur@clemson.edu

Paolo Guarneri

Post Doctoral Fellow
e-mail: pguarne@clemson.edu

Georges Fadel

e-mail: fgeorge@clemson.edu

Margaret M. Wiecek

e-mail: wmalgor@clemson.edu
Department of Mathematical Sciences,
Clemson University,
Clemson, SC 29634

See Acknowledgment.

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received February 5, 2012; final manuscript received January 28, 2013; published online March 26, 2013. Assoc. Editor: Michael Kokkolaras.

J. Mech. Des 135(4), 041004 (Mar 26, 2013) (8 pages) Paper No: MD-12-1094; doi: 10.1115/1.4023553 History: Received February 05, 2012; Revised January 28, 2013

This work considers the impact of thermal behavior in battery design. The cell performance worsens when the operating temperature falls outside of the ideal range, and evenness of cell temperatures is sought to prevent cell electrical unbalance which may lead to performance fading and premature failure. The heat transfer between the cells and the coolant depends on the cell packaging and layout. A multi-objective optimization model is posed whose Pareto efficient designs minimize cell temperature deviations while maintaining evenness of temperature distribution. The special characteristics of the battery design problem (comparable objectives, anonymity and Pigou–Dalton principle of transfers) make it suitable for the application of the equitability preference, which is a refinement of the Pareto optimality that has not been used in engineering design. The proposed approach based on equitability is applied to compute the spacing of the cylindrical cells in a battery module that yields an optimal thermal behavior.

Copyright © 2013 by ASME
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Fig. 1

The battery layout

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Fig. 2

Illustration of geometric layout of battery components (12 columns, 6 rows)

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Fig. 3

Illustrating anonymity of objectives

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Fig. 4

Illustrating Pigou–Dalton principle of transfers

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Fig. 5

The relationship between the layout designs at the battery and vehicle levels

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Fig. 6

Evaluating convexity of absolute temperature deviations in terms of spacing factor pcell

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Fig. 7

Cell coolant temperature drop (black line is coolant temperature, gray line is cell temperature)

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Fig. 8

Condensed Pareto optimal and equitable outcomes with line of equity (two views)




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