Title: Decomposition-based design optimisation of electric vehicle powertrains using proper orthogonal decomposition
Author: M.J. Alexander, J.T. Allison, P.Y. Papalambros
General Motors Technical Center, 30500 Mound Road, Warren, MI 48090, USA.
The MathWorks, Inc., 3 Apple Hill Drive, Natick, MA 01760, USA.
Department of Mechanical Engineering, University of Michigan, 3200 EECS c/0 2250 G.G. Brown, 2350 Hayward Street, Ann Arbor, MI 48104, USA
Abstract: Effective powertrain design for the emerging electric vehicle market is a complex, multidisciplinary problem. As such, engineers may often use formal decomposition-based optimisation strategies to partition the problem into more manageable subproblems and then integrate their solutions to obtain an optimal system design. Sometimes, these strategies yield decision variables that consist of highly-discretised functional data which must be reduced to enable efficient, practical optimisation. Reduced representation methods such as Proper Orthogonal Decomposition (POD) can help achieve this goal, but the effectiveness of POD in terms of design solution accuracy and optimisation efficiency is dependent on its interaction with the optimisation strategy. Therefore, this paper investigates the impact of a tuning parameter within POD on solution accuracy and optimisation efficiency in the context of decomposition-based electric vehicle powertrain design.
Keywords: decomposition; design optimisation; analytical target cascading; electric vehicles; powertrain design; reduced representations; POD; proper orthogonal decomposition; functional variables; coupling variables; dimensionality; optimal design.
Int. J. of Powertrains, 2011 Vol.1, No.1, pp.72 - 92
Date of acceptance: 29 Apr 2011
Available online: 15 Aug 2011