Decomposition-based design optimisation of electric vehicle powertrains using proper orthogonal decomposition

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.