Evaluation of Drive Cycle-Based Traction Motor Design Strategies Using Gradient Optimisation

Stavros Pastellides, Stiaan Gerber, Rong-Jie Wang and Maarten Kamper
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Stavros Pastellides: Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa
Stiaan Gerber: Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa
Rong-Jie Wang: Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa
Maarten Kamper: Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa

Energies, 2022, vol. 15, issue 3, 1-21

Abstract: In this paper, two design optimisation methods are evaluated using gradient-based optimisation for electric vehicle traction applications. A driving cycle-based approach is used to evaluate specific operational points for the design optimisation procedure. To determine the operational points, an energy centre of gravity (ECG) approach is used. Both optimisation methods are described, namely the point based method and the flux mapping method, with a focus on the flux mapping procedure. Within the flux mapping approach, an inner optimisation loop is defined in order to maintain the stability of gradient calculation for the gradient-based optimisation. An emphasis is placed on the importance of how the optimisation problem is defined, in terms of the objective function and constraints, and how it affects a gradient based optimisation. Based on a design case study conducted in the paper, it is found that the point-based strategy realised motor designs with a slightly lower overall cost (5.66% lower than that of the flux mapping strategy with 8 ECG points), whereas the flux mapping strategy found motor designs with a lower input energy (1.48% lower than that of the point-based strategy with 8 ECG points). This may be attributed to the difference in the definition and interpretation of constraints between these two methods. It is also shown that including more operational points from the driving cycle in the design optimisation leads to designs with reduced total input energy and thus better drive-cycle energy efficiency. This paper further illustrates the significant computational advantages of a gradient-based optimisation over a global optimisation method as it can be completed within a fraction of the time while still finding a global optimum, as long as the problem definition is correctly determined.

Keywords: design optimisation; drive cycle; electric vehicle; finite element analysis; gradient-based optimisation; permanent magnet machines (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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