Multi-objective optimisation for battery electric vehicle powertrain topologies

Date published

2016-10-06

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Volume Title

Publisher

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

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Type

Article

ISSN

0954-4070

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Citation

Othaganont P, Assadian F and Auger DJ., Multi-objective optimisation for battery electric vehicle powertrain topologies. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Volume 231, Issue 8, pp. 1046-1065

Abstract

Electric vehicles are becoming more popular in the market. To be competitive, manufacturers need to produce vehicles with a low energy consumption, a good range and an acceptable driving performance. These are dependent on the choice of components and the topology in which they are used. In a conventional gasoline vehicle, the powertrain topology is constrained to a few well-understood layouts; these typically consist of a single engine driving one axle or both axles through a multi-ratio gearbox. With electric vehicles, there is more flexibility, and the design space is relatively unexplored. In this paper, we evaluate several different topologies as follows: a traditional topology using a single electric motor driving a single axle with a fixed gear ratio; a topology using separate motors for the front axle and the rear axle, each with its own fixed gear ratio; a topology using in-wheel motors on a single axle; a four-wheel-drive topology using in-wheel motors on both axes. Multi-objective optimisation techniques are used to find the optimal component sizing for a given requirement set and to investigate the trade-offs between the energy consumption, the powertrain cost and the acceleration performance. The paper concludes with a discussion of the relative merits of the different topologies and their applicability to real-world passenger cars.

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Github

Keywords

Battery electric vehicles, multi-objective optimization, powertrain topologies

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Attribution-NonCommercial 4.0 International

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