Proceedings Article10.1109/EVS.2013.6914933
Optimization method for drive train topology design and control of electric vehicles
Christiane Bertram,Hans-Georg Herzog +1 more
- 01 Nov 2013
- pp 1-8
5
TL;DR: In this paper, a genetic algorithm is used to optimize the drive train of a pure electric vehicle with respect to the energy efficiency and the additional needed copper for the electrical machines and lithium for the energy storages.
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Abstract: The present paper deals with an optimization problem of pure electric vehicles' power trains. The energy consumption is strongly influenced by the size of the components of the vehicle and is highly dependent on the chosen topology. Therefore a method defining possible topologies of the drive train in advance of the optimization is presented in this paper. The chosen reasonable topologies are optimized with respect to the energy efficiency and the additional needed copper for the electrical machines and lithium for the energy storages using a Genetic Algorithm. The method, the chosen optimization algorithm and the results are presented and discussed within this paper.
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TL;DR: In this paper, the Pareto front is analyzed for the optimization of a parallel hybrid electric drive train on both minimal fuel consumption and minimal use of copper for the electrical machine and lithium within the electrical energy storage.
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Dominik Buecherl,Christiane Bertram,Andreas Thanheiser,Hans-Georg Herzog +3 more
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TL;DR: In this paper, scalability is used as a powerful tool of electric drive train simulation, which enables the size variegation of drive train components like the electrical machine, the frequency inverter, and the energy storage.
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