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Multi-objective optimization for 10-kW rated power dynamic wireless charging systems of electric vehicles

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Abstract

In this paper, we propose a method to optimize the output power, efficiency, and cost of the dynamic wireless charging (DWC) system of electric vehicles by using the transmitting coil spacing as the decision variable. In a set of transmitting equipment, we adopt a structure with two transmitting networks in parallel and derive loss models. The expressions of the output power and efficiency of the DWC system are obtained by data fitting. In addition, combined with the proposed cost function, we construct a multi-objective optimization problem on output power, efficiency, and cost. Due to the complexity of the objective function, it is difficult to solve the problem by the analytic method, and thus we propose a constrained adaptive particle swarm optimization (CAPSO) algorithm with high accuracy to solve the problem. Finally, the simulation results verify the feasibility of the proposed model. The advantages of the proposed CAPSO algorithm and the optimization results under different weight combinations are presented.

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Acknowledgements

This work was partially supported by National Key R&D Program of China (Grant No. 2018YFA0703800), Science Fund for Creative Research Group of the National Natural Science Foundation of China (Grant No. 61621002), and Zhejiang Key R&D Program (Grant No. 2021C01198).

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Authors and Affiliations

  1. State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, 310027, China

    Ze Zhou, Zhitao Liu & Hongye Su

  2. School of Automation, Wuhan University of Technology, Wuhan, 430070, China

    Liyan Zhang

Authors
  1. Ze Zhou
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  2. Zhitao Liu
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  3. Hongye Su
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  4. Liyan Zhang
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Correspondence to Zhitao Liu.

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Zhou, Z., Liu, Z., Su, H. et al. Multi-objective optimization for 10-kW rated power dynamic wireless charging systems of electric vehicles. Sci. China Inf. Sci. 65, 202201 (2022). https://doi.org/10.1007/s11432-020-3255-5

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  • DOI: https://doi.org/10.1007/s11432-020-3255-5

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