Adaptive Sliding Mode Control with Enhanced Optimal Reaching Law for Boost Converter Based Hybrid Power Sources in Electric Vehicles


Vol. 19, No. 2, pp. 549-559, Mar. 2019
10.6113/JPE.2019.19.2.549


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 Abstract

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.


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Cite this article

[IEEE Style]

B. Wang, C. Wang, Q. Hu, G. Ma, J. Zhou, "Adaptive Sliding Mode Control with Enhanced Optimal Reaching Law for Boost Converter Based Hybrid Power Sources in Electric Vehicles," Journal of Power Electronics, vol. 19, no. 2, pp. 549-559, 2019. DOI: 10.6113/JPE.2019.19.2.549.

[ACM Style]

Bin Wang, Chaohui Wang, Qiao Hu, Guangliang Ma, and Jiahui Zhou. 2019. Adaptive Sliding Mode Control with Enhanced Optimal Reaching Law for Boost Converter Based Hybrid Power Sources in Electric Vehicles. Journal of Power Electronics, 19, 2, (2019), 549-559. DOI: 10.6113/JPE.2019.19.2.549.