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http://dx.doi.org/10.6113/JPE.2019.19.2.549

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

Wang, Bin (Shaanxi Key Laboratory of Intelligent Robots, Xi'an Jiaotong University)
Wang, Chaohui (State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University)
Hu, Qiao (Shaanxi Key Laboratory of Intelligent Robots, Xi'an Jiaotong University)
Ma, Guangliang (State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University)
Zhou, Jiahui (State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University)
Publication Information
Journal of Power Electronics / v.19, no.2, 2019 , pp. 549-559 More about this Journal
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.
Keywords
Adaptive sliding mode control; Boost converter; Electric vehicle; Hybrid power source; Particle warm optimization;
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