Xiaokan Wang1,2,*, Qiong Wang1, Liang Shuang3, Chao Chen4
Computer Systems Science and Engineering, Vol.39, No.2, pp. 237-250, 2021, DOI:10.32604/csse.2021.015945
Abstract Electric vehicles such as trains must match their electric power supply and demand, such as by using a composite energy storage system composed of lithium batteries and supercapacitors. In this paper, a predictive control strategy based on a Markov model is proposed for a composite energy storage system in an urban rail train. The model predicts the state of the train and a dynamic programming algorithm is employed to solve the optimization problem in a forecast time domain. Real-time online control of power allocation in the composite energy storage system can be achieved. Using standard train operating conditions for simulation,… More >
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