Hyper-Spherical Search Optimized Fuzzy Logic Control Considering Operating Conditions for Hybrid Tram

Abstract

Rule-based control strategy has significant advantages of strong robustness and high flexibility, and has gradually become a classical implementation method to optimize the energy management performance of modern energy-storage trams. However, it also faces the problems of over-reliance on expert experience and poor adaptability to operating conditions. Therefore, an improved dynamic power distribution method for tram lithium battery/supercapacitor energy storage system is proposed, which introduces road slope and running speed into the decision variable layer of traditional fuzzy logic control input. Firstly, the membership functions and domain are formulated according to operating conditions, the response time of high power density of supercapacitor is adjusted to improve the dynamic performance of the tram. Secondly, the hyper-spherical search algorithm is used to optimize the weight of fuzzy control rules, the peak current of the lithium battery is minimized and the life span of the energy storage system is increased. Finally, the fuzzy control strategies combined with different decision variables are compared and analyzed by using the data of modern tram western suburban line in Beijing. The results show that the proposed strategy achieves multiple superior to traditional fuzzy control strategy in power distribution, charge state offset ranges of lithium battery and supercapacitor, and energy storage system overall efficiency. Compared with the traditional fixed weight scheme, the peak current of the lithium battery is reduced by 31.02% and the continuous tram mileage is increased by 22.45% in the rule weight dynamic optimization scheme.