Energy Management Strategy of Modern Tram Based on the Combination of Rule Control and Driving Conditions

doi:10.3901/JME.2023.04.221

Abstract

Abstract: Rule based control has significant advantages of strong robustness and high flexibility. It has gradually become a classic method to optimize the energy management performance of energy storage modern tram, but it also faces the problem of relying too much on expert experience and poor adaptability to working conditions. Therefore, aiming at the lithium battery / super capacitor hybrid energy storage system for tram, a new dynamic power distribution method is proposed by introducing road slope and running speed into the input of traditional fuzzy logic control. The membership function and universe are formulated according to the driving conditions, and the response time of super capacitor high power density is adjusted to optimize the dynamic performance of the train; Particle swarm optimization algorithm is used to optimize the weight of fuzzy control rules, so as to reduce the peak current of lithium battery and prolong the service life of energy storage system while ensuring the power demand of train; The proposed strategy is applied to the comparison and verification of the data of the western suburb line of Beijing modern tram. The results show that compared with the traditional fuzzy control, the fuzzy control integrating driving condition information achieves multiple optimizations in power distribution, SOC(state of charge) offset range of lithium battery and super capacitor, operating stress of lithium battery and overall efficiency of energy storage system, and the regenerative braking energy recovery rate is significantly improved; Compared with the traditional fixed weight scheme, the peak current of lithium battery is reduced by 31.02%, the driving range of train is increased by 22.45%, and the algorithm can find the global optimal solution within 7 iterations. The operation speed is fast and easy to implement.

Key words: hybrid energy storage, tram, lithium battery, supercapacitor, energy management

CLC Number:

TM91

GAO Fengyang, ZHANG Haoran, WANG Wenxiang, LI Mingming. Energy Management Strategy of Modern Tram Based on the Combination of Rule Control and Driving Conditions[J]. Journal of Mechanical Engineering, 2023, 59(4): 221-231.

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