Hierarchical energy management strategy for hybrid electric vehicle based on dynamic FSM-Fuzzy control strategy

doi:10.16731/j.cnki.1671-3133.2018.03.013

Abstract

Abstract: Search mechanism is comprehensive improved by using the advantage of Particle Swarm Optimization(PSO)algorithm and Genetic Algorithm(GA)aiming at the problem of slow convergence and poor convergence accuracy of artificial bee colony algorithm.Benchmark functions show that the convergence speed and accuracy of the algorithm improved obviously.On the basis of the algorithm,designing the composite power electric vehicle FSM-Fuzzy layered energy management strategy,the fuzzy control strategy membership function size and ship are closed-loop learning by calling for the Advisor software.The result shows:under the UDDS and SC03 condition,the energy consumption can still reduce 8.36 % and 8.58 % under the strategy learned by the improved artificial bee colony algorithm.

Key words: artificial bee colony improving, composite power electric vehicle, control strategy

CLC Number:

U461.1

Song Xiaolin,Ren Xiangxi. Hierarchical energy management strategy for hybrid electric vehicle based on dynamic FSM-Fuzzy control strategy[J]. Modern Manufacturing Engineering, 2018, 450(3): 68-73.

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