Hybrid Electric Vehicle Energy Online Allocation Strategy Based on Fuzzy Reinforcement Learning

Abstract

To lessen fuel consumption of hybrid electric vehicle, energy online distribution strategy based on fuzzy reinforcement learning is proposed. Vehicle dynamic model and key component model are built, so that hybrid power system simulation model is given. Energy distribution problem of hybrid electric vehicle is transferred to constrained optimization problem of stochastic dynamic system through modelling, and solving problem based on fuzzy reinforcement learning is put forwarded. Fuzzy reinforcement learning is used to optimize fuzzy inference system real-time, which makes fuzzy inference system adjust with driving cycle adaptively, so that optimal control under any driving cycle come true. Clarified by simulation, fuel consumption under the control of rule-based is 3.89L/km, and it is 3.45L/km under the control of fuzzy reinforcement learsning, which saves 11.31% fuel consumption compared with rule-based. The data above proves validity of fuzzy reinforcement learning on hybrid electric vehicle energy management.