Fuzzy optimization of energy management for power split hybrid electric vehicle based on particle swarm optimization algorithm

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Abstract
A dual planetary gear hybrid electric vehicle is introduced in the paper. The speed and torque relations between different components of the power split hybrid system are systematically established using the lever analogy. Based on the electric power balance, the influence of the ratio between the engine speed and output speed of the power coupling system on the hybrid electric vehicle powertrain transmission efficiency is revealed, and the transmission efficiency optimization strategy is further proposed. Since some engine operation points are distributed in the low-efficiency region, the engine torque control strategy is designed using fuzzy control algorithm. The fuzzy membership function and fuzzy rules are optimized by particle swarm optimization to reduce the bad influence of expert experience and knowledge on the derivation of optimal engine torque. The vehicle powertrain and the control strategy models are established based on AVL/Cruise and MATLAB/Simulink platforms, and the joint simulation is conducted. Simulation results show that the proposed optimal energy management strategy can optimize the operation points of the engine. The final value of the battery state of charge is kept within a reasonable range, and the equivalent fuel consumption of the whole vehicle is reduced by 10.26% compared with that the transmission efficiency optimization control strategy.
Funding Information
  • Foundation for Jiangsu key Laboratory of Traffic and Transportation Security (TTS2018-01)
  • National Natural Science Foundation of China (51475213)
  • National Natural Science Foundation of China (U1764257)
  • ‘333 Project’ of Jiangsu Province (BRA2018178)

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