Genetic Algorithm-Based Optimization of Torque Energy-Saving Coordinated Control for Hybrid Electric Vehicle

WANG Ping; ZHANG Hong; LI Chunfu

doi:10.3969/j.issn.1001-2222.2023.03.014

Vehicle Engine ›› 2023, Vol. 0 ›› Issue (3) : 88-92. DOI: 10.3969/j.issn.1001-2222.2023.03.014

Genetic Algorithm-Based Optimization of Torque Energy-Saving Coordinated Control for Hybrid Electric Vehicle

WANG Ping¹,ZHANG Hong²,LI Chunfu²

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Abstract

In order to improve the energy-saving effect of hybrid electric vehicle, genetic algorithm (GA) was introduced based on the equivalent fuel consumption minimization strategy (ECMS). Then an energy-saving coordinated control strategy was designed to optimize the engine torque system based on GA. With the shock wave intensity of whole vehicle as the objective function of value index, the optimal torque parameters were obtained through GA optimization, and the engine torque in the running stage of mode was optimized to reduce the impact effect and obtain the better torque following effect. The results show that GA optimization plays the role of peak cutting and valley filling on engine torque and hence can obtain higher vehicle power stability. The intensity of shock wave decreases by nearly 45% under NEDC conditions after using the algorithm. GA-ECMS coordinated control scheme can improve the quality of mode switch and the economy of hybrid power system as well. The real road operating condition verifies the coordinated effect of GA-ECMS torque optimization. The GAoptimized hybrid drive can acquire the stable engine torque and achieve the excellent coordinated control performance.

Key words

hybrid；torque / genetic algorithm / coordinated control / energy saving

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WANG Ping,ZHANG Hong,LI Chunfu. Genetic Algorithm-Based Optimization of Torque Energy-Saving Coordinated Control for Hybrid Electric Vehicle[J]. Vehicle Engine. 2023, 0(3): 88-92 https://doi.org/10.3969/j.issn.1001-2222.2023.03.014