Optimization of pure electric vehicle regenerative braking fuzzy control strategy using improved whale algorithm

doi:10.16731/j.cnki.1671-3133.2024.11.013

Abstract

Abstract: To enhance the regenerative braking energy recovery rate of pure electric vehicles while ensuring effective braking performance,a refined approach was proposed to optimize the fuzzy control strategy using an improved whale algorithm. Introducing battery State of Charge (SOC),vehicle speed,and braking intensity as fuzzy control inputs,with regenerative braking proportion coefficient K as the output,the control parameters were optimized using an improved whale algorithm,thereby enhancing the proportion of braking power provided by the front axle motor. Concurrently,refining the adaptive weights of the whale algorithm prevents the algorithm from converging to local optima during the iterative process. Through simulation analysis,the enhanced fuzzy control strategy proposed has been validated to not only improve energy recovery compared to both the pre-optimized and traditional control strategies but also ensure braking effectiveness under NEDC conditions.

Key words: pure electric vehicle, regenerative braking, fuzzy control, improved whale algorithm

CLC Number:

U469.72

LI Huaxin, CHEN Fangfang, XU Tianqi, CHENG Sanbang, MAO Yisheng. Optimization of pure electric vehicle regenerative braking fuzzy control strategy using improved whale algorithm[J]. Modern Manufacturing Engineering, 2024, 530(11): 96-102.

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