Research on fuzzy control strategy for electro-hydraulic combined braking energy recovery based on an improved differential evolution algorithm

Abstract

Regenerative braking energy recovery is essential for electric vehicles due to their limited driving range. A fuzzy regenerative braking control strategy based on an improved differential evolution algorithm and segmented braking force distribution is proposed. Firstly, a segmented braking force distribution strategy for the front and rear axles is designed by integrating the ideal braking force distribution curve (I-curve) with ECE regulations. This approach ensures a balance between energy recovery efficiency and driving safety under varying braking intensities. Secondly, a fuzzy controller is developed to regulate the proportion of regenerative braking force. The controller takes vehicle speed, battery state of charge (SOC), and braking intensity as inputs based on the recognition of the driver’s braking intention. Furthermore, an improved differential evolution algorithm with adaptive control parameters is introduced to optimize the membership functions of the fuzzy controller in an offline manner. Ultimately, co-simulation using MATLAB/Simulink and CarSim is conducted to validate the proposed strategy. The results demonstrate that, compared to a baseline fuzzy control strategy, the proposed method increases the energy recovery rate by 15.8% and 14.9% under the New European Driving Cycle (NEDC) and the Worldwide Harmonized Light Vehicles Test Procedure (WLTP), respectively. Moreover, when compared to a fuzzy control strategy optimized by the particle swarm optimization (PSO) algorithm, the proposed strategy achieves additional improvements of 1.04% and 2.90% under the same test cycles, thereby effectively enhancing the energy recovery performance of the electro-hydraulic composite braking system.