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<p>This paper presents an electro-hydraulic composite braking coordination control strategy for optimizing energy efficiency in plug-in hybrid electric vehicles by integrating regenerative and mechanical braking. The approach is based on a three-speed hybrid unique gearbox (3-DHT). Initially, a working mode division strategy is developed to address the dynamic coupling during multi-mode switching in the front axle 3-DHT gearbox. This strategy is established considering the torque characteristics of the front axle dual motors. The differential evolution (DE) algorithm is employed to determine the braking force distribution coefficient that maximizes system efficiency. Subsequently, a joint constraint model incorporating braking strength and road adhesion coefficient is formulated. A refined DE algorithm is employed to dynamically distribute front-rear braking force based on real-time road conditions. Simulation outcomes generated through AVL-CRUISE/Simulink/CarSim illustrate that the proposed approach boosts braking energy recuperation by 4.10% (NEDC) and 2.63% (WLTC) relative to an ideal distribution. This advancement diminishes repercussions, enhances fluidity, and guarantees safety throughout braking maneuvers.</p>

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Optimized Composite Braking Energy Recovery Control for Plug-in Hybrid Electric Vehicle with a 3-Speed Dedicated Hybrid Transmission

  • 期刊论文

  • 发表日期：

    2025年7月13日

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  • Xuanyao Wang,
  • Qing Wang

摘要

This paper presents an electro-hydraulic composite braking coordination control strategy for optimizing energy efficiency in plug-in hybrid electric vehicles by integrating regenerative and mechanical braking. The approach is based on a three-speed hybrid unique gearbox (3-DHT). Initially, a working mode division strategy is developed to address the dynamic coupling during multi-mode switching in the front axle 3-DHT gearbox. This strategy is established considering the torque characteristics of the front axle dual motors. The differential evolution (DE) algorithm is employed to determine the braking force distribution coefficient that maximizes system efficiency. Subsequently, a joint constraint model incorporating braking strength and road adhesion coefficient is formulated. A refined DE algorithm is employed to dynamically distribute front-rear braking force based on real-time road conditions. Simulation outcomes generated through AVL-CRUISE/Simulink/CarSim illustrate that the proposed approach boosts braking energy recuperation by 4.10% (NEDC) and 2.63% (WLTC) relative to an ideal distribution. This advancement diminishes repercussions, enhances fluidity, and guarantees safety throughout braking maneuvers.