中文摘要：

研究电传动履带车辆再生制动控制策略问题。再生制动技术要保证车辆获得最佳制动效能,延长制动器寿命并充分回收能量,因此对其控制策略提出较高要求。传统的控制策略对门限参数漂移的适应能力较差,存在模式切换频繁,制动器磨损严重和能量回收率较低等问题。为解决上述问题,提出了一种粒子群算法优化的模糊再生制动控制方案,在SIMULINK和d SPACE环境下建立了驾驶员-测试控制器在环的半实物仿真平台,实现了再生制动控制策略的优化设计与实时验证。实验结果表明,与传统门限逻辑控制策略相比,优化的模糊控制策略在能量回收率方面提高了2.83%,在燃油经济性方面提高了31.16%,具有很好的控制效果和实际应用价值。

英文摘要：

The research target of this paper focus on regenerative braking control strategy of electric tracked vehi- cle. In order to ensure the braking efficiency, brake serving life and energy regeneration of vehicle, higher demands are needed for control strategy. Because of poor adaptation in parameter changes, the gateway control has problems in mode switching, brake wear and energy recovery. To solve the problems, a control strategy of regenerative braking was designed through fuzzy logic control. The subordinating degree function was optimized by using a particle swarm optimization algorithm. A driver - controller based hardware - in - the - loop simulation （HILS） platform was built and the control strategy was verified. The simulations rew：al that the optimized fuzzy control is superior to gateway control in energy recuperation by 2. 83% and fuel saves by 31.16% , which will achieve a good control effect and practical value.