基于GA的电动汽车再生制动策略优化

Optimization of Regenerative Braking Strategy for Electric Vehicle Based on GA

制动能量回收是提高电动汽车能量利用率的重要技术,稳定且可靠的制动效能也是衡量车辆性能的重要指标。该文分别建立了驾驶员制动意图模糊识别模型和基于遗传算法的制动力分配优化模型;采用模糊推理的方法识别驾驶员的制动意图,以制动强度大小作为模糊控制器的输出;基于ECE法规和I曲线建立前、后轴制动力分配优化模型,并采用遗传算法对该模型进行求解;在Matlab/Simulink中建立电动汽车制动系统仿真模型。结果表明,采用遗传算法优化的电动汽车制动能量回收控制策略能够有效提高制动过程中的能量回收率,同时保证制动的稳定性。

Braking energy recovery is an important technology to provide energy efficiency for electric vehicles. Stable and reliable braking efficiency is also an important index to measure vehicle performance. The fuzzy identification model of driver braking intention and the optimization model of braking force distribution based on genetic algorithm （GA） are established respectively. The braking intention is identified by fuzzy control method,the severity of braking is used for describing the braking intention. To ensure the stability of braking,the braking force distribution calculation is based on ECE line and I curve,and genetic algorithm is applied to solve the model. The simulation model of vehicle braking system is established with Matlab/Simulink. The results show that the braking energy recovery control strategy of electric vehicle optimized by GA can effectively improve the energy recovery during braking,and ensure the stability of the brake.