ISG型混合动力汽车粒子群优化模糊控制研究

Research on Particle Swarm Optimization Fuzzy Control for ISG Hybrid Electric Vehicle

针对ISG型混合动力汽车能量分配的控制过程,应用传统的模糊控制存在精度不高、自适应能力有限等问题。提出一种粒子群优化模糊控制的方法。在应用传统模糊逻辑建立控制模型基础上,利用粒子群算法对模糊控制中的隶属度函数进行优化,实现了优化的隶属度函数随环境变化以及负载变化实时跟踪模糊控制器的参数变化。仿真结果表明,与Insight控制策略和传统模糊控制策略相比,该方法能够降低电池组SOC变化,同时提高混合动力系统的燃油经济性。试验结果验证使用该方法能够在一定程度上将电池SOC控制在比较合理的范围。

In the process of controlling the energy distribution of ISG hybrid vehicle,lower precision and limited adaptive capability were caused by using the traditional fuzzy control strategy.A novel particle swarm optimization fuzzy control strategy was proposed.By using particle swarm algorithm,the membership function was optimized based on the control model built by the traditional fuzzy logic.The fuzzy controller parameters that real-time traced by the optimized membership function with environment and load changing was realized.The simulation result shows that this method is able to reduce the change of battery SOC and improve the fuel economy of hybrid electric system compared with using Insight control strategy and the traditional fuzzy control strategy.The experimental result proves that the battery SOC can be controlled within a reasonable scope with this method.