电动汽车燃料电池电压温度参数的逆控制优化

Electric Vehicle Fuel Cell Voltage Temperature Parameter Inverse Control Optimization

摘要:

燃料电池的温度和电压是影响电动汽车性能最关键的两个参数;由于电动汽车燃料电池的温度和电压具有较强的非线性和耦合性的特点,使得传统的线性系统理论无法适用;为此,提出一种基于最小二乘支持向量机(LS-SVM)的燃料电池逆控制优化算法;利用LS-SVM建立燃料电池逆模型,利用RLS算法对燃料电池逆模型进行校验,利用ε-滤波方法对控制器进行在线参数调节;仿真结果证明该逆控制方法能够快速准确地对燃料电池中电压和温度进行精确解耦控制,保证了电动汽车对燃料电池的性能要求。

Abstract:

the fuel cell temperature and voltage are two of the key parameters for the performance of ev. Because the temperature and voltage of the electric car fuel cell has the characteristics of strong nonlinear and coupling, make the traditional linear system theory can not be applicable. For this, put forward a kind of based on least squares support vector machines (LS - SVM) fuel cell inverse control optimization algorithm. The fuel cell was established based on the LS - SVM inverse model, using the RLS algorithm to check fuel cell inverse model, using the epsilon - filter method for on-line parameter adjustment controller. The simulation results show that the inverse control method can fast in the fuel cell voltage and temperature accurately decoupling control, to ensure the electric car performance requirements of fuel cell. 