基于Nelder-Mead优化的PEMFC三阶RQ等效电路参数辨识研究

精确、有效的燃料电池等效电路有助于分析燃料电池内部工作情况,确保燃料电池系统稳定可靠地运行。针对燃料电池内部工作状态无法使用传感器精确监测的问题,提出了基于Nelder-Mead优化算法的PEMFC 3阶RQ等效电路参数辨识方法 ,根据电池工作原理建立3阶RQ非线性等效电路模型,将模型参数与实际物理意义相结合建立复数域下的实部、虚部加权目标函数,最后在电化学交流阻抗谱实验的基础上进行参数辨识研究。研究结果表明:在相同初始条件下,Nelder-Mead优化算法在精度、速度上与最小二乘法相当,但抗干扰能力更强;与遗传算法相比,精度相当但速度更高,可以用于燃料电池的在线参数辨识。

Research on Parameter Identification of Third-order RQ Equivalent Circuit of PEMFC Based on Nelder-Mead Optimization

An accurate and effective equivalent circuit of fuel cell helps to analyze the internal working conditions of the fuel cell and ensure the stable and reliable operation of the fuel cell system. Aiming at the problem that the internal working state of the fuel cell cannot be accurately monitored by sensors, a parameter identification method for the third-order RQ equivalent circuit of proton exchange membrane fuel cell(PEMFC) was proposed based on the Nelder-Mead optimization algorithm. According to the working principle of the battery, a third-order RQ nonlinear equivalent circuit model was established. The model parameters and the actual physical meaning were combined to establish the weighted objective functions of the real and imaginary parts in the complex domain. Finally, parameter identification was carried out based on an electrochemical AC impedance spectroscopy experiment. Research results showed that under the same initial conditions, the Nelder-Mead optimization algorithm was equivalent to the least squares method in terms of accuracy and speed, but its anti-interference capability was stronger; compared with the genetic algorithm, its accuracy was comparable but its speed was higher, thus it can be used for the online parameter identification of fuel cell.