In order to control the temperature of PEMFC in a certain range,a method of adjusting MPC parameters based on BP-neural network was proposed.Firstly,Build the temperature model of PEMFC(including nonlinear and linear models),then give the step-change load current,the cooling water flow was adjusted by MPC,and the collected data samples were trained by neu-ral network,finally,the trained BP Neural Network generated Simulink module is connected to the MPC controller to adjust the two weight parameters of the controller,which makes the effect of the MPC controller more ideal.It turns out the temperature con-trol strategy can improve the control effect of MPC and control the temperature of PEMFC in an ideal range.
关键词
质子交换膜燃料电池/权重参数/BP-神经网络/参数整定/MPC/温度控制
Key words
PEMFC/Weight Parameter/BP-Neural Network/Parameter Setting/MPC/Temperature Control
维普
万方数据