基于最大功率搜索的PEMFC冷启动协同MPC优化研究OA

In allusion to the optimization control problems in the cold start process of proton exchange membrane fuel cells(PEMFC),a method of optimization based on maximum power search collaborative model predictive control(Pmax-MPC)is proposed.After analyzing the mechanism characteristics and existing challenges of PEMFC cold start process,a mathematical model of fuel cell single cell system is established,and an model predictive control(MPC)controller is designed.The MPC algorithm is used to predict the relationship curve between current and power during the battery start-up process.The extreme value search algorithm is used to obtain the maximum power point of the battery from the predicted value,achieving the maximum power optimization control during the cold start process.The Matlab/Simulink software is used to establish the lumped parameter simulation model of the fuel cell system,so as to validate the control strategy.The simulation results show that the proposed control optimization strategy can shorten the self-start time of fuel cells at-10℃by 24.5%,and can ensure that the maximum ice volume fraction inside the cell during cold start does not exceed 65%.While shortening the cold start time of fuel cells,it effectively suppresses the growth of ice integral number,providing a new idea for the rapid start of PEMFC in low-temperature environments.