Temperature control of proton exchange membrane fuel cell thermal management system based on fuzzy PID

The temperature regulation of the fuel cell thermal management system is characterized by slow response speed, system oscillation, and strong coupling, which is prone to problems with unstable temperature control and affects the characteristics of the fuel cell and the lifetime of the electric stack. For a 300kW high-power fuel cell system, to effectively control the flow of the thermal management system to achieve temperature regulation accurately, this paper proposes a fuzzy PID control strategy based on the optimization of the genetic algorithm. By establishing the model of the electric stack and thermal management system, including the core components such as the water pump, radiator, fan, temperature control valve, etc., the response mechanism of the thermal management system and the flow distribution and heat exchange of each component are analyzed. Based on the existing test data and related debugging experience, the basic fuzzy rule system is designed, after which the genetic algorithm is used for adaptive adjustment and dynamic optimization of control parameters. The system modeling is carried out in Matlab/Simulink, and a variety of widely varying current test conditions are designed. The simulation results show that compared with the traditional PID control strategy, this control strategy can effectively decouple the cooling fan and circulating water pump, realize the precise control of the fuel cell temperature under different working conditions, and reduce the amount of system oscillation and the degree of fluctuation of the fuel cell stack voltage.