Adaptive Thermal Management Strategy of Fuel Cell Vehicle Systems with Environmental Adaptability

Thermal management of proton exchange membrane fuel cells plays a crucial role in the long-term stable operation of fuel cell vehicle systems. Existing thermal management strategies ignore the key role of system component characteristic constraints in reducing the influence of thermal perturbations from the vehicle’s exterior environment, making it challenging to achieve the desired control results. In this study, an active adaptive coupled thermal management strategy is proposed. It considers the changing thermal environment and the component characteristics of the thermal management system. The approach combines particle filter estimation, closed-loop model predictive control, and fuzzy control to regulate the critical components of the thermal management system and act in concert to optimize the thermal management of the fuel cell. Compared with the closed-loop model predictive control alone, the strategy proposed in this study reduces the average errors of the stack’s coolant inlet and outlet temperatures by $\mathbf{3 9 . 9 \%}$ and $30.5 \%$, respectively. The proposed active thermal management strategy exhibits excellent performance in an external thermal environment with unpredictable disturbances.