Nonlinear Stochastic Adaptive Control of PEMFC Temperature Management System

To address the problem of the proton exchange membrane fuel cell (PEMFC) temperature management under stochastic disturbances, this paper integrates a PEMFC thermal model with a water pump model and establishes a nonlinear stochastic model for temperature regulation. The objective is to maintain the stack temperature at its optimal value. Due to the inherent complexity of the PEMFC electrochemical reactions, the thermal dynamics exhibit strong nonlinear characteristics. To tackle this issue, a control strategy based on the stochastic backstepping method is proposed. Furthermore, to cope with variations in membrane water content and ambient temperature during operation, we design stochastic estimator-based adaptive laws. Simulation results, considering both stochastic disturbances driven by tracking error and those driven by stack temperature and load current, indicate that the proposed control strategy effectively maintains the stack temperature at 343 K under various operating conditions, with a maximum deviation of 0.2 K, thereby confirming its effectiveness and robustness.