Predictive coordination control algorithm for cooling system of a 140-kW proton exchange membrane fuel cell stack based on decoupling of component function
Aug 2026· International Journal of Green Energy· Vol 23, pp. 3111 - 3125· 0 citations· 33 references
Abstract
ABSTRACT Operating temperature dominates performance and durability of proton exchange membrane fuel cell, and optimal control of operating temperature is essential for high performance and longer lifespan. Hence, this paper proposes predictive coordination control algorithm for cooling system of fuel cell stack. Lumped-parameter dynamic model of cooling system is established to quantify time constant of stack temperature and influence of time latency on temperature at stack inlet and outlet. Isolation-based analysis of heat exchange between heat generation and dissipation decouples component functions by considering coolant recirculation transport, and relationship between actuators and control targets is determined. Time latency and radiator heat dissipation are compensated predictively, and predictive coordination control algorithm is developed for three temperature objectives and three actuators. Simulation shows that proposed algorithm reduces temperature overshoot by more than 50% and settling time by 30% compared with PI controller, with relative errors within ±1.23% and ±2.05% for coolant temperature at stack inlet and outlet respectively. Experiment demonstrates that maximal overshoots are within 0.6% and 0.8% respectively, while maximal steady-state relative errors are within 0.4% and 0.5% respectively, with settling times below 28 s and 24 s respectively. Proposed algorithm effectively improves steady-state accuracy and transient response of cooling system. HIGHLIGHTS Dynamic model reveals thermal inertia and large transport delay for the cooling system. Function decoupling contributes to the relation between actuators and control targets. A predictive coordination control algorithm is developed for the cooling system. Simulation proves better performance of the proposed algorithm compared to PI control. Experiment validates the control performance for stable error and transient response.
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