This study explores the design of a tapered cathode flow channel in a proton exchange membrane fuel cell (PEMFC), leveraging artificial intelligence and multi-objective optimization techniques to attain an optimal configuration. First, the influence of the channel height ratio and mass flow rate on PEMFC performance was systematically examined. The results reveal that decreasing the height ratio and increasing the mass flow rate lead to reduction in the standard deviation of current density, accompanied by a monotonic rise in pressure drop. The average current density initially rises before exhibiting a slight decline. Subsequently, a surrogate model based on a Backpropagation (BP) neural network was constructed, with height ratio and mass flow rate as input variables, to accurately predict the average current density, its standard deviation, and the channel pressure drop. The findings demonstrate that the BP-based surrogate model can reliably predict current density, its standard deviation, and channel pressure drop. The Mean Relative Errors (MREs) for current density, standard deviation, and pressure drop are 0.84%, 1.44%, and 1.77%, respectively, with all coefficients of determination (R²) exceeding 0.999. Finally, Pareto optimal solutions for current density, standard deviation, and pressure drop of the tapered PEMFC were obtained through integration a multi-objective genetic algorithm. Results show that the optimized tapered PEMFC achieves the current density of 3141.41 A/m², the standard deviation of 53.58 A/m², and the channel pressure drop of 5.49 Pa. Compared with the conventional channel, the optimized PEMFC exhibits an 7.02% increase in current density and an 3.7% reduction in standard deviation, while maintaining the pressure drop within an acceptable range.

The proton exchange membrane fuel cell (PEMFC) and the hydrogen hybrid power system are studied by the fuzzy-PID (FPID) control method and the fuzzy-PID control method by Artificial Bee Colony algorithm (ABC-FPID), respectively. The results reveal that compared with the FPID control method, the temperature overshoot of the PEMFC stack under the ABC-FPID control method is decreased by 0.6%. Moreover, the circulating water flow rate within the full operating envelope (about 3 min) is reduced by 19.46 L, which means the ABC-FPID control method is more effective in regulating the stack temperature. Then, the ABC-FPID control method is proposed to study the hydrogen hybrid power system, and the system output power matching, operating characteristic curve of the fuel cell, state of charge (SOC) of the lithium battery, system efficiency and hydrogen demand are obtained. The results indicate that the maximum system efficiency reaches 46.3%, the average system efficiency is 33.8%, and the average hydrogen demand is 0.192 kg/s. Overall, the ABC-FPID control method can efficiently ensure the stability of the fuel cell’s output power, and actively prompt the lithium battery to fulfill the function of “peak shaving and valley filling” under variable load power conditions.