The article presents a study on optimizing the performance of a single-channel high-temperature proton exchange membrane fuel cell (PEMFC) through a three-dimensional simulation model and multi-objective optimization. Five main influencing factors were identified, and optimization objectives included power density, system efficiency, and exergy efficiency. The research compared the prediction accuracies of response surface methodology (RSM) and artificial neural network (ANN) for evaluating high-temperature PEMFC performance. The optimal solution derived through RSM-NSGA III resulted in maximum power density, system efficiency, and exergy efficiency. Additionally, combining EWM with VIKOR provided the best solution, enhancing the efficiency of the high-temperature PEMFC. The article emphasizes the importance of finding clean renewable energy sources like hydrogen-fueled PEMFC to combat environmental degradation and the energy crisis. It highlights the advantages of high-temperature PEMFC over conventional low-temperature PEMFC and discusses the challenges faced by PEMFC technology. Various influencing factors on PEMFC performance are explored, and previous studies on PEMFC improvements are referenced. The study concludes by providing suggestions for enhancing the design of high-temperature PEMFC for improved performance and reduced production costs.