Robust model for optimization of forming process for metallic bipolar plates of cleaner energy production system

Energy production systems such as proton-exchange membrane fuel cell (PEMFC) has a promising future in the cleaner energy market due to zero emissions. Rubber pad forming (RPF) process of metallic bipolar plates of PEMFCs is gaining attention among the researchers. Studies based on design of experiments have been conducted to find the crucial parameters of the forming process. These methods are based on the assumptions of the model structure, correlated residuals, etc., which can cause uncertainty in estimation ability of the model on unseen data. Therefore, the present study focuses on the design of robust models of these parameters for PEMFCs using an optimization approach of genetic programming (GP). The inputs from the experiments considered in GP are radius, the friction coefficient, the filling factor and the minimum thickness. Experiments on PEMFCs validates the performance of the GP models. Further, the relationships between the two inputs and the three outputs for PEMFCs are generated as well as the contributions of each input to each of the output. Optimization of the models generated by GP can further determine the forming quality of metallic bipolar plates of PEMFCs by an appropriate setting of the two inputs.