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In the proton exchange membrane fuel cell (PEMFC), the uneven distribution of contact pressure on the gas diffusion layer (GDL) will lead to the increase in local contact voltage, thus increasing the ohmic loss of the stack, and will affect the porosity to change the reaction gas concentration. Therefore, it is essential to optimize the consistency and uniformity of contact pressure. In this paper, the bolt-encapsulated different scale stack models are established. The influence of the cell number on the distribution characteristics of the contact pressure on the outermost and innermost GDLs in different stacks is discussed. According to the GDL contact pressure distribution characteristics in the 6-stack, it is found that it can be used as the data extraction model for optimizing the clamping condition of the 80-stack. Subsequently, the optimal Latin hypercube design is used to randomly generate 280 data sets with different clamping conditions, and a data-driven surrogate model based on the Support Vector Regression is used to predict the contact pressure distribution characteristics of GDLs in the 6-stack according to changes in clamping condition. Then, the surrogate model is taken as the fitness evaluation function in Gray Wolf Optimizer, and the clamping condition of the 80-stack is optimized, which improves the uniformity and consistency of the contact pressure distribution on the GDL by 66.67%. This paper proposes a strategy to optimize the clamping condition of large-scale stacks based on the calculation and prediction of the contact pressure distribution on the GDLs in small-scale stacks.

Intelligent optimization of clamping design of PEM fuel cell stack for high consistency and uniformity of contact pressure