Multi-objective optimization design of a planar membrane humidifier based on NSGA-II and entropy weight TOPSIS

The external humidifier plays an important role in regulating the internal water content and improving the output efficiency of the fuel cells. In the current study, parameter influence research and multi-objective optimization were carried out on the planar membrane humidifier. The length, width, and height of the flow channel and the thickness, porosity, and acid equivalent concentration of the membrane were specified as design variables; the humidification capacity, pressure loss, and volume were set as the optimization objectives. Based on the detailed numerical simulation results, the radial basis function (RBF) meta-model combined with the non-dominated sorting genetic algorithm II (NSGA-II) was employed to approximate the performance of the humidifier and search for the Pareto fronts. Then, the optimal point was selected by the technique of order preference similarity to the ideal solution (TOPSIS) with entropy weight. The validated results showed that the RBF meta-model can achieve high-precision fitting of the performance of humidifiers. It was also found that the channel geometry factors were the most significant design variables for humidifier performance, far exceeding the impacts of membrane-related parameters. In this paper, the influence of geometric parameters and material parameters on the planar membrane humidifier was comprehensively studied, and a complete process of multi-objective optimization was proposed, guiding for determining the design parameters.