Optimization and matching of the air loop system in a fuel cell for high-altitude application

Given the serious net power decline and excessive mass of the system in heavy power fuel cells (FCs) operating at variable altitudes, optimizing and matching the appropriate air compressor of FC emerged as a prominent area of research. This study aims to perform multi-objective and multi-parameter optimization of the FC air loop to improve the performance of the FC system for heavy power under a variable altitude environment. Based on the experimental test data, combined with semi-empirical and semi-mechanism equations, five air compressor models with different power levels were developed, and their performance covered the altitude from 0 to 4000 m. Pareto theory is introduced to evaluate the three-dimensional objectives of cathode system mass, isentropic efficiency, and system net power under different air supply parameters and different power levels of air compressors. The Pareto front is solved by a multi-objective particle swarm optimization (MOPSO) algorithm under different altitudes. The results show that compared with the single-objective PSO with customized weight summation (PSO1 and PSO2), MOPSO improves 2.38% and 8.89% for net power, respectively. The three objectives for the optimized configuration are −12.20% (0.61%), 15.87% (27.40%), and 23.96% (−2.74%) improved than baseline1 (baseline2) for the 4000 m altitude.