Multi-category Parameter Adaptive Optimization Of Direct Methanol Fuel Cell System Based On Co-simulation

Direct Methanol Fuel Cell（DMFC）is one of the most clean power sources that can replace traditional heat engines and batteries.With its advantages of simple structure,easy operation,high energy density and continuous operation,it has broad application prospects in the fields of transportation,communication,portable electronic equipment and national defense.At this stage,DMFC still has problems of methanol penetration,polarization and catalyst poisoning which affect the performance of DMFC.In order to alleviate the above drawbacks,this thesis is dedicated to consider the multi-category parameters,including operating parameters,plate geometry parameters,and the coupling effects of membrane electrode（MEA）physical parameters on DMFC performance,establish a Co-simulation model of Matalab and Fluent,and adaptively optimize DMFC multi-category parameters to improve energy conversion efficiency of DMFC.According to the operating characteristics and performance requirements of DMFC,a multi-parameter adjustable experimental test platform is built and the cell performance test method has been determined in the present research.Based on the experimental polarization curves under different parameters,the multi-category parameters affecting the energy conversion efficiency of DMFC cells were analyzed and determined,including methanol solution concentration C_Me,methanol solution flow rate F_Me,running temperature T and air flow rate F_Air,proton exchange membrane thickness Thickness,cathode catalyst loading Loading and voltage U.Secondly,a Computational Fluid Dynamics（CFD）simulation model that considers the relationship between DMFC performance and multi-category parameters has been established in this thesis.Based on surrogate-assisted hierarchical particle swarm optimization（SHPSO）algorithm,DMFC multi-category parameters are optimized.Finally,a co-simulation model of DMFC,combines SHPSO optimization algorithm and CFD simulation model is established,which greatly improves the parameter optimization efficiency of DMFC while energy conversion efficiency is considered as the index,and realizes adaptive optimization of multi-category parameters.This research shows that the CFD simulation model established in this thesis is verified by experimental results and has high universality and accuracy for simulating the numerical relationship between multi-category parameters and DMFC energy conversion efficiency.In addition,the co-simulation model established in this paper greatly improves the multi-category parameter optimization efficiency of DMFC,and the optimization results are tested.It is also found that the DMFC energy conversion efficiency is 3.80%higher than the maximum energy conversion efficiency of the initial experimental sample,thus verifying the accuracy and effectivenss of the co-simulation model.