An Adaptive Joint Operating Parameters Optimization Approach for Active Direct Methanol Fuel Cells

The operating parameters of the active direct methanol fuel cell (DMFC) are essential factors that affect performance. However, it is challenging to maintain optimal maximum output power density due system’s complexity, conditions variation, and correlations between those parameters. This paper proposes an adaptive joint optimization method for methods include numerical simulation operation Based on orthogonal tests, a BP neural network used build performance evaluation model can quantify influence combination obtained by whale algorithm (WOA) through model. experimental results show could respond accurately adaptively under different conditions. improves 8.71%.