A Modified Algorithm for Optimal Estimation of Fuel Cell Parameters

For enhanced performance and efficient operation of a fuel cell (FC) power system, it is indispensable to estimate its intrinsic parameters precisely. Then only, a proper design of the FC system can be accomplished. Here, the parameter estimation problem is articulated in the form of an unique objective function to be minimized. The total of squared deviation (TSD) between the experimental and estimated FC stack voltages is considered to be the objective function. Here, a modified grey wolf optimization algorithm (MDGWOA) is implemented to optimally estimate the parameters of different proton exchange membrane fuel cell (PEMFC) stacks. In the past, many evolutionary approaches were proposed for FC parameter estimation. MDGWOA showcases improved accuracy as compared to other approaches in terms of lesser TSD which is evident from the comparative results.