Post-prognostics decision-making strategy for load allocation on a stochastically deteriorating multi-stack fuel cell system

This work proposes a load allocation decision strategy based on deterioration prognostics information for multi-stack fuel cell systems. The is characterized by the overall resistance value, as it carries key aging of cell. dynamics then modeled an increasing stochastic process whose trend function output power. Combining system and consumption, multi-objective optimization (MOO) decision-making proposed to manage operation system. Based this algorithm, optimal operating power computed each stack. Finally, performance approach compared case without post-prognostics three-stack simulation results show that can in real time scheduling among stacks.