Real-time optimal power sharing in multi-stack fuel cells

This paper presents a real-time optimization strategy for power allocation between two fuel cell stacks, maximizing overall efficiency while minimizing hydrogen consumption. The proposed method accounts for stack degradation, characterized by a time-varying electron transfer coefficient (alpha), estimated in real-time using RLSKalman filtering from voltage measurements. The strategy also considers hydrogen crossover effects, which impact fuel efficiency and utilization. The optimization approach was evaluated against two conventional strategies-equal distribution and daisy chain-demonstrating superior performance across various operating scenarios. A new efficiency-based daisy chain algorithm was introduced and compared with the classical powerbased method, further highlighting the benefits of the optimization framework. The real-time formulation enables on-the-fly parameter estimation and model updates, making it adaptable to multiple stacks and various objective functions. This approach provides a robust and scalable solution for fuel cell power management under degradation, aging, and other adverse conditions.