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

Abstract

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 (α), estimated in real-time using RLS-Kalman 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 power-based 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.