Emergent Mind

Abstract

In recent years, fuel cell/battery hybrid systems have attracted substantial attention due to their high energy density and low emissions. The online energy management system (EMS) is essential for these hybrid systems, tasked with controlling the energy flow and ensuring optimal system performance, encompassing fuel efficiency and mitigating fuel cell and battery degradation. This research proposes a novel approach to energy management for hybrid fuel cell/battery systems with multiple fuel cell stacks. It introduces an online EMS that employs Mixed Integer Quadratic Programming (MIQP) to independently control each fuel cell stack in the hybrid system. The performance of this method is compared to Dynamic Programming (DP), a standard approach for energy management in such systems. Results demonstrate that the proposed method achieves superior computational efficiency compared to DP while delivering improved performance. Furthermore, the research reveals that independent control of multiple stacks results in a more optimized system operation compared to traditional methods, which consider multiple stacks as a single entity and implement identical control actions across all.

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