# Online energy management system for a fuel cell/battery hybrid system with multiple fuel cell stacks

**Authors:** Junzhe Shi, Ulf Jakob Flø Aarsnes, Dagfinn Nærheim, Scott Moura  
**arXiv:** [2310.13208](https://arxiv.org/abs/2310.13208)  
**Date:** 2023-10-20  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2310.13208v1/

## Key points

- Fuel cell/battery hybrid systems have gained attention for high energy density and low emissions
- Online Energy Management System (EMS) is crucial for optimizing performance by controlling energy flow, maximizing fuel efficiency, and minimizing degradation
- Proposed online EMS uses Mixed Integer Quadratic Programming (MIQP) to independently control each fuel cell stack in the system
- MIQP-based approach offers superior computational efficiency and enhanced overall system performance compared to Dynamic Programming (DP)
- Individualized control of multiple stacks leads to more optimized system operation than traditional methods treating all stacks as a single entity
- Focus on fuel efficiency optimization contributes to sustainable and environmentally-friendly energy solutions.

## Summary

Fuel Cell/Battery Hybrid Systems: Enhancing Performance with an Online Energy Management System

 have gained significant attention in recent years for their high energy density and low emissions. To optimize the performance of these systems, an <b>online energy management system (EMS)</b> is crucial for controlling energy flow, maximizing fuel efficiency, and minimizing degradation of fuel cells and batteries. This study introduces a novel approach to energy management for hybrid fuel cell/battery systems with multiple fuel cell stacks. The proposed online EMS utilizes <b>Mixed Integer Quadratic Programming (MIQP)</b> to independently control each fuel cell stack within the hybrid system. A comparative analysis is conducted against <b>Dynamic Programming (DP)</b>, a conventional method for energy management in such systems. Results indicate that the MIQP-based approach offers superior computational efficiency while delivering enhanced overall system performance. Furthermore, the research highlights that individualized control of multiple stacks leads to more optimized system operation compared to traditional methods that treat multiple stacks as a single entity with uniform control actions across all units. This innovative strategy demonstrates promising potential for advancing the efficiency and effectiveness of hybrid fuel cell/battery systems in various applications. With its focus on <b>fuel efficiency optimization</b>, this study contributes to the ongoing efforts towards sustainable and environmentally-friendly energy solutions.