Health-aware Energy Management Strategy for Fuel Cell Hybrid Self-Guided Vehicle with Conflict-aware Navigation Approach

Industry 4.0 has significantly advanced automation and robotics, making Self-Guided Vehicles (SGVs) essential in modern manufacturing for improving efficiency and productivity. Hybrid SGVs, combining batteries and Fuel Cells (FCs), are proposed as a robust solution to meet energy concerns. However, the dynamic and unpredictable nature of manufacturing environments requires an advanced Energy Management System (EMS) for such SGVs. This EMS must adapt to varying conditions and frequent start-stop cycles, which is crucial for maintaining the health and efficiency of the FC. To make the EMS more suitable for these environments, adaptive navigation should be designed to optimize the process by learning from previous missions, improving motion execution, and generating efficient power profiles. Therefore, this paper proposes a FC health-aware EMS integrated with adaptive navigation to optimize power distribution between the FC and battery. Our approach addresses the challenges of dynamic environments, enhancing energy efficiency and extending the operational lifespan of SGVs. The results show that combining the two strategies improves power distribution of the energy sources of Hybrid SGVs in dynamic environments.