A CBR-Based Energy Management Framework for Hybrid UAVs Based on State Extraction

Energy management in hybrid drones faces significant challenges due to computational complexity and adaptability requirements in dynamic environments. In response, this article presents a multistage framework for a hybrid drone's real-time energy management system (EMS) that employs a case-based reasoning (CBR) method. CBR requires minimal computational resources, making it ideal for real-time applications, such as hybrid drone EMS. The framework ensures CBR's adaptability by extracting comprehensive state variables' data under optimal conditions across a wide array of load scenarios. The state variables' dataset, which is extracted and reduced offline, serves as a repository that CBR relies on for real-time decision-making. The superiority of the proposed framework in terms of adaptability and computational efficiency is verified by evaluating it against various benchmark EMSs through extensive simulations.