Energy Management and Power Distribution in Hybrid Vehicles

As new energy technologies continue to evolve, hybrid electric vehicles (HEV) have emerged as a key transitional choice from gasoline-powered vehicles to new energy vehicles, owing to their extended driving range and environmental benefits. This paper systematically summarizes the structure principles of HEV and outlines three currently mainstream energy management strategies, including those based on deterministic and fuzzy control rules, those based on global and instantaneous optimization, and those based on reinforcement learning and deep learning methods. Additionally, this article also compared the performance characteristics of the three system architectures: series, parallel, and hybrid configuration. Through combined simulation studies, this paper explores the fuel economy and system stability under different strategies. Finally, in response to the challenges in complex operating conditions, this paper points out that intelligent and data-driven approaches will play a crucial role in future energy management. This research provides a theoretical foundation and practical insights for the development of more efficient and intelligent energy management systems in hybrid electric vehicles.