Optimal energy management strategies for hybrid electric vehicles: A recent survey of machine learning approaches

Hybrid Electric Vehicles (HEVs) have emerged as a viable option for reducing pollution and attaining fuel savings in addition to reducing emissions. The effectiveness of HEVs heavily relies on the energy management strategies (EMSs) employed, as it directly impacts vehicle fuel consumption. Developing suitable EMSs for HEVs poses a challenge, as the goal is to maximize fuel economy yet optimize vehicle performance. EMSs algorithms are critical in determining power distribution between the engine and motor in HEVs. Traditionally, EMSs for HEVs have been developed based on optimal control theory. However, in recent years, a rising number of people have been interested in utilizing machine-learning techniques to enhance EMSs performance. This article presents a current analysis of various EMSs proposed in…