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E-mobility, or electric mobility, has emerged as a pivotal solution toaddress pressing environmental and sustainability concerns in thetransportation sector. The depletion of fossil fuels, escalating greenhouse gasemissions, and the imperative to combat climate change underscore thesignificance of transitioning to electric vehicles (EVs). This paper seeks toexplore the potential of artificial intelligence (AI) in addressing variouschallenges related to effective energy management in e-mobility systems (EMS).These challenges encompass critical factors such as range anxiety, charge rateoptimization, and the longevity of energy storage in EVs. By analyzing existingliterature, we delve into the role that AI can play in tackling thesechallenges and enabling efficient energy management in EMS. Our objectives aretwofold: to provide an overview of the current state-of-the-art in thisresearch domain and propose effective avenues for future investigations.Through this analysis, we aim to contribute to the advancement of sustainableand efficient e-mobility solutions, shaping a greener and more sustainablefuture for transportation.

A Review on AI Algorithms for Energy Management in E-Mobility Services