Intelligent Battery Management in Electric Vehicles: A Comprehensive Review of AI Techniques

To reduce carbon emissions and tackle global environmental problems, the automotive sector has focused heavily on electric vehicles (EVs). However, the eventual deterioration of battery health and performance may adversely affect the efficiency of EVs. Due to their ability to accurately assess battery health, analyse faults, and control temperature for enhanced safety, reliability, and effective optimisation of EV performance, artificial intelligence (AI) techniques have garnered significant interest. This review investigates and evaluates the effects of AI techniques to improve the battery management system (BMS) of electric vehicles (EVs). A variety of methodologies are employed to perform a statistical analysis of relevant BMS papers. The statistical analysis assesses essential characteristics such as current research trends, keyword analysis, nation analysis, authorship, collaboration, publishers, and research classification. Moreover, a thorough examination of the goals, contributions, advantages, and disadvantages of advanced AI methods is provided. In addition, several key guidelines and recommendations are presented, along with a number of significant concerns and challenges, for potential future enhancement. Future researchers could utilise the statistical analysis as a guide to develop innovative BMS technologies for EVs that function and are managed sustainably.