Evolution of Electrical Vehicles, Battery State Estimation, and Future Research Directions: A Critical Review

Abstract

The crucial function of Battery management systems in the world of electric vehicles is thoroughly examined in this extensive article. With the popularity of Electric vehicles skyrocketing, accurate state-of-charge estimation has emerged as a critical element for guaranteeing the best battery performance, longevity, and safety. This work conducts a comprehensive analysis of 210 papers by an organized literature study and thematic analysis. It aims to offer a precise description of State charge estimate approaches, identify areas where information is lacking, and highlight the necessary topics for future research. This paper presents a thorough investigation of the evolution and significance of electric cars in the current period, a topic that has not been previously explored by other reviews. During the process of conducting theme analysis, the advantages and difficulties of high-performing techniques for state of charge prediction are examined, and a comprehensive categorization of hybrid approaches with high accuracy is generated. The literature examines several sorts of approaches based on the Kalman filter. Finally, the most effective method for getting the best possible prediction for the State of charge is explained, along with the progression of these algorithms. This paper concludes with a complete review of current trends in state of charge estimate, derived from an examination of several research paths.

Keywords

• Battery management system
• Kalman filter
• electrical vehicle
• state of charge estimation
• hybrid algorithm