Review on the State of Charge Estimation Methods for Electric Vehicle Battery

• Published in: World electric vehicle journal Vol. 11; no. 1; p. 23
• Main Authors: Zhang, Mingyue, Fan, Xiaobin
• Format: Journal Article
• Language: English
• Published: MDPI AG 01.03.2020
• Subjects: batteries; control-theory-driven estimation; electric vehicles; multi-scale; state of charge; test-driven estimation
• ISSN: 2032-6653; 2032-6653
• DOI: 10.3390/wevj11010023

Battery technology has been one of the bottlenecks in electric cars. Whether it is in theory or in practice, the research on battery management is extremely important, especially for battery state-of-charge estimation. In fact, the battery has a strong time-varying and non-linear properties, which are extremely complex. Therefore, accurately estimating the state of charge is a challenging task. This paper reviews various representative patents and papers related to the state of charge estimation methods for an electric vehicle battery. According to their theoretical and experimental characteristics, the estimation methods were classified into three groups: the traditional methods based on the battery experiments, the modern methods based on control theory, and other methods based on the innovative ideas, especially focusing on the algorithms based on control theory. The results imply that the algorithms based on control theory, especially intelligent algorithms, are the focus of research in this field. The future development direction is to establish a rich database, improve hardware technology, come up with a much better battery model, and give full play to the advantages of each algorithm.