Adaptive filter algorithms for state of charge estimation methods: A comprehensive review

Abstract

Battery management system is compulsory for long life and effective utilization of lithium ion battery. State of charge (SOC) is key parameter of battery management system. SOC estimation isn't an easy job. Effective estimation of SOC involves complex algorithms where. Conventional methods of SOC estimation does not take continuously varying battery parameters into account thus large noise in both voltage and current signal are observed resulting in inaccurate estimation of SOC. Therefore, in order to improve the accuracy and precision in SOC estimation, improved adaptive algorithms with better filtering are employed and discussed in this paper. These adaptive algorithms calculate time varying battery parameters and SOC estimation are performed while bringing both time scales into account. These time scales may be slow-varying characteristics or fast-varying characteristics of battery. Some experimentations papers have proved that these adaptive filter algorithms protect battery from severe degradation and accurately calculate battery SOC. This paper reviews all previously known adaptive filter algorithms, which is the future of the electrical vehicles. At the end, a comparison is built based upon recent papers which talked on SOC at their differences in control strategies, efficiency, effectiveness, reliability, computational time and cost.