Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation

• Published in: Energies (Basel) Vol. 12; no. 3; p. 446
• Main Authors: Ali, Muhammad Umair, Zafar, Amad, Nengroo, Sarvar Hussain, Hussain, Sadam, Junaid Alvi, Muhammad, Kim, Hee-Je
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 30.01.2019
• Subjects: Alternative energy sources; Batteries; battery management system; Computer engineering; electric vehicle; Electric vehicles; Electrical engineering; Electrodes; energy storage system; Lithium; lithium-ion battery; state of charge; United States > US; China; Pakistan
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en12030446

Energy storage system (ESS) technology is still the logjam for the electric vehicle (EV) industry. Lithium-ion (Li-ion) batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life. The accurate estimation of the state of charge (SOC) of a Li-ion battery is a very challenging task because the Li-ion battery is a highly time variant, non-linear, and complex electrochemical system. This paper explains the workings of a Li-ion battery, provides the main features of a smart BMS, and comprehensively reviews its SOC estimation methods. These SOC estimation methods have been classified into four main categories depending on their nature. A critical explanation, including their merits, limitations, and their estimation errors from other studies, is provided. Some recommendations depending on the development of technology are suggested to improve the online estimation.