Subspace-based modeling and parameter identification of lithium-ion batteries

• Published in: International journal of energy research Vol. 38; no. 8; pp. 1024 - 1038
• Main Authors: Li, Yong, Liao, Chenglin, Wang, Lifang, Wang, Liye, Xu, Dongping
• Format: Journal Article
• Language: English
• Published: Chichester Blackwell Publishing Ltd 25.06.2014; Wiley; John Wiley & Sons, Inc
• Subjects: Algorithms; Applied sciences; Direct energy conversion and energy accumulation; Dynamic characteristics; Electric batteries; electric vehicle; Electric vehicles; Electrical engineering. Electrical power engineering; Electrical power engineering; Electrochemical conversion: primary and secondary batteries, fuel cells; Electrochemistry; Energy; Exact sciences and technology; Excitation; Frequency analysis; frequency-domain characteristics; Lithium; Lithium-ion batteries; lithium-ion battery; Mathematical models; Parameter identification; Robustness; state-space model; subspace identification; Dynamic characteristic; frequency-domain characteristics; electric vehicle; Battery; subspace identification; Lithium; state-space model; Modeling; lithium-ion battery; dynamic characteristics
• ISSN: 0363-907X; 1099-114X
• DOI: 10.1002/er.3124

SUMMARYFor reliable and safe operation of lithium‐ion batteries in electric vehicles, the monitoring of state‐of‐charge and state‐of‐health is necessary. However, these internal states cannot be measured directly, which are usually estimated through model‐based techniques. Therefore, an accurate application‐oriented battery model is of significant importance. The purpose of this paper is to present a novel method on battery modeling and parameter identification. In this work, a state‐space model with clear mathematical and electrochemical meanings is proposed on the basis of the electrochemical basics of lithium‐ion batteries. The frequency‐domain characteristics of the lithium‐ion batteries are also investigated. On the basis of the frequency analysis, an identification test profile that can excite the dynamic characteristics of the battery fully and persistently is proposed. A subspace‐based algorithm is then adopted to identify the parameters of the battery model. The performance and robustness of the estimated model are validated through some experiments and simulations. The validation results show that the proposed method can achieve an acceptable accuracy with the maximum error being less than 2%. Copyright © 2013 John Wiley & Sons, Ltd. A state‐space model with clear mathematical and electrochemical meanings is proposed for a lithium‐ion battery. A novel identification test profile, which can excite the dynamic characteristics of the battery fully and persistently, is designed on the basis of the frequency‐domain characteristics of the lithium‐ion batteries. A subspace‐based algorithm is introduced for the parameter identification of the battery model.