Lithium-Ion Battery State-of-Health Estimation Using the Incremental Capacity Analysis Technique

• Published in: IEEE transactions on industry applications Vol. 56; no. 1; pp. 678 - 685
• Main Authors: Stroe, Daniel-Ioan, Schaltz, Erik
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aging; Algorithms; Battery charge measurement; Electric vehicle; Electric vehicles; Estimation; incremental capacity analysis; Integrated circuits; Lithium; Lithium-ion batteries; lithium-ion battery; Management systems; Model accuracy; Power management; Rechargeable batteries; state-of-health (SOH) estimation; Temperature measurement
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2019.2955396

The implementation of an accurate and low computational demanding state-of-health (SOH) estimation algorithm represents a key challenge for the battery management systems in electric vehicle (EV) applications. In this article, we investigate the suitability of the incremental capacity analysis (ICA) technique for estimating the capacity fade and subsequently the SOH of LMO/NMC-based EV lithium-ion batteries. Based on calendar aging results collected during 11 months of testing, we were able to relate the capacity fade of the studied batteries to the evolution of four metric points, which were obtained using the ICA. Furthermore, the accuracy of the proposed models for capacity fade and SOH estimation was successfully verified considering two different aging conditions.