Electric vehicle battery state of health estimation using Incremental Capacity Analysis. (1st August 2023)

• Record Type: Journal Article
• Authors: Gismero, Alejandro; Nørregaard, Kjeld; Johnsen, Bjarne; Stenhøj, Lasse; Stroe, Daniel-Ioan; Schaltz, Erik
• Is Part Of: Journal of energy storage. Volume 64(2023)
• Publication Date: 2023-08-01
• Subjects: Electric vehicle (EV) -- Battery state estimation -- Incremental capacity analysis (ICA) -- Lithium-ion batteries -- State of health (SOH); Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2023.107110
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: The state of health (SOH) is an essential indicator for electric vehicle (EV) batteries. It is important to ensure a proper and safe operation of the battery and of great interest for the increasing second-hand market. As the battery is the most expensive EV component the value of the entire vehicle depends on the SOH. The purpose of this work is to develop and verify a non-invasive method to determine the SOH and study the capability of the incremental capacity analysis (ICA) method to estimate SOH of real EVs. The ICA technique is a common method for battery state estimation through the analysis of the voltage changes produced by the electrochemical reactions that occur during charging and discharging. In this work aging tests have been carried out on cells to determine the ICA features with the best performance to estimate the SOH. LMO/NMC-based batteries used in the BMW i3 have been aged and analyzed using ICA. The position of some of the features extracted from the incremental capacity (IC) curve was used to estimate the SOH of the batteries. Subsequently, in order to verify the method, two vehicles with different mileage were tested using similar conditions, obtaining an accurate SOH estimation with an overall root mean square error (RMSE) of 2%. The proposed method has shown to be effective both in cells and in commercial available vehicles, allowing the estimation of SOH during charging and without the need to interfere in the process. Highlights: Non-intrusive state of health method for electric vehicles through incremental capacity analysis. Extensive calendar and cycling aging tests at cell level. State of health indicators independent from battery aging conditions.