Capacity and Impedance Estimation by Analysing and Modeling in Real Time Incremental Capacity Curves

• Main Authors: Mikel Oyarbide, Mikel Arrinda, Denis Sánchez, Haritz Macicior, Paul McGahan, Erik Hoedemaekers, Iosu Cendoya
• Format: Article
• Language: English
• Published: MDPI AG 2020-09-01
• Series: Energies
• Subjects: Li-ion; aging; state of health; incremental capacity; capacity fade; resistance rise
• Online Access: https://www.mdpi.com/1996-1073/13/18/4855

The estimation of lithium ion capacity fade and impedance rise on real application is always a challenging work due to the associated complexity. This work envisages the study of the battery charging profile indicators (CPI) to estimate battery health indicators (capacity and resistance, BHI), for high energy density lithium-ion batteries. Different incremental capacity (IC) parameters of the charging profile will be studied and compared to the battery capacity and resistance, in order to identify the data with the best correlation. In this sense, the constant voltage (CV) step duration, the magnitudes of the IC curve peaks, and the position of these peaks will be studied. Additionally, the behaviour of the IC curve will be modeled to determine if there is any correlation between the IC model parameters and the capacity and resistance. Results show that the developed IC parameter calculation and the correlation strategy are able to evaluate the SOH with less than 1% mean error for capacity and resistance estimation. The algorithm has been implemented on a real battery module and validated on a real platform, emulating heavy duty application conditions. In this preliminary validation, 1% and 3% error has been quantified for capacity and resistance estimation.