It is essential to understand the state-of-health (SOH) of the individual electrode to avoid accelerating degradation of Li-ion battery. Electrode SOH can be quantified based on estimating the capacity and the utilization range of each electrode. Here, we introduce two methods: i) voltage fitting (VF) and ii) peak alignment (PA), and compare their ability to estimate the electrode SOH parameters. Both methods assume the half-cell open-circuit potentials (OCPs) are invariant functions of the stoichio-metric states with the cell aging, which can make the accuracy of the electrode parameter estimation vulnerable to degradation that would cause changes in the half-cell OCP curves. This hypothesis is verified experimentally by applying the two methods to aged cells cycled at high temperature. A discernible misalignment of the peaks is observed in the differential voltage curve from the VF method indicating the estimation result is incorrect, even though it reconstructs the OCV with the small error and estimates the cell capacity accurately. Therefore, it is seen that the lower voltage error and the accurate cell capacity estimate do not necessarily promise a better estimation accuracy for the electrode SOH parameters.
- Dynamic Systems and Control Division
Comparison of Individual-Electrode State of Health Estimation Methods for Lithium Ion Battery Available to Purchase
Lee, S, Siegel, JB, Stefanopoulou, AG, Lee, J, & Lee, T. "Comparison of Individual-Electrode State of Health Estimation Methods for Lithium Ion Battery." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems. Atlanta, Georgia, USA. September 30–October 3, 2018. V002T19A002. ASME. https://doi.org/10.1115/DSCC2018-9014
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