Method to Quantify Ohmic Resistance in the Context of Lithium-Ion Cell Ageing

Li-ion cells have a complex voltage response to current due to the combination of resistance contributions from cell internal components. Each of these contributions changes uniquely with degradation. These contributions include multiple sources of ohmic resistance. Ohmic resistance contributions are hard to separate and quantify due as their instantaneous nature prevents time constant separation. This paper uses a novel automated multiple-objective parameter optimization approach for analyzing ohmic resistance results from Electrochemical Impedance Spectroscopy (EIS) at 3 different test temperatures. This allows the overall ohmic resistance contribution to be separated into temperature and non-temperature dependent aspects. This is done through fitting ohmic resistance data using both temperature independent and Arrhenius temperature dependent terms. This equation is structured into a dual optimization function ensuring fitting with both overall accuracy and physical meaning. The optimization minimizes Root Mean Square Error (RMSE) on the resistance data and on the matching of the Arrhenius temperature dependent slope. The approach was proven in a case study comparing an unused baseline Li-ion cell with two Li-ion cells aged through emulated automotive cycling at 45°C. The results showed that the temperature dependent electrolyte resistance stayed almost identical however the temperature independent contact resistance related to the material and electrode-current collector increased noticeably. The paper demonstrates that this proposed approach can give accurate and automated analysis of physically informed finding, allowing for more detailed ohmic resistance modelling and allowing targeted degradation analysis.