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Li-ion cell degradation has a strong impact on electric vehicle performance both directly, through performance reduction, and indirectly through deviating behavior away from initial control system calibration. This necessitates a process for evaluating degradation causes and quantifying corresponding behavioral changes. This paper shows a holistic approach for achieving this, giving both an insight into the causes of cell degradation and emulation of the resultant performance changes through a virtual tools platform which can be used for degradation algorithm development. Additionally, the paper is an overview of the novel methodology developed within the process including testing, data evaluation, modelling and electrical and chemical validation. The process makes use of electrical cycling and electrochemical impedance spectroscopy (EIS) data to evaluate cell stoichiometry and individual impedance features to achieve a much more comprehensive ageing behavioral adaptation than is typically present in Li-ion cell equivalent circuit models. This is achieved while maintaining the versatility and computational efficiency of compact model approaches. The outlined process also gives a resolution of performance changes that allow for conclusions to be drawn on the root causes of ageing only through evaluation of electrical data, which is itself significant. Chemical analysis results are shown to verify the validity of the ageing cause conclusions shown by the process. |
