Parameter sensitivity analysis of electrochemical model-based battery management systems for lithium-ion batteries

Accurate identification of physical parameters of a lithium-ion electrochemical model is of critical importance fornext-generation battery management systems. The complexity of the electrochemical model increases the difficultyof the identification process, and hence the analysis of parameter identifiability is the cornerstone for accurateparameter identification. The overarching goal of this paper is to analyze the parameter sensitivity of an electrochemicalmodel under both the charging process and real-world driving cycles. The boundaries for the sensitivityanalysis of 26 physical parameters are determined with a systematic benchmarking of published parametersfor lithium Nickel-Manganese-Cobalt-Oxide/graphite cells. In particular, the sensitivity of the parameters is analyzednot only for terminal voltage but also for essential states in an electrochemical model-based battery managementsystem, e.g., cathode bulk state of charge, cathode surface state of charge and anode potential. Thesensitivity matrices of the parameters under different C-rates and depth of discharge regions clearly show theirdifferent influences on capacity-related parameters and other parameters. Furthermore, the rankings of the normalizedparameter sensitivity index provide us the identifiability of the parameters, as well as the influence ofparameter inaccuracy on the main functionalities in an electrochemical model-based battery management system