Uncertainty-aware state estimation for electrochemical model-based fast charging control of lithium-ion batteries

Abstract

Fast charging capability is considered a critical factor for the widespread adoption of electric vehicles. High charging currents can, however, severely affect battery health due to the danger of metallic lithium deposition on the anode and consequent degradation reactions. The charging speed should therefore be limited with respect to battery temperature, state of charge, and cell design, governing the onset point of lithium plating. Electrochemical models are a suitable tool providing continuous estimates of the anode potential as the main lithium plating indicator while covering a wide operational range. In this article, we present a novel charging control scheme based on a real-time capable simulation framework with adjustable model resolution. A profound investigation of error sources and modeling uncertainties motivates online state corrections towards a lower bound of the anode potential, which are realized by selective adjustments of the lithium distribution within electrode particles based on the full cell voltage error. Simulations of controlled and conventional CC charging profiles indicate the importance of continuously adapting the charging power for different operating conditions. Further, simulated state and parameter distortions as they might result from initialization and parameterization errors show that our estimation strategy can mitigate the risk of unsafe control operations.