An electrochemical impedance spectroscopy-based battery charging strategy considering lithium plating

Large-scale battery systems, comprising series- or parallel-connected battery cells, are widely deployed in applications such as electric vehicles and grid-level energy storage. To ensure safe operation, it is critical to regulate the battery’s power output within its allowable limits to prevent violations of individual cell constraints. This becomes particularly important during fast charging, overcharging can lead to lithium plating on the anode, increasing the risk of thermal runaway. Electrochemical Impedance Spectroscopy (EIS) offers insight into the internal electrochemical behavior of batteries by analyzing their response to alternating current (AC) excitations across a wide frequency range. This capability enables early detection of lithium plating. Leveraging EIS measurement and analysis data, this work proposes an improved Football Team Training Algorithm (FTTA) for identifying parameters of a fractional-order (FO) battery model. Building upon this, a lithium plating-aware charging prediction strategy is developed to guide fast charging operations. Experimental results demonstrate that the proposed method improves charging speed by 11% and reduces per-cycle capacity degradation to 73% of that observed with conventional constant current (CC) charging.