Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells

Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant ($\tau$), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (\~2s to less than 1s). This study also shows that the required model parameters (i0S, $\tau$, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios).