Quantifying Lithium Inventory Losses during Extended Calendar Aging Protocols
Extended calendar aging consumes cyclable lithium through solid electrolyte growth, requiring differential capacity verification before warranty assignment.
Storage Degradation Model
Meaning
Predictive mathematical frameworks simulate the long-term capacity fade and impedance growth of inactive batteries over time under different environmental conditions. By employing a storage degradation model, pack designers can estimate the self-discharge and life expectancy of cells held at varying states of charge and temperatures. These simulations allow developers to optimize thermal management systems for stored or parked battery systems.
Mathematical Basis
Semi-empirical equations relate the rate of capacity loss to exponential temperature dependencies derived from the Arrhenius relationship. The model uses the square root of storage time to capture the diffusion-limited growth of the solid electrolyte interphase. This mathematical structure allows the algorithm to predict aging with minimal computational load.
Model Validation
Experimental calibration demands long-term aging tests where cells are stored across a matrix of temperatures and voltages. Sourcing teams evaluate the model predictions against this baseline to verify performance before selecting a cell supplier. If the modeled capacity fade diverges from test results at high temperatures, it indicates that secondary degradation mechanisms like electrode cracking are occurring.
System Integration
Battery management systems implement these mathematical representations to update the health state of the pack during dormant periods. This ensures that the state of charge estimation remains accurate even after the system has been inactive for several weeks.