Abstract:

As Li-ion batteries are used in increasingly diverse applications, their performance and reliability become more critical. Reliability testing of Li-ion batteries involves battery capacity fade monitoring over repeated charging/discharging cycles. Cycling at a nominal charge/discharge current requires an extensive amount of time and resources, and hence a battery qualification process based on battery cycle testing may cause delays in time to market. Discharge C-rate variable can be used for accelerating Li-ion battery cycle testing. This paper develops an accelerated capacity fade model for Li-ion batteries under multiple C-rate loading conditions, to translate the performance and degradation of a battery population at accelerated C-rate conditions to normal C-rate conditions. A nonlinear mixed-effects regression modeling technique is used to take into account the variability of repeated capacity measurements on individual batteries in a population. The model is validated using the experimental data from two battery populations that have been fielded.