As lithium ion cells age, they experience power and energy fade associated with impedance rise and capacity loss, respectively. Identification of key aging parameters in lithium ion battery models can validate degradation hypotheses and provide a foundation for State of Health (SOH) estimation. This paper develops and simplifies an electrochemical model that depends on two key aging parameters, cell resistance and the solid phase diffusion time of Li+ species in the positive electrode. Off-line linear least squares and on-line adaptive gradient update processing of voltage and current data from fresh and aged lithium ion cells produce estimates of these aging parameters. These estimated parameters vary monotonically with age, consistent with accepted degradation mechanisms such as solid electrolyte interface (SEI) layer growth and contact loss.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
- Physical and Theoretical Chemistry
- Electrical and Electronic Engineering