State-of-charge estimation for lithium ion batteries via the simulation of lithium distribution in the electrode particles

State of charge (SOC) estimation is a key function of the battery management system for human-machine interactions and systems control. This study proposes a new approach for SOC estimation based on computing the amount of Lithium (Li) in the electrode particles. The distribution of the Li concentration in the electrode particles are simulated and dynamically updated by solving the solid phase diffusion equation. By integrating the Li concentration distribution function over the battery volume, the battery SOC is estimated according to the calculated amount of dischargeable Li in the particles. The capacity changes of a LiPFeO sub(4) battery during discharge are measured and calculated using this approach. The calculated capacities agree well with the measured capacities. The maximum difference is approximately 2.4%. The effects of operating temperature and current density on the Li concentration distribution during discharge are investigated. The Li concentration gradient in the particles increases as the operating temperature decreases or as the discharge rate increases. The capacity of dischargeable Li decreases approximately linearly by 52.2% as the operating temperature decreases from 25 [degrees]C to -20 [degrees]C, while it increases less than 3.5% when the operating temperature increases from 25 [degrees]C to 40 [degrees]C.