Novel Battery SOC/SOP/SOH Estimation Algorithms in a Unified Framework

The performance of pure electric and hybrid electric vehicles highly depends on accurate and reliable knowledge of internal battery parameters. Specifically, parameters such as the state-of-charge (SOC), state-of-health (SOH) and state-of-power (SOP) are of particular interest. This paper presents new algorithms for estimating these three key parameters using an OCV-R-RC electrical equivalent circuit model. The proposed SOC, SOH and SOP estimation algorithms are tightly coupled and work cooperatively. In order to estimate the SOC, this paper introduces a combined Coulomb counting and Regressed Voltage-based SOC estimation method that combines the traditional Coulomb counting with a regressed open-circuit voltage (OCV)-based SOC estimation technique. As a by-product of the SOC estimation algorithm, the electrical parameters are estimated and used to predict the SOH. For SOP estimation, unlike the traditional HPPC method that uses fixed battery parameters and voltage limits, this papers proposes a dynamic power capability estimation method by taking into account voltage limits, current limits and the estimated electrical parameters. The proposed algorithm is called the IV-limited SOP estimation algorithm. Finally, computer simulations are performed to validate the effectiveness of these algorithms.