Inverse Characterization of Open-Circuit Voltage for State-of-Charge Estimation of Batteries
Document Type
Conference Proceeding
Publication Date
1-1-2023
Publication Title
2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023
Keywords
battery management systems, battery modeling, Li-ion battery, open-circuit voltage, state of charge
Abstract
Accurate characterization of the relationship between the open-circuit voltage (OCV) and the state of charge (SOC) of Li-ion batteries is essential in the battery management system (BMS) to perform robust SOC estimation. Conventionally, the OCV-SOC relationship is represented by an analytical function, that defines the OCV as a function of SOC. However, determining SOC using this function requires slow and sensitive numerical root-finding algorithms like the bisection method. Hence, this paper formulate the concept of inverse OCV modeling to have an functional representation that defines the SOC as a function of OCV. The advantages of inverse formulation include direct SOC calculation for a given OCV, elimination of root-finding algorithms, and simplified mathematical derivations for battery model parameter estimation. The inverse curve characterization is demonstrated using data from a commercially available cylindrical Li-ion battery cell.
DOI
10.1109/ITEC55900.2023.10187061
ISBN
9798350397420
Recommended Citation
Sunil, Sooraj; Sundaresan, Sneha; Pillai, Prarthana; and Balasingam, Balakumar. (2023). Inverse Characterization of Open-Circuit Voltage for State-of-Charge Estimation of Batteries. 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023.
https://scholar.uwindsor.ca/computersciencepub/84