SOC Estimation Error Analysis for Li Ion Batteries

Abstract

State of charge (SOC) estimation is one of the most critical functions in battery management systems. Identifying and quantifying the contribution made by each error source plays an important role in improving the accuracy of SOC estimation. This paper proposes a novel framework to analyze each error source and quantify their contributions. To demonstrate the framework, a case study was conducted to assess the error contributions from the current sensor, the Ah integration software and hardware, and the estimation of the reference Ah capacity in the Ah counting method. Three standard tests such as the capacity test, pulse test, and drive cycle test were performed on a commercial battery pack. The results indicate that the software and hardware that perform Ah integration contributed most of the inaccuracy. Also, the inaccuracy from the estimation of the reference Ah capacity contributed much more than from the current sensor.