Low-Cost Kalman Filter-Based Battery Tester for Accurate Capacity and State of Charge Estimation

Accurately estimating battery status significantly impacts battery use and performance. If the estimated battery capacity differs significantly from the actual value, the estimation of the state of charge (SoC) and battery use time will be inaccurate. However, accurate battery testers are unaffordable for educational use. Therefore, in this study, a low-cost battery tester is developed to estimate the battery’s capacity and SoC using the Kalman filter (KF) method. The battery tester can be operated in two modes: charging and discharging. In the charging mode, the battery is charged using the constant current and constant voltage modes. In the discharge mode, energy is released at a constant current to a resistor. Battery capacity and SoC are estimated using the KF method, allowing for improved prediction. The battery tester’s performance is investigated by comparing it with the coulomb counting method. Experimental results using the battery tester show that the KF method yielded estimation errors of 0.83% for battery capacity and $\mathbf{0. 0 2 1} \%$ for SoC under the charging mode. Additionally, the KF method yielded estimation errors of 0% for battery capacity and 0.8% for SoC under the discharging mode.