Tuning Window Size to Improve the Accuracy of Battery State-of-Charge Estimations Due to Battery Cycle Addition

The primary indicator of battery level in a battery management system (BMS) is the state of charge, which plays a crucial role in enhancing safety in terms of energy transfer. Accurate measurement of SoC is essential to guaranteeing battery safety, avoiding hazardous scenarios, and enhancing the performance of the battery. To improve SoC accuracy, first-order and second-order adaptive extended Kalman filtering (AEKF) are the best choices, as they have less computational cost and are more robust in uncertain circumstances. The impact on SoC estimation accuracy of increasing the cycle and its interaction with the size of the tuning window was evaluated using both models. The research results show that tuning the window size (