Reliability Evaluation of Battery Energy Storage System Considering the SOC/SOH Estimation Errors Caused by Sensor Drifts

Measurement errors in voltage and current sensors may result in overcharge and overdischarge of the battery, thereby reducing battery reliability. However, this relationship has not been well characterized in existing studies. To address this issue, a reliability evaluation method of battery energy storage system (BESS) considering sensor deviations is proposed. First, the error distribution of the battery state estimation is derived within the extended Kalman filter framework. In addition, the battery aging state, thermal stability, and internal resistance are investigated to characterize the evolution of battery reliability based on the degradation mechanism. On this basis, the battery reliability is modeled by integrating these three aspects. Finally, the reliability model of BESS is developed utilizing the universal generating function technique. Case studies demonstrate a correlation between sensor error and battery reliability. A 1% error of the sensor can accelerate the battery reliability decrease by 6 times. In some cases, an internal short circuit may lead to a complete loss of battery reliability. By reducing the sensor error from 1% to 0.5%, the reliability of BESS can be improved by up to 24.6% after 1000 cycles. These conclusions are significant for predicting the life cycle performance and guiding the design of BESS monitoring systems.