State of Health Estimation for Second Life Lithium-Ion Batteries: Indicators and Considerations

This study aims to provide valuable insights into state of health estimation of second-life lithium-ion batteries in stationary energy storage systems by conducting an analytical examination of key technical indicators and considerations. By considering these factors, we can enhance our understanding of the estimation process and make informed decisions regarding the conditions of utilizing these batteries in their second life. The approach, presented in this paper, focuses on two main aspects. Firstly, it takes into account the unique characteristics of these batteries, which exhibit different responses to operational factors compared to their initial life cycle in electrical vehicles. Secondly, it considers monitoring conditions of stationary storage systems to develop an enhanced monitoring system which leads to an efficient performance of batteries in their second-life. By addressing these aspects, we aim to optimize the utilization of second-life batteries in stationary storage systems and ensure their reliable operation. This methodology, which utilizes Kalman filter and empirically derived data, has demonstrated significantly improved reliability and accuracy compared to other methodologies. By leveraging Kalman filter, we were able to enhance the estimation process and achieve a more precise estimation of state of health in stationary energy storage systems.