Novel battery wear leveling method for large‐scale reconfigurable battery packs

Summary As the market and the application areas of high capacity battery energy storage systems are rapidly increasing, there is a correspondingly high interest in the topic of minimizing battery state of health degradation in battery packs. In this article, a novel method for battery management in large‐scale battery packs is introduced, aiming to minimize battery degradation by enforcing a special wear leveling (WL) policy, adapted from the flash memory arrays. Using this method in conjunction with a hybrid mathematical‐electrochemical battery model, a reconfigurable battery management system (BMS) is proposed and evaluated. The results of the performance analysis and in‐depth comparisons with other state‐of‐the‐art solution shows that the proposed method achieves significantly longer operating times for the battery packs—for example, 415% improvement over the classical BMS in the load current variation scenario. As the computing and memory requirements are relatively low, the new battery WL method can also be implemented on embedded systems with limited resources. A critical comparison and analysis of the fields of flash memory arrays and battery packs is conducted, demonstrating that they share similar challenges in terms of reducing degradation and prolonging the system lifetime. Based on the identified analogy of concepts, one of the most efficient flash wear leveling (WL) algorithms has been adapted and applied to solve the battery selection problem in a reconfigurable battery pack. The proposed battery WL method has been used, in conjunction with a hybrid mathematical‐electrochemical battery model, to simulate a reconfigurable battery management system (BMS). We have also applied this well‐known battery degradation model to commercially available Li‐ion batteries, showing that it can accurately track the actual degradation of the batteries over their entire lifetime. A systematic process has been designed to analyze the performance of the reconfigurable BMS with the proposed method. This process consists of several experimental scenarios which enable an in‐depth comparison of our BMS with other relevant BMS solutions, based on several objective criteria. The experimental results show that the new method achieves significantly longer operating times for the battery packs, as compared to the other BMS solutions considered, especially the fixed topology BMS, which is the most widely used in current large‐scale storage systems.