Insulation fault monitoring of lithium-ion battery pack: Recursive least square with adaptive forgetting factor

The large-scale and high voltage of lithium-ion battery packs have brought severe challenges to the insulation performance of the system. An effective insulation fault diagnosis scheme is of great significance in ensuring the operation of the battery pack. In this work, a battery insulation detection scheme based on an adaptive filtering algorithm is proposed. Firstly, an insulation resistance detection scheme based on signal injection is designed. Then, an insulation resistance estimation algorithm based on the adaptive forgetting factor recursive least square (AFFRLS) algorithm is proposed, which uses fuzzy logic to adaptively correct the forgetting factor. Finally, the proposed insulation detection scheme is verified by four groups of experiments under different dynamic and static conditions. The experimental results show that the AFFRLS algorithm has a significant filtering effect and can suppress the influence of system noise and battery voltage fluctuation on the estimation results. The adaptive forgetting factor ensures the dynamic performance of the algorithm.