A Fault-Tolerant SoC Estimation Method for Series-Parallel Connected Li-Ion Battery Pack

The accurate state of charge (SoC) estimator has great significance for ensuring the safety and reliability of Li-ion battery systems. However, the accurate SoC estimation for a series-parallel connected battery pack is a remaining challenge due to the strong inconsistency characteristic caused by cell open-circuit (COC) faults. Therefore, a novel fault-tolerant multimodule SoC estimation method for the series-parallel connected battery pack is proposed. An average module model is used to describe the performance of the battery pack. A bias correction model considering SoC, series resistance, and polarization characteristic inconsistency is developed to describe in-pack modules. A noise adaptive H infinity filter-unscented H infinity filter is employed to estimate SoC for the average module. The SoCs of in-pack modules are obtained by an optimized recursive least square method. A correlation coefficient-based method is developed to detect COC fault and isolate the fault module. Finally, several experiments on a 4s-3p battery pack are taken to evaluate and verify the real-time performance, stability, and accuracy of the proposed method. The result shows that both online and offline SoC estimation error is less than 1% for healthy modules, and it is less than 2.5% for the fault module in which one-third capacity is lost randomly.

Automated summary

A novel fault-tolerant multimodule SoC estimation method is proposed for a series-parallel connected battery pack, using average module model and bias correction model to describe the battery pack's performance. An H infinity filter is employed to estimate SoC for the average module, and a recursive least square method is used to obtain the SoCs of in-pack modules. Experimental results show good real-time performance, stability, and accuracy of the proposed method.