基于双变结构滤波的动力锂电池SOC估算方法

Dual variable-structure filter-based SOC estimation method for lithium-ion power battery

电池荷电状态(SOC)是动力电池的重要参数,提出了双变结构滤波算法,实现动力锂电池SOC的高精度估算。采用一个变结构滤波对电池Thevenin模型进行参数辨识与高阶多项式对OCV-SOC非线性特性进行建模;虽然变结构滤波估算SOC时能有效保证收敛,为了进一步提高变结构滤波SOC估算精度,对另一个变结构滤波参数进行模糊化处理,提高变结构滤波自适应性,提出了模糊-变结构滤波算法,实现SOC状态的精确估算。基于Arbin电池测试平台,仿真结果表明所提出的双变结构滤波能有效提高SOC估算精度,其SOC估算的最大绝对误差1.50%,平均绝对误差0.09%。

State of charge(SOC)is one of the most important parameters for electric vehicle power battery.The dual variable-structure filter algorithm was presented to estimate SOC for lithium-ion power battery.One variable-structure filter was used for parameter identification of Thevenin battery model and capturing the nonlinear characteristics between OCV and SOC model by high-order polynomial.Although the variable structure filter could effectively guarantee the convergence of SOC estimation,the parameters should be fuzzed to improve the accuracy of SOC estimation and its adaptive ability.Therefore,the fuzzy variable-structure filter algorithm was proposed to accurately estimate the battery SOC.The test performed in the Arbin test platform show that the dual variable-structure filter can effectively improve the SOC estimation accuracy with the maximum error of 1.50%and the average absolute error of 0.09%.