基于模糊辨识算法的蓄电池荷电状态测量方法与模块设计

针对蓄电池荷电状态在线监测中对准确度和测量速度的要求,本文提出采用模糊辨识算法对蓄电池进行系统辨识。并通过对蓄电池的荷电状态与内阻、端电压数据的分析,建立了蓄电池荷电状态的模糊规则模型,并以此进行蓄电池荷电状态的测量,得到均方误差为0.0052。测量结果表明基于模糊辨识算法的蓄电池荷电状态测量能够满足蓄电池在线监测的要求,且易于硬件实现。文章还使用DSP Builder设计了蓄电池荷电状态测量模块,其中内阻测量采用了特征分解谱估计的信号提取方法,荷电状态测量则实现了模糊辨识算法所得出的模糊规则模型的运用。

Battery State of Charge Measurement Methods and Modular Designbased on Fuzzy Identification Algorithm

According to the accuracy and speed requirements of battery State of Charge measurement for online monitoring, this paper presents a battery system identification based on Fuzzy Identification Algorithm. And through the analysis of battery State of Charge and internal resistance, voltage-side data, the fuzzy rule model of battery State of Charge is built. The measuring mean square error of the model is 0.0052. Measurement results show that method for the State of Charge of the battery measuring based on Fuzzy Identification Algorithm can battery-line monitoring to meet the requirements, and easily implemented in hardware. The article also use the DSP Builder to design the battery State of Charge measurement module, where the resistance was measured using the signal feature extraction method based on Eigendecomposition Spectrum Estimation,and State of Charge measurement is to achieve the uses of the fuzzy rule model derived from Fuzzy Identification Algorithm.