【摘要】 阀控铅酸蓄电池的老化失效机理复杂 ,失效模式受诸多因素影响 ,单纯通过浮充状态数据分析难于准确估计电池的劣化程度 .在对蓄电池放电特性分析的基础上 ,研究了采用模糊神经网络方法建立蓄电池的劣化程度预测模型 ,根据部分放电的测量数据进行劣化程度的预测 ,实测数据证明了模型的有效性更多还原

【Abstract】 The mechanism of VRLA battery deterioration is very complex, and the deterioration models are affected by many factors. It is difficult to evaluate the health of VRLA battery only through analysis of data in a floating state. From the study on battery characteristics during discharging, a fuzzy neural network is adapted to build the model for SOH prediction. The SOH has been calculated using part of discharge testing data. The satisfactory accuracy has been demonstrated by test data.更多还原