CAJ | 학술논문

为了准确估算锂离子电池的荷电状态（SOC）,在分析影响锂离子电池剩余容量时变特性的基础上,综合国内外几种常用的预测锂离子电池方法,将改进Elman网络应用到锂离子电池的容量预测和模型建立中。实验结果表明：该网络不仅局部泛化能力好,而且有较好的动态性能和逼近能力,能够满足电池容量预测的误差要求。
위료준학고산리리자전지적하전상태（SOC）,재분석영향리리자전지잉여용량시변특성적기출상,종합국내외궤충상용적예측리리자전지방법,장개진Elman망락응용도리리자전지적용량예측화모형건립중。실험결과표명：해망락불부국부범화능력호,이차유교호적동태성능화핍근능력,능구만족전지용량예측적오차요구。
In order to accurately estimate the lithium-ion battery state of charge（SOC）,the analysis on the remaining capacity lithium-ionbatteries based on the time-varying characteristics,comprehensive international prediction of several common lithium ion battery methods,modified Elman network was used to predict the lithium ion battery capacity and model.The results show that the network not only local generalization ability at the same time have better dynamic performance and approximation capability of the battery capacity to meet the requirements of the prediction error.