%0 Journal Article
%T NARMAX method for estimating the residual capacity of Ni/MH battery pack for electric vehicle<br>电动车用Ni/MH电池组剩余容量的非线性自回归滑动平均预测
%A GUO Gui-fang
%A CAO Bing-gang
%A <br>郭桂芳
%A 曹秉刚
%J 控制理论与应用
%D 2011
%I 
%X An accurate state of charge(SOC) determines the residual diving distance of electric vehicles. For evaluating the state of charge(SOC) of the Ni/MH battery pack for electric vehicle, we propose an identification approach using NARMAX(nonlinear auto-regressive moving average with exogenous inputs) model. Employing the federal urban driving schedule(FUDS) tested data and adopting the simplified linear approximation of NARMAX method, we build the multiinput model for the SOC of the battery pack. This model is used for predicting the real-time SOC, and the results are compared with the tested data. The comparison of the predicted results with the tested data shows that the proposed method is simple and efficient. The maximum relative error of the estimation results is within 1%.
%K electric vehicle
%K Ni/MH battery pack
%K state of charge(SOC)
%K NARMAX method
%K prediction<br>电动汽车
%K Ni/MH电池组
%K 荷电状态
%K NARMAX
%K 辨识预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=833C4203053F2327F326E1B2A6F7102E&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=E158A972A605785F&sid=E543FC2C7CA75C74&eid=240CB58995465C01&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=15