IGBT模块结温预测BP神经网络模型
发布时间:2018-07-15 11:20
【摘要】:探索了BP(Back Propagation)神经网络在IGBT模块结温预测中的应用。首先从物理机理角度分析了IGBT模块中饱和压降、集电极电流与温度的内在关系。通过IGBT结温测试试验,获取了三者的关系图,并建立了基于饱和压降的温敏参数法结温预测模型。最后建立了BP神经网络结温预测模型,并与温敏参数法进行了对比分析,证明该方法计算速度更快,误差降低。
[Abstract]:The application of BP (back Propagation) neural network in IGBT module junction temperature prediction is explored. Firstly, the relationship between saturation voltage drop, collector current and temperature in IGBT module is analyzed from the point of view of physical mechanism. Through IGBT junction temperature test, the relationship diagram of the three is obtained, and the temperature prediction model of temperature sensitive parameter method based on saturation pressure drop is established. Finally, the prediction model of junction temperature based on BP neural network is established, and compared with the temperature sensitive parameter method, it is proved that the calculation speed of this method is faster and the error is reduced.
【作者单位】: 河北工业大学电气工程学院;天津电力公司城东供电公司;
【基金】:国家自然科技基金资助项目(51377044) 河北省科技支撑计划基金资助项目(13214303D,14214503D)
【分类号】:TN322.8;TP183
[Abstract]:The application of BP (back Propagation) neural network in IGBT module junction temperature prediction is explored. Firstly, the relationship between saturation voltage drop, collector current and temperature in IGBT module is analyzed from the point of view of physical mechanism. Through IGBT junction temperature test, the relationship diagram of the three is obtained, and the temperature prediction model of temperature sensitive parameter method based on saturation pressure drop is established. Finally, the prediction model of junction temperature based on BP neural network is established, and compared with the temperature sensitive parameter method, it is proved that the calculation speed of this method is faster and the error is reduced.
【作者单位】: 河北工业大学电气工程学院;天津电力公司城东供电公司;
【基金】:国家自然科技基金资助项目(51377044) 河北省科技支撑计划基金资助项目(13214303D,14214503D)
【分类号】:TN322.8;TP183
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