基于电热建模的DC-DC变换器退化参数识别数字孪生方法

Chuangchuang Lu, Weiyang Zhou, Ke-feng Jin
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引用次数: 0

摘要

对于大多数数字孪生方法来说,由于数字模型不是物理模型的完美复制品,难以实现高精度的参数识别。本文首次提出了一种新的基于电热模型的DT方法,该方法具有比理想模型更真实的特点,可获得准确的参数识别。通过计算所提出的数字模型的功率损耗,可以得到数字模型中自热器件(如mosfet、二极管和电容器)的温度,从而可以更新这些器件中温度相关参数的值,从而保证更准确的结果。在500W降压变换器上对该方法进行了验证,实验结果表明,MOSFET导通电阻的最大估计误差为0.6%,比传统的DT方法精度提高了数百倍。
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Electrothermal Modeling Based Digital Twin Method for Degradation Parameters Identification of DC-DC Converter
For most digital twin (DT) method, it is challenge to achieve high accuracy parameters identification due to the digital model is not a perfect replica of physical model. In this paper, a novel DT approach based on electrothermal model, which features more realistic than ideal model, is firstly proposed to obtain accurate parameters identification. By calculating the power loss of the proposed digital model, the temperature of self-heating devices in the digital model, such as MOSFETs, diodes and capacitors, can be obtained, so that the values of the temperature-dependent parameters in these devices can be updated, and hence more accurate results can be guaranteed. The proposed method is validated on a 500W buck converter and the experimental results show that the maximum estimated error of the on-state resistances of MOSFET is 0.6%, which is hundreds of times higher accuracy than conventional DT methods.
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