基于机器学习的LCC电路混合建模

Xi Lu, Shuhao Yang, Saijun Mao
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引用次数: 1

摘要

研究了一种LCC谐振电路的混合建模方法。混合模型包括传统数学模型和机器学习误差模型。首先,介绍了传统的数学建模方法和等效电路。其次,基于PLECS和实际硬件参数对实际LCC电路进行了仿真,得到了实际输出数据。然后,将实际数据与数学模型输出数据进行对比,得到误差数据。第三,引入机器学习算法对误差数据进行建模,通过适当的权系数,得到LCC电路的混合模型。最后,将不同工况下的混合模型输出与仿真结果进行比较,验证了该方法的有效性和先进性。
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Hybrid Modeling for LCC Circuit Based on Machine Learning
This paper investigates a hybrid modeling method for LCC resonate circuit. The hybrid model includes traditional mathematical model and machine learning error model. First, the traditional mathematical modeling method and equivalent circuit are presented. Second, a practical LCC circuit is simulated based on PLECS and real hardware parameter, and actually output data is obtained. Then, based on the comparison between real data and mathematical model output data, the error data is obtained. Third, machine learning algorithm is introduced to model this error data, and with a proper weight coefficient, a hybrid model for LCC circuit is obtained. Finally, comparison the hybrid model output under different working condition with simulation results can certify the effectiveness and advancement of this proposed method.
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