State Estimation of Buck Converter by Using Kalman Filter

Kadir Eker, Y. Cetinceviz, E. Şehirli, Faruk Erken
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Abstract

This study presents buck converter modeling and estimation of state variables in noisy and noiseless environments using Kalman Filter. Firstly, the linearized state space model of the buck converter is obtained and the simulation model is created. The output voltage of the buck converter, the state variables of inductor current and capacitor voltage are estimated using the Kalman state observer. The simulations are carried out in the MATLAB/Simulink software environment. Eventually the estimation of the state variables with the Kalman filter has been verified by comparing it with the model of the converter with maximum 7.10%%, minimum 0.0% error regarding to different scenarios.
基于卡尔曼滤波的Buck变换器状态估计
研究了利用卡尔曼滤波对降压变换器在有噪声和无噪声环境下的状态变量进行建模和估计。首先,建立了buck变换器的线性化状态空间模型,并建立了仿真模型。利用卡尔曼状态观测器估计了buck变换器的输出电压、电感电流和电容电压的状态变量。仿真在MATLAB/Simulink软件环境下进行。最后,通过与变换器模型进行比较,验证了卡尔曼滤波对状态变量的估计,在不同的情况下,最大误差为7.10%,最小误差为0.0%。
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