Online Inductance Monitoring Based on Dynamic Characteristics and ESR Effect Compensation for Buck Converter Without
Chen Chen1, Liang Wang2, Wanyang Wang3
1School of Electronic Information, Wuhan University of Science and Technology, Wuhan 430081, China.
Abstract:
Inductor parameter variations often affect the control performance of digital current mode (CM)-controlled buck converters as their high performance relies on accurate converter modeling. However, recent studies have shown that reliably monitoring inductance with current sensors and high-frequency sampling greatly increases the overall cost of this process. To address this issue, an online inductance monitoring method without a current sensor is proposed in this study. First, an inductance calculation model is derived by applying the dynamic characteristics of a buck converter with inductor volt-second and capacitor charge balance principles. The model's accuracy is guaranteed by considering inductor current switching ripple characteristics. Nevertheless, output capacitor equivalent series resistance (ESR) can degrade the accuracy of the proposed calculation model. Thus, to enhance the tolerance of the inductance calculation model to capacitor ESR, the ESR effect on inductance monitoring is investigated. With the proposed capacitor ESR estimation method, inductance monitoring achieves reliable accuracy, even for a buck converter with high capacitor ESR. The effectiveness of the proposed method is verified by simulations and experiments on a buck converter with digital sensorless current mode (SCM) control.
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