A Low-Cost Digital Capacitor Current Estimation Algorithm Based on Parameter Identification for Buck Converter Application

In switching converters, capacitor current is a critical feedback parameter due to its ability to rapidly reflect dynamic load variations, making it widely applicable in various control strategies such as current-mode feedback regulation. With the rapid advancement of digital power technology, current detection must be implemented in the digital domain, typically requiring high-bandwidth current sensors and high-speed analog-to-digital converters (ADCs). To address the high-cost challenge associated with capacitor current sampling in digital buck converters, this paper proposes a low-cost digital capacitor current estimation technique based on output voltage information tracking. By analyzing the dynamic characteristics of the output voltage, the method achieves precise estimation of the capacitor current. This paper thoroughly investigates the error issues arising from time constant mismatch in the proposed capacitor current estimation method and introduces an online time constant identification approach based on the output capacitor ( $\mathbf {C}_{\mathbf {o}}$ ) and its equivalent series resistance (ESR). By dynamically adjusting the estimator parameters, the estimation accuracy is significantly improved. The proposed algorithm is experimentally validated on a buck converter prototype. The results demonstrate that the error in the time constant after identification and correction is controlled within 3%, and the capacitor current estimation accuracy is maintained within 6%.