Aluminum electrolytic capacitor (AEC) is one of the most age-affected components in power electronic converters and its reliability has been a major concern. As the growth of service life, the equivalent series resistance (ESR) of AEC increases due to the loss of electrolyte. Therefore, online ESR estimation is critical for condition monitoring of AEC. This paper proposes an online ESR estimation method for output capacitor of boost converter. By analyzing the voltage ripple, ESR calculation model is derived. Based on the model, only output voltage and inductor current need to be measured, which can be obtained directly from double closed-loops converter. To implement this proposed method, a detailed extraction scheme based on wavelet transform denoising (WTD) is presented. Non-ideal factors (noise and voltage spikes) are analyzed and the superiority of the proposed parameter identification scheme is verified. The proposed estimation method can obtain ESR for the converter operating at different working conditions such as resistive loads and converter loads. Effect of temperature on ESR is incorporated for accurate determination of the health of capacitor. Simulation and experimental results are provided to verify the effectiveness of the method.

The aluminum electrolytic capacitor (AEC) is one of the most vulnerable parts in power electronic converters and its reliability is crucial to the whole system. With the growth of service time, the equivalent series resistance (ESR) increases and the capacitance (C) decreases due to the loss of electrolytes, which will result in extra power loss and even damage to transistors. To prevent significant damages, the AEC must be replaced at an optimal period and online health monitoring is indispensable. Through the analysis of degradation parameters (ESR and C), ESR is proved to be a better health indicator and therefore is determined as the monitoring parameter for AEC. From the capacitor perspective, ESR estimation schemes of output capacitors for a Buck converter are studied. Based on the voltage–current characteristics, two ESR calculation models are proposed, which are applicable for both continuous conduction mode (CCM) and discontinuous conduction mode (DCM). From the point of implementation view, the advantages and disadvantages of the two estimation schemes are pointed out, respectively. A Buck prototype is built and tested, and simulation and experimental results are provided to validate the proposed ESR estimation schemes.

The inherent second harmonic power pulse in single-phase grid-connected rectifiers leads to a noticeable output voltage ripple and thus results in the degradation of the system. A novel second harmonic suppression control is introduced in this paper to address this issue. The key point of the proposed control lies in the real-time prediction of the phase-shifted full-bridge (PSFB) converter’s desired duty cycle through accurate PSFB converter modeling. By accurately predicting the ideal duty cycle, the proposed control facilitates a significant enhancement in the control loop’s gain specifically at the second harmonic frequency, thereby improving the overall system performance. To validate the theoretical analysis, a series of simulations and experiments were conducted. The results demonstrate the effectiveness of the proposed second harmonic suppression control in mitigating second harmonic output voltage ripple.

The optimal design of electromagnetic interference (EMI) filters relies on accurate characterization of noise source impedance. The conventional insertion loss method involves integrating two distinct passive two-port networks between the linear impedance stabilization network (LISN) and the equipment under test (EUT). The utilization of the insertion loss to formulate a system of binary quadratic equations concerning the real and imaginary components of the impedance of the noise source enables the precise extraction of the magnitude and phase of the noise source impedance in theory. However, inherent inaccuracies in the insertion loss method during extraction can compromise impedance accuracy or even cause extraction failure. This work employs a series inductance method to overcome these limitations. Exact analytical expressions are derived for the magnitude and phase of the noise source impedance. Subsequently, the application scope of the series insertion loss method is analyzed, and the impact of insertion loss measurement error on noise source impedance extraction accuracy is quantified. Requirements for improving extraction accuracy are discussed, and method optimization strategies are proposed. The permissible range of insertion loss error ensuring a solution exists is deduced. Finally, simulation and experimental results validate the proposed approach in a buck converter.

The precise in-circuit impedance extraction in a switched-mode power supply (SMPS) is essential for the optimal design of electromagnetic interference (EMI) filters. The design of EMI filter parameters based on in-circuit impedance has already been widely investigated in the literature, but the variation characteristics of the in-circuit impedance for an SMPS is still a research gap and needs further study. In this article, based on the concept of the inductive coupling approach, a novel method for in-circuit impedance modeling is proposed. Subsequently, an accurate in-circuit impedance modeling is derived, which indicates that the in-circuit impedance for the SMPS is related to the external impedance, the modal impedance under different switching modes, and the proportion of each switching mode. Based on the derived model, the variation characteristics of the in-circuit impedance are revealed, which can provide valuable guidance for the design of EMI suppression measures. Finally, the simulation results show good agreement with the calculated results. Experimental verification further indicates that the model accurately characterizes the impedance of the switching power supply across the range of 10 kHz to 30 MHz, with amplitude deviation within 3 dB and phase deviation below 6 degrees. This work provides a quantitative foundation for designing electromagnetic interference suppression strategies, enabling more precise filter optimization over a broad frequency range.