Jinxin Han

Bio: Jinxin Han is an academic researcher from Chongqing University. The author has contributed to research in topics: Time–frequency analysis & Equivalent series resistance. The author has an hindex of 1, co-authored 1 publications receiving 10 citations.

Online Estimation of ESR for DC-Link Capacitor of Boost PFC Converter Using Wavelet Transform Based Time–Frequency Analysis Method

Abstract: Aluminum electrolytic capacitor (AEC) is one of the most age-affected components in ac–dc conversion, and its equivalent series resistance ( ESR ) is an important index for reflecting the healthy condition of AEC. In AEC-used boost power factor correction (PFC) converters, ESR of AEC causes a small jump in the switching ripple of output voltage at switching moments, especially at turn- off moments. This small jump is hardly observed at line-frequency scale, either using time-domain analysis or frequency-domain analysis. However using time–frequency analysis this jump is very prominent due to its singularity. In this article, an online ESR estimation method of AEC is proposed by using the wavelet transform (WT) based time–frequency analysis. The relationship between ESR and the jump amount of output voltage at turn- off moments is analyzed first, and then the ESR calculation model is derived using WT with the wavelet basis of the first derivative of Gaussian function. An appropriate sampling interval for the output voltage and the inductor current is determined. Besides, the online ESR estimation scheme is implemented including the hardware and software designs. Furthermore, a prototype of boost PFC converter with 220 V ac input and 360 V dc output is built, where an average current mode control chip UC3854 is used. Four factors are discussed for estimation accuracy in the experiment, and the estimated results are consistent with the results measured by LCR meter with a relative error less than 10%.

An Overview of Condition Monitoring Techniques for Capacitors in DC-Link Applications

Abstract: Capacitors are widely used in dc links of power electronic converters to balance power, suppress voltage ripple, and store short-term energy. Condition monitoring (CM) of dc-link capacitors has great significance in enhancing the reliability of power converter systems. Over the past few years, many efforts have been made to realize CM of dc-link capacitors. This article gives an overview and a comprehensive comparative evaluation of them with emphasis on the application objectives, implementation methods, and monitoring accuracy when being used. First, the design procedure for the CM of capacitors is introduced. Second, the main capacitor parameters estimation principles are summarized. According to these principles, various possible CM methods are derived in a step-by-step manner. On this basis, a comprehensive review and comparison of CM schemes for different types of dc-link applications are provided. Finally, application recommendations and future research trends are presented.

ESR Estimation for Aluminum Electrolytic Capacitor of Power Electronic Converter Based on Compressed Sensing and Wavelet Transform

Abstract: The aluminum electrolytic capacitor (AEC) is one of the most important parts of a power electronic converter. Throughout its lifespan, the equivalent series resistance (ESR) of the AEC will increase, which will affect the performance of the power electronic converter. To guarantee the reliability of a converter, it is necessary to monitor the health state of the AEC, for which one common technique is to estimate the ESR of the AEC. Equipment with a high sampling rate is usually required because converter usually works at a high frequency. This requirement will increase the cost of ESR monitoring. To address this issue, this article proposes a novel method of estimating the ESR for an AEC. The proposed method uses an innovative compressed sensing approach to acquire the ripple voltage and current. Instead of complete reconstruction of the ripple voltage and current, only the high-frequency features in the wavelet subspace are reconstructed and used to calculate the ESR. The proposed method reduces the cost of data sampling, transmission, and storage. This method is not limited by the converter circuit structure and can be applied in various environments. Simulations and experiments were carried out to verify the effectiveness of the proposed method.

An ESR Quasi-Online Identification Method for the Fractional-Order Capacitor of Forward Converters Based on Variational Mode Decomposition

Abstract: An quasi-online equivalent series resistance (ESR) identification method that considers the impact of capacitance based on variational mode decomposition (VMD) of forward converters is proposed in this letter. First, the capacitance impact is included in ESR derivation. Subsequently, VMD is adopted to process characteristic signals for harmonic analysis, filter out noise, and simplify circuits design. The experiments and simulation are employed to verify the proposed method. In addition, in order to overcome the disadvantages of using ideal capacitors in the traditional simulation, fractional-order capacitors are constructed to describe the nonideal characteristics of the capacitor. Meanwhile, the identification result is compared with the LCR meter measurement. Thus, the superiority of the proposed ESR quasi-online identification method and the construction method of fractional-order capacitors are confirmed through comparative analysis.

ESR Estimation for Aluminum Electrolytic Capacitor of Power Electronic Converter Based on Compressed Sensing and Wavelet Transform

Abstract: The aluminum electrolytic capacitor (AEC) is one of the most important parts of a power electronic converter. Throughout its lifespan, the equivalent series resistance (ESR) of the AEC will increase, which will affect the performance of the power electronic converter. To guarantee the reliability of a converter, it is necessary to monitor the health state of the AEC, for which one common technique is to estimate the ESR of the AEC. Equipment with a high sampling rate is usually required because converter usually works at a high frequency. This requirement will increase the cost of ESR monitoring. To address this issue, this article proposes a novel method of estimating the ESR for an AEC. The proposed method uses an innovative compressed sensing approach to acquire the ripple voltage and current. Instead of complete reconstruction of the ripple voltage and current, only the high-frequency features in the wavelet subspace are reconstructed and used to calculate the ESR. The proposed method reduces the cost of data sampling, transmission, and storage. This method is not limited by the converter circuit structure and can be applied in various environments. Simulations and experiments were carried out to verify the effectiveness of the proposed method.

A Novel Hybrid Approach for Partial Discharge Signal Detection Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Approximate Entropy.

Abstract: To eliminate the influence of white noise in partial discharge (PD) detection, we propose a novel method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and approximate entropy (ApEn). By introducing adaptive noise into the decomposition process, CEEMDAN can effectively separate the original signal into different intrinsic mode functions (IMFs) with distinctive frequency scales. Afterward, the approximate entropy value of each IMF is calculated to eliminate noisy IMFs. Then, correlation coefficient analysis is employed to select useful IMFs that represent dominant PD features. Finally, real IMFs are extracted for PD signal reconstruction. On the basis of EEMD, CEEMDAN can further improve reconstruction accuracy and reduce iteration numbers to solve mode mixing problems. The results on both simulated and on-site PD signals show that the proposed method can be effectively employed for noise suppression and successfully extract PD pulses. The fusion algorithm combines the CEEMDAN algorithm and the ApEn algorithm with their respective advantages and has a better de-noising effect than EMD and EEMD.