A Reference Submodule Based Capacitor Condition Monitoring Method for Modular Multilevel Converters

Wang, Zhongxu; Zhang, Yi; Wang, Huai; Blaabjerg, Frede

doi:10.1109/tpel.2019.2961712

Cited by 32 publications

(11 citation statements)

References 20 publications

(32 reference statements)

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“…Alternatively, capacitance monitoring is implemented by explicitly monitoring the charging time of the capacitor. The strategy in these approaches [26], [27], is to rst isolate each SM and compare the charging time with a reference SM. A downside of this type of approach is that it can take several hours to conduct monitoring for a large MMC.…”

Section: ) Parameter Changesmentioning

confidence: 99%

Hybrid Condition Monitoring for Power Converters: Learning-Based Methods With Statistical Guarantees

et al. 2023

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In this paper, a new learning-based method is proposed for the early detection of changes of parameters in power converters. It circumvents the pertinent shortcomings of previous model-based methods, such as their need for acquiring switching signals, dependence on the control method, or the need for isolating a part of the system during monitoring and thus interfering with the system performance or its start-up time. Additionally, a downside of the learning-based approaches, which is that their performance depends on the quality of the measurements, is addressed through constructing hybrid models that combine the benets of both lines of development. Our approaches are evaluated with several types of features based on wavelet decomposition and empirical mode decomposition. Using these, an ANN-based classier is trained for fault detection. For achieving the nal decision on the presence or absence of a fault state, we propose the use of sequential hypothesis testing. This hybrid approach yields a much higher reliability than instantaneous ANNbased classication, while allowing for a statistically sound cross-temporal information integration and providing a controllable error bound for the probability of misclassications. The proposed method was evaluated on two data-sets recorded from a buck converter and an arm of a modular multilevel converter. The results show that, for both systems, the proposed method is capable of reliably recognizing changes of the system parameters. The potential for practical applications is shown through an implementation on a low-power-consumption microcontroller. INDEX TERMS Fault diagnosis, power converters, DC/DC Converter, MMC, machine learning, signal processing, hybrid models I. INTRODUCTIONC ONDITION monitoring of power converters in energy systems is of great importance, considering the wide range of applications in which they play a critical role, and their long operational time. While there are many dierent power converter topologies, these broadly share the same principles of operation via active and passive elements. Hence, very similar condition monitoring methods can, with some modications, be applied for dierent power converters.The specic condition monitoring technique proposed in this paper is applied to two dierent power converter topologies. The rst is a buck converter, a widely employed DC-DC power converter [1]. The second system is an arm of a of modular multilevel converter (MMC). These converters have gained great interest in academia as well as industry shortly after they were initially proposed [2], due to their modular design, their

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Section: ) Parameter Changesmentioning

confidence: 99%

Hybrid Condition Monitoring for Power Converters: Learning-Based Methods With Statistical Guarantees

et al. 2023

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“…According to (14), ΔV pk decreases with the increase of junction temperature T j , and ΔV pk has a linear relationship with T j . In addition, ΔV pk increases linearly with increasing load current I L and linearly with increasing capacitor charging voltage.…”

Section: Junction Temperature Monitoring Of Igbt Devicesmentioning

confidence: 99%

A novel integrated monitoring method for MPPF capacitor and IGBT junction temperature of half‐bridge modules

Zhang

et al. 2023

IET Power Electronics

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Capacitance and Insulated gate bipolar transistor (IGBT) junction temperature are two critical healthy parameters for modular multilevel converters (MMC) sub‐modules (SMs) condition monitoring. This paper proposes an integrated monitoring method for capacitance degradation and IGBT junction temperature variation. By measuring multiple characteristics of the same port voltage, the capacitance and the junction temperature can be obtained simultaneously, which greatly simplifies the measurement unit required for condition evaluation and realizes the submodule‐level condition monitoring at a lower cost. The capacitance is characterized by voltage changes during capacitor discharging and the junction temperature is monitored by capacitor voltage overshoot (peak value) during IGBT turn‐off. Theoretical analysis and experimental results verify the effectiveness of the proposed method and articulated the influence of load current, SM capacitor pre‐discharge voltage, and junction temperature. Moreover, an online data‐acquisition circuit for time‐specific capacitor voltage characterization is devised.

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“…The cell capacitors are either Metallized Polypropylene Film Capacitors (MPPF-Caps) or Aluminum Electrolytic Capacitors (Al-Caps) and nowadays the MPPF-Caps are more adopted in industrial MMCC cells due to higher lifespan and self-healing capability [109], [110] while Al-Caps are especially used in prototypes and demonstrators [111]. However, according to [112], [113] Al-Caps are still advantageous in some MMCC applications where design objectives are high energy density and low costs.…”

Section: Failure Mechanisms In Mmccsmentioning

confidence: 99%

Faults in Modular Multilevel Cascade Converters—Part I: Reliability, Failure Mechanisms, and Fault Impact Analysis

Rojas

Jerez

Hackl

et al. 2022

IEEE Open J. Ind. Electron. Soc.

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Modular Multilevel Cascade Converters (MMCCs) are considered a promising power electronics topology in industry. Their scalability allows to reach (ultra/very) high voltage levels with low harmonic content and high efficiency and makes MMCCs an ideal solution for high-power applications; such as electrical drives, solid-state transformers and high-voltage direct-current (HVDC) transmission systems. However, the high levels of thermal, electrical and mechanical stress on the power electronics devices and the large number of components (e.g. capacitors or semiconductors) make MMCCs prone to faults reducing its reliability. In this first part of the paper, a comprehensive overview of reliability on MMCCs, failure mechanisms and fault impact analysis in MMCCs, including failure rates and fault modes is presented. Also a set of tables which collect all information to easily detect and identify faults in MMCCs is presented.

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A Reference Submodule Based Capacitor Condition Monitoring Method for Modular Multilevel Converters

Cited by 32 publications

References 20 publications

Hybrid Condition Monitoring for Power Converters: Learning-Based Methods With Statistical Guarantees

Hybrid Condition Monitoring for Power Converters: Learning-Based Methods With Statistical Guarantees

A novel integrated monitoring method for MPPF capacitor and IGBT junction temperature of half‐bridge modules

Faults in Modular Multilevel Cascade Converters—Part I: Reliability, Failure Mechanisms, and Fault Impact Analysis

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