Optimized Method for Reliability and Redundancy Analysis of MMC Based on Component Operating Conditions

Lv, Gangming; Wang, Yue; Yin, Taiyuan; Gao, Guoqing; Xuan, Jiazhuo; Ding, Chao

doi:10.1109/pedg.2019.8807636

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Techniques for exploring the entire system's reliability based on each module's failure rate include RBD (Reliability Block Diagram), FTA (Fault tree analysis), and Markov model [22]- [33]. References [24] and [25] used RBD to analyze the MMC converter's reliability, availability, and power loss according to the redundancy. However, it is difficult for RBD to consider the various failure modes and complex circuit structures in modular converters.…”

Section: B Literature Review MMC (Modular Multilevel Converter) Mchb ...mentioning

confidence: 99%

Markov Model-Based Reliability Analysis Considering the Redundancy Effect of Modular Converters

Jo,

Kim,

et al. 2024

IEEE Access

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This paper uses a DAB converter and a non-isolated DC-DC converter as modules. It analyzes the differences in circuit characteristics and reliability due to the redundancy effect by combining them in series and parallel. In particular, reliability is analyzed considering the redundancy effect when the rated power of the DAB converter and non-isolated DC-DC converter are designed to be 50% and 100% of the module-rated power, respectively. The conventional FTA method can analyze failures that reflect the operational risks of modules but cannot analyze partial failures when failures occur in some modules. To solve this problem, this paper predicts the failure rate and MTBF of the converter by modeling state changes and partial failures between modules of a modular converter based on the Markov model. The impact of the redundancy effect on reliability is presented as a quantitative value by calculating the failure rate of major components from the MIL-STD-217F fault library and substituting it into the Markov model.INDEX TERMS bidirectional dc-dc converters, dual active bridge (DAB), fault tree analysis (FTA), Markov model, mean time between failures (MTBF), redundancy, reliability

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Section: B Literature Review MMC (Modular Multilevel Converter) Mchb ...mentioning

confidence: 99%

Markov Model-Based Reliability Analysis Considering the Redundancy Effect of Modular Converters

Jo,

Kim,

et al. 2024

IEEE Access

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“…Unequal aging among the components is caused by internal or external faults, these faults have impact on all cells of one cluster which leads to a statistical dependency of the reliability functions of the cells. This is studied in more detail in [92]. Notice that cluster redundancy has not been reported in the literature, and is not included in (10).…”

Section: ) Power Mmccsmentioning

confidence: 99%

“…The propagation of aging effects can be minimized by predictive maintenance and/or condition monitoring of the main components, adjusting the maintenance intervals in accordance to the varying failure rates of the individual components [74]. By adding redundant components or cells in combination with fault-tolerant control strategies, the reliability of the MMCC can be substantially increased [74], [92]. In [95], an interesting estimation of lifetime based on operating conditions of a converter, neglecting electromechanical information, has been proposed.…”

Section: ) Power 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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Air-Cooling System Optimization for IGBT Modules in MMC Using Embedded O-Shaped Heat Pipes

Wang

Yang

et al. 2021

IEEE J. Emerg. Sel. Topics Power Electron.

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Optimized Method for Reliability and Redundancy Analysis of MMC Based on Component Operating Conditions

Cited by 3 publications

References 8 publications

Markov Model-Based Reliability Analysis Considering the Redundancy Effect of Modular Converters

Markov Model-Based Reliability Analysis Considering the Redundancy Effect of Modular Converters

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

Air-Cooling System Optimization for IGBT Modules in MMC Using Embedded O-Shaped Heat Pipes

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