A comparison of various open-circuit fault detection methods in the IGBT-based DC/AC inverter used in electric vehicle

Moosavi, Seyed Saeid; kazemi, asadollah; Akbari, Hesam

doi:10.1016/j.engfailanal.2018.09.020

Cited by 51 publications

(23 citation statements)

References 18 publications

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“…This detection mechanism is similar to [93]. Other unsupervised learning methods in anomaly detection and fault diagnosis, including k-means and SOMs, can be found in [118].…”

Section: B Anomaly Detection and Fault Diagnosismentioning

confidence: 81%

“…The diagrammatic representation implies the conditional dependence relationship between the decision variables. The underlying relationship in the model is formulated in the Bayesian framework [1] and can be inferred in Design [79], [80], Control [4], [51], [81]- [85], Maintenance [86]- [97] Radial Control [121], [122], Maintenance [7], [74], [96], [118], [123]- [126] Relevance vector machine (RVM)…”

Section: Machine Learningmentioning

confidence: 99%

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An Overview of Artificial Intelligence Applications for Power Electronics

Zhao

Blaabjerg

Wang

2021

IEEE Trans. Power Electron.

454

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This paper gives an overview of the Artificial Intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration. The applications of four categories of AI are discussed, which are expert system, fuzzy logic, metaheuristic method, and machine learning. More than 500 publications have been reviewed to identify the common understandings, practical implementation challenges, and research opportunities in the application of AI for power electronics. This paper is accompanied by an Excel file listing the relevant publications for statistical analytics.

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“…This detection mechanism is similar to [93]. Other unsupervised learning methods in anomaly detection and fault diagnosis, including k-means and SOMs, can be found in [118].…”

Section: B Anomaly Detection and Fault Diagnosismentioning

confidence: 81%

Section: Machine Learningmentioning

confidence: 99%

An Overview of Artificial Intelligence Applications for Power Electronics

Zhao

Blaabjerg

Wang

2021

IEEE Trans. Power Electron.

454

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show abstract

“…Therefore, traditional relays can be effective enough to detect and shut down the faulty component. However, the case is very different in open circuit faults, since the increase in current is not that significant, and if the sensitivity of the relays is reduced to the point they can sense these small current fluctuations, false tripping will also occur [68,69]. The intermittent behavior of RES can also cause false alarms if relays are being used for open-circuit fault detection [68].…”

mentioning

confidence: 99%

“…In this method, by applying Park vector transformation on the calculated average 3-phase current, the angle and magnitude of the currents in the complex domain are obtained, and by using pattern algorithms to analyze the trajectory of the space vector deviations, a fault can be identified. The complexity of this method is its main drawback [67,69]. In addition, this current based method and other similar ones in this category, such as two methods proposed in [72], contain another disadvantageous behavior which is a full one fundamental period delay between the occurrence and the actual detection [73].…”

mentioning

confidence: 99%

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Smart Inverters for Microgrid Applications: A Review

et al. 2019

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In a microgrid, with several distributed generators (DGs), energy storage units and loads, one of the most important considerations is the control of power converters. These converters implement interfaces between the DGs and the microgrid bus. In order to achieve higher functionality, efficiency and reliability, in addition to improving the control algorithms it is beneficial to equip the inverters with “smart” features. One interpretation of “smartness” refers to minimizing the requirement of communication and therefore switching from centralized to decentralized control. At the same time, being equipped with efficient and state of the art communication protocols also indicates “smartness” since the requirement of communication cannot be completely omitted. A “smart inverter” should offer some features such as plug and play, self-awareness, adaptability, autonomy and cooperativeness. These features are introduced and comprehensively explained in this article. One contribution discussed here is the possibility of achieving long-range wireless communication between inverters to empower various control schemes. Although current efforts aim to modify and improve power converters in a way that they can operate communication free, if a suitable and functional communication protocol is available, it will improve the accuracy, speed and robustness of them.

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Study of Budding Snubber Quality Deterioration in Solid Oxide Fuel Cell‐Fed Inverter Used in Microgrid Energy Conversion

Ghosh,

Chattopadhyay,

Banerjee

et al. 2024

Energy Tech

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One of the biggest issues today is generating energy in a way that is clean, effective, and environmentally benign. The most crucial part of an integrated grid‐connected system is the grid inverter. Budding snubber quality deterioration in the microgrid (MG) inverters is a very critical issue. Snubbers are essential components in power electronic circuits. Snubbers increase efficiency and reliability while also enhancing circuit performance, enabling greater switching frequencies. Herein, a nascent snubber resistance fault (NSF) detection technique in a three‐phase inverter (3PhI) connected with the solid oxide fuel cell used in MG applications is presented. For fault detection, an investigation is conducted using the fast Fourier transform to the inverter output current signal. The investigation is done on the effect of different percentages of snubber resistance fault in the inverter on the zero‐frequency component, fundamental current component, total harmonic distortion factor, and the subharmonic current components of the inverter current. Depending on the best‐fit parameters, an attempt is made to successfully detect the 3PhI NSF. An algorithm is proposed for NSF detection. Furthermore, this investigation's distinctive contribution and comparative analysis are presented.

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A comparison of various open-circuit fault detection methods in the IGBT-based DC/AC inverter used in electric vehicle

Cited by 51 publications

References 18 publications

An Overview of Artificial Intelligence Applications for Power Electronics

An Overview of Artificial Intelligence Applications for Power Electronics

Smart Inverters for Microgrid Applications: A Review

Study of Budding Snubber Quality Deterioration in Solid Oxide Fuel Cell‐Fed Inverter Used in Microgrid Energy Conversion

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