A review of data-driven prognostics in power electronics

Kabir, Ahsanul; Bailey, C.; Lu, Hua; Stoyanov, Stoyan

doi:10.1109/isse.2012.6273136

Cited by 27 publications

(11 citation statements)

References 12 publications

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“…The identification of model parameters and states enables an exact assessment of the monitored indicator and related uncertainties (model errors, measurements errors, bandwidth of operating conditions). The data driven approach can realise predictions for remaining useful life (RUL) through statistical and probabilistic methods [8]. The approach is used to identify a suitable damage propagation model utilising collected information about the degradation path and relevant operating conditions to identify a suitable damage propagation model.…”

Section: Prognostic Approachesmentioning

confidence: 99%

Prognostics of automotive electronics with data driven approach: A review

Ahsan

Stoyanov

Bailey

2016

2016 39th International Spring Seminar on Electronics Technology (ISSE)

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Prognostics and Health Management (PHM) is a comprehensive framework that can deal with solutions for predicting and maintaining electronic system's health. The emerging concept of PHM is increasingly considered for adoption in many engineering fields such as automotive, mechanical, electrical, industrial, aerospace and railway. PHM of electronic components and systems can offer competitive advantages by improving performance, reliability, safety, maintainability and availability. In this paper, a brief description of PHM concept, current PHM approaches, key prognostics components and corresponding monitored/sensed parameters in automotive PHM applications are presented. Software tools developed for PHM applications are also reviewed. Particular focus is given on data driven approaches for prognostics of performance and reliability of automotive electronic systems. Based on the undertaken review of state-of-art in this area, key requirements and attributes of prognostic frameworks for automotive electronics are formulated and future prognostics challenges for the sector are discussed.

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Section: Prognostic Approachesmentioning

confidence: 99%

Prognostics of automotive electronics with data driven approach: A review

Ahsan

Stoyanov

Bailey

2016

2016 39th International Spring Seminar on Electronics Technology (ISSE)

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“…Data-driven prognostics methods used mainly artificial intelligence tools (neuronal networks, Bayesian networks, Markovian processes, etc.) or statistical methods to learn the degradation model, and to predict the future health state of the system [1]. The principle of these methods consists of two phases: a first phase during which a behavior model (including the degradation) is learned; and a second phase where the learned model is used to first estimate the current operating condition of the system, and then to predict its future state.…”

Section: Date Drivenmentioning

confidence: 99%

“…More Electric Vehicles proposes to use more electrical power to drive Vehicles subsystems such as Traction Motors/Inverters, Auxiliary Motors/Inverters, Energy Storage, etc. Power electronic converters have recently generated great interest in researchers and industrialists working in this area [1,2].…”

Section: Introductionmentioning

confidence: 99%

Prognostic capability evaluation of power electronic modules in transportation electrification and vehicle systems

Alghassi

Perinpanayagam

Jennions

2013

2013 15th European Conference on Power Electronics and Applications (EPE)

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Health management and reliability are fundamental part of the design and development cycle of the power electronic products. This paper presents the study and investigation about the prognostic and health management of power electronic IGBT module. To achieve this aim, a fusion approach has been introduced. In addition, for the physic based part of approach, a thermal model is used to predict temperatures of inaccessible locations within the power module. Then by employing the rainflow algorithm, the remaining life of the power electronic IGBT module has been determined.

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“…More Electric Vehicles propose to use more electrical power to drive vehicle subsystems such as Traction Motors/Inverters, Auxiliary Motors/Inverters, Energy Storage, etc. Power electronic converters have recently generated great interest among researchers and industrialists working in this area [1].…”

Section: Introductionmentioning

confidence: 99%

A simple state-based prognostic model for predicting remaining useful life of IGBT power module

Alghassi

Perinpanayagam

Jennions

2013

2013 15th European Conference on Power Electronics and Applications (EPE)

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Health management and reliability are fundamental aspects of the design and development cycle of power electronic products. This paper presents the prognostic evaluation of a power electronic IGBT module. To achieve this aim, a simple state-based prognostic (SSBP) method has been introduced and applied on the data which was extracted from an aged power electronic IGBT and its remaining useful life was determined.

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A review of data-driven prognostics in power electronics

Cited by 27 publications

References 12 publications

Prognostics of automotive electronics with data driven approach: A review

Prognostics of automotive electronics with data driven approach: A review

Prognostic capability evaluation of power electronic modules in transportation electrification and vehicle systems

A simple state-based prognostic model for predicting remaining useful life of IGBT power module

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