Prognostics and health management of safety relevant electronics for autonomous driving

Alexandru Prisacaru

doi:10.4233/uuid:a586c76e-ff97-4f24-9b0f-f62417539495

Prognostics and health management of safety relevant electronics for autonomous driving

Alexandru Prisacaru

Electronic Components, Technology and Materials

Research output: Thesis › Dissertation (TU Delft)

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Abstract

This thesis describes a series of experiments, algorithms, and methodology development for implementing Prognostics and Health Management (PHM) in the field of automotive electronics. Furthermore, a new PHM framework is proposed explicitly tailored for the harsh environment electronics. In addition, the entire apparatus is built, such as the sensing capabilities of electronic packages and control units. A central PHM ECU is also developed to acquire the signal from sensors, process it, and perform calculations.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Delft University of Technology
Supervisors/Advisors	Zhang, G.Q., Promotor Gromala, P.J., Copromotor, External person
Award date	23 Jun 2021
Print ISBNs	978-94-6421-400-0
DOIs	https://doi.org/10.4233/uuid:a586c76e-ff97-4f24-9b0f-f62417539495
Publication status	Published - 23 Jun 2021

Keywords

prognostics
piezoresitive stress sensor
diagnostics
machine learning
reliability
electronic packages
virtual twin

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10.4233/uuid:a586c76e-ff97-4f24-9b0f-f62417539495

dissertation-coverFinal published version, 51 MB

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abstract = "This thesis describes a series of experiments, algorithms, and methodology development for implementing Prognostics and Health Management (PHM) in the field of automotive electronics. Furthermore, a new PHM framework is proposed explicitly tailored for the harsh environment electronics. In addition, the entire apparatus is built, such as the sensing capabilities of electronic packages and control units. A central PHM ECU is also developed to acquire the signal from sensors, process it, and perform calculations. ",

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AB - This thesis describes a series of experiments, algorithms, and methodology development for implementing Prognostics and Health Management (PHM) in the field of automotive electronics. Furthermore, a new PHM framework is proposed explicitly tailored for the harsh environment electronics. In addition, the entire apparatus is built, such as the sensing capabilities of electronic packages and control units. A central PHM ECU is also developed to acquire the signal from sensors, process it, and perform calculations.

KW - prognostics

KW - piezoresitive stress sensor

KW - diagnostics

KW - machine learning

KW - reliability

KW - electronic packages

KW - virtual twin

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M3 - Dissertation (TU Delft)

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Prognostics and health management of safety relevant electronics for autonomous driving

Abstract

Keywords

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