A Mission Profile-Based Reliability Modeling Framework for Fault-Tolerant Electric Propulsion

Thurlbeck, Alastair P.; Cao, Yue

doi:10.1109/tia.2022.3144620

Cited by 16 publications

(5 citation statements)

References 22 publications

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“…The measured rotor position θ m (𝑡), true rotor position θ r (𝑡), and PSOE ∆𝜃(𝑡) are related as shown in (1). Since the speed is obtained by differentiating speed, the measured speed ω m (𝑡), actual rotor speed ω r (𝑡), and the influence of PSOE on speed measurement may be derived as (2). The key notable difference between an SPSOE a DPOSOE is that, in the case of an SPSOE, the term ∆𝜃 ̇(𝑡) = 0.…”

Section: Figure 1 Position Sensor Offset Error From a Motor Cross-sec...mentioning

confidence: 99%

Modeling and Detection of Dynamic Position Sensor Offset Error in PMSM Drives

Kuruppu¹,

Abeyratne²,

Hettiarachchi³

2023

Preprint

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<p> Rotor position information obtained through a position sensor is crucial for proper field-oriented control (FOC) of permanent magnet synchronous machine based high dynamic energy conversion applications. In applications such as transportation and industrial, PMSM energy conversion systems are subjected to harsh environmental conditions such as vibration, shock, and thermal shock causing mechanical interfaces holding positions sensors to fail, introducing error to the position measurement. A dynamic position sensor offset error (DPSOE), being such a failure mode has the potential to degrade system torque output or more adversely, reverse machine torque output that may cause catastrophic outcomes. This paper evaluates different DPSOE scenarios, presents an approach to model the failure mode for analysis and proposes two novel and robust DPSOE detection methods for PMSM drive systems. The proposed detection methods are analytically proven and supported by simulation and experimental results under multiple operating conditions proving robustness. </p>

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Section: Figure 1 Position Sensor Offset Error From a Motor Cross-sec...mentioning

confidence: 99%

Modeling and Detection of Dynamic Position Sensor Offset Error in PMSM Drives

Kuruppu¹,

Abeyratne²,

Hettiarachchi³

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The measured rotor position 𝜃 𝑚 (𝑡), true rotor position 𝜃 𝑟 (𝑡), and PSOE ∆𝜃(𝑡) are related as shown in (1). Since the speed is obtained by differentiating position, the measured speed 𝜔 𝑚 (𝑡), actual rotor speed 𝜔 𝑟 (𝑡), and the influence of PSOE on speed measurement may be derived as (2). In SPSOE ∆𝜃(𝑡) is constant and ∆𝜃 ̇(𝑡) = 0, while during DPSOE ∆𝜃(𝑡) is time-varying and ∆𝜃 ̇(𝑡) is non-zero.…”

Section: Problem Statement and Key Challengesmentioning

confidence: 99%

Modeling and Detection of Dynamic Position Sensor Offset Error in PMSM Drives

2023

View full text Add to dashboard Cite

Rotor position information obtained through a position sensor is crucial for proper fieldoriented control (FOC) of permanent magnet synchronous machine-based high dynamic energy conversion applications. In applications such as transportation and industrial, PMSM energy conversion systems are subjected to harsh environmental conditions such as vibration, shock, and thermal shock causing mechanical interfaces holding position sensors to fail, introducing errors to the position measurement. A dynamic position sensor offset error (DPSOE), being such a failure mode has the potential to degrade system torque output or more adversely, reverse machine torque output that may cause catastrophic outcomes. This paper evaluates different DPSOE scenarios, presents an approach to model the failure mode for analysis and proposes two novel, and robust DPSOE detection methods for PMSM drive systems. The proposed detection methods are analytically proven and supported by simulation and experimental results under multiple operating conditions proving robustness.

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“…Handbook-driven approaches benefit from the straightforward failure rate calculation, however, all the aforementioned handbook approaches carry some shortcomings despite having updates on their handbooks. [82].…”

Section: Iii) Lifetime Modelmentioning

confidence: 99%

“…For instance, a simple fault-tolerant system may consist of three states, including the healthy state, the failure state, and the post-fault state. The healthy and postfault states are both considered as operational states [130]. The MC approach can be simulated as a state space system, in which the state variables are the probabilities that a system will reach each state over time [131].…”

Section: System Level Lifetime Prediction Metodsmentioning

confidence: 99%

An Overview of Lifetime Management of Power Electronic Converters

et al. 2022

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An expected lifetime of converters is of great importance for optimal decision-making in the planning of modern Power Electronic (PE) systems. Hence, the lifetime management of power electronic systems has attracted a lot of attention in academia and industry. This paper is a guideline for managing the lifetime of power converters. Analyzing the different kinds of failures, failure modes and their corresponding mechanisms are investigated in the first section along with the failure data needed as input parameters of the assessment. In the second section, lifetime prediction in two aspects of component-level and system level is discussed and all the possible techniques to achieve them are investigated and compared. All the steps required to predict the lifetime in the component-level including electrothermal modeling, cycle counting, lifetime model, damage accumulation, parameter estimation, and lifetime distribution are described and then system level methods consisting of reliability block diagrams, fault-tree analysis, and Markov chains are examined and compared. The last section contains the roadmap of the lifetime extension including the reliable design and condition monitoring. INDEX TERMSReliability, Lifetime management, Lifetime analysis, Lifetime prediction, Lifetime extension, Empirical model, Physics of failure, failure mechanism FIGURE 1. Guideline of the reliability of power electronic systems.

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A Mission Profile-Based Reliability Modeling Framework for Fault-Tolerant Electric Propulsion

Cited by 16 publications

References 22 publications

Modeling and Detection of Dynamic Position Sensor Offset Error in PMSM Drives

Modeling and Detection of Dynamic Position Sensor Offset Error in PMSM Drives

Modeling and Detection of Dynamic Position Sensor Offset Error in PMSM Drives

An Overview of Lifetime Management of Power Electronic Converters

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