Real-Time Hardware-in-the-Loop Simulation of Permanent-Magnet Synchronous Motor Drives Under Stator Faults

Alvarez-Gonzalez, Fernando; Griffo, Antonio; Sen, Bhaskar; Wang, Jiabin

doi:10.1109/tie.2017.2688969

Cited by 79 publications

(44 citation statements)

References 31 publications

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“…The methodology is based on models and an HIL platform, following the fault injection approach presented in Section 3.2.2. In the literature, most of the work presented about HIL platforms was focused on the development and validation of new control strategies and embedded units [27][28][29] and in some cases, authors mention the use of such platforms for the analysis of specific faults [30][31][32][33]. Nevertheless, it is difficult to find publications where an HIL platform is used systematically in the analysis of fault modes and effects of a system.…”

Section: Need For a Quantitative Fault Analysis Methodologymentioning

confidence: 99%

Model-Based Fault Analysis for Railway Traction Systems

Olmo¹,

Garramiola²,

Poza³

et al. 2018

Modern Railway Engineering

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Fault analysis in industrial equipment has been usually performed using classical techniques such as failure modes and effects analysis (FMEA) and fault tree analysis (FTA). Model-based fault analysis has been used during the last several years in order to overcome the limitations of classical methods when complex industrial equipment has to be analyzed. In railway and automotive sectors, the development and validation of new products are based on hardware-in-the-loop (HIL) platforms. In this chapter, a methodology to enhance classical FMEAs is presented. Based on HIL simulations, the objective is to improve the results of the fault analysis with quantitative information about the effects of each fault mode. In this way, the impact of the fault analysis in the design of the traction system, the development of new diagnostic functionalities and in the maintenance tasks will increase.

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Section: Need For a Quantitative Fault Analysis Methodologymentioning

confidence: 99%

Model-Based Fault Analysis for Railway Traction Systems

Olmo¹,

Garramiola²,

Poza³

et al. 2018

Modern Railway Engineering

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show abstract

“…In general, apparent and incremental inductance matrices are not equal (L s = L i ) unless the machine is linear, which can easily be verified by plugging Equation 4in Equation (13). The full CM set of equations is defined by Equations (2), (3), (10), and (12).…”

Section: CMmentioning

confidence: 99%

Fast and Accurate Model of Interior Permanent-Magnet Machine for Dynamic Characterization

2019

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A high-fidelity two-axis model of an interior permanent-magnet synchronous machine (IPM) presents a convenient way for the characterization and validation of motor dynamic performance during the design stage. In order to consider a nonlinear IPM nature, the model is parameterized with a standard dataset calculated beforehand by finite-element analysis. From two possible model implementations, the current model (CM) seems to be preferable to the flux-linkage model (FLM). A particular reason for this state of affairs is the rather complex and time-demanding parameterization of FLM in comparison with CM. For this reason, a procedure for the fast and reliable parameterization of FLM is presented. The proposed procedure is significantly faster than comparable methods, hence providing considerable improvement in terms of computational time. Additionally, the execution time of FLM was demonstrated to be up to 20% shorter in comparison to CM. Therefore, the FLM should be used in computationally intensive simulation scenarios that have a significant number of iterations, or excessive real-time time span.

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“…Alvarez-Gonzalez et al [34] give a high-fidelity implementation of the emulator in a hardware platform A research survey on DTC algorithms is presented in Wang et al [35], were performance factors subjected to PMSM are discussed. Siami et al [36] presented a predictive control for the control of matrix converters.…”

Section: Review Of Existing Resourcesmentioning

confidence: 99%

A Review on Controlling Techniques for Permanent Magnet Synchronous Motor (PMSM) and Current State of the Art in the Research Area

Thampi¹,

Kiran²

2019

CAE

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The significance of Permanent Magnet Synchronous Motors (PMSM) is that it offers high performance and efficiency for motor drives. The controlling of the high-performance motor is characterized by smooth operation of the motor over entire speed range, control ability of torque even at zero speed, fast acceleration, and deceleration. The optimization of the speedcontrol performance under different constraints and uncertainties is the biggest concern in PMSM. In that sense, various speedcontrol mechanisms were presented towards identifying the better way to control PMSM drive having high-speed features and desired torque response. However, it is necessary to have a suitable control mechanism where the better adjustment of performance can be achieved for a different operating condition. However, it is quite hard to distinguish the system characteristics and dynamic control parameters during real-time operation due to complexity in PMSM system. This paper intends to present the survey of controlling strategies in PMSM and current research trends in PMSM. Along with the research gap, a futuristic line of research is presented.

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Real-Time Hardware-in-the-Loop Simulation of Permanent-Magnet Synchronous Motor Drives Under Stator Faults

Abstract: interests range from motion control and electromechanical energy conversion to electric drives for applications in automotive, renewable energy, household appliances and aerospace sectors. He is a fellow of the IET and a senior member of IEEE.

Cited by 79 publications

References 31 publications

Model-Based Fault Analysis for Railway Traction Systems

Model-Based Fault Analysis for Railway Traction Systems

Fast and Accurate Model of Interior Permanent-Magnet Machine for Dynamic Characterization

A Review on Controlling Techniques for Permanent Magnet Synchronous Motor (PMSM) and Current State of the Art in the Research Area

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