A Model-Based Suboptimal Control to Improve Induction Motor Efficiency

Pelegrin, Jessé de; Torrico, César Rafael Claure; Carati, Emerson Giovani

doi:10.1007/s40313-015-0216-0

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…Where losses in the stator define by Pstatloss, Protloss are losses in the rotor, and Pirloss are losses in the induction motor [22]. Based in (2), the efficiency formula, which was shown in in (1) can be rewritten as (4).…”

Section: Methods 21 Performance Of Traction Motormentioning

confidence: 99%

Performance analysis of three-phase induction motor for railway propulsion system

Kamar,

Lestari,

Soewono

et al. 2023

IJPEDS

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A three-phase induction motor absorbs the most electric power among other electrical loads. Therefore, three-phase induction motors are the primary electric motors used in industrial applications thanks to their simple construction and easy operation, as well as low cost and low maintenance costs. Efficiency is a critical parameter that characterizes an induction motor as a traction motor. The traction motor is defined as the engine's effectiveness in converting electrical power at its input into mechanical energy by rotating torque on its axis. One way to analyze the efficiency is to use test data obtained from laboratory tests in case-loaded and no-load tests. Calculations using several formulas on the efficiency of an induction motor as a traction motor produce the same result, namely the efficiency of 98.6% by applying variable frequency drive (VFD). The result of laboratory tests and their analysis can be used as a reference for designing three-phase induction motors for railway traction motors, especially traction motors for high-speed trains<em>.</em>

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Section: Methods 21 Performance Of Traction Motormentioning

confidence: 99%

Performance analysis of three-phase induction motor for railway propulsion system

Kamar,

Lestari,

Soewono

et al. 2023

IJPEDS

View full text Add to dashboard Cite

show abstract

“…The simplified system model of an induction motor drive consists of a plant model and a control algorithm where the plant model is a lumped parameter model of a squirrel cage induction machine, and the control algorithm is the DRFOC. All of the models and algorithms presented in this section are derived according to [20,40,41].…”

Section: Theoretical Models and Algorithms Applied In The Papermentioning

confidence: 99%

Model-based control algorithm development of induction machines by using a well-defined model architecture and rapid control prototyping

Horvath

Kuslits²,

Lovas

2020

Electr Eng

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This paper presents a new control algorithm development approach for induction machines by using model-based design and a systematically built model architecture implemented in MATLAB/Simulink. The model architecture follows a threelayer structure, and it is developed according to the principle of functional decomposition and the needs of reusability and expandability. The first model layer consists of elementary model and algorithm components, the second contains a machine simulation model and a field-oriented control (FOC) algorithm, built upon the first layer's components, and the third realises the executable models by connecting the models and algorithms defined in the second layer. Furthermore, rapid control prototyping (RCP) is discussed as an experimental validation method, and an experimental setup with RCP is also introduced. The application of the presented methods is demonstrated by simulations as well as by experiments, and by using a control algorithm based on FOC as an example. KeywordsInduction machine · Control algorithm development · Field-oriented control (FOC) · Model-based design (MBD) · Modular architecture · Rapid control prototyping (RCP) · MATLAB/Simulink Abbreviations DRFOC Direct rotor field-oriented control DSC Direct self-control DTC Direct torque control ECU Electronic control unit FOC Field-oriented control HIL Hardware-in-the-loop MBD Model-based design NIC Network interface control PMSM Permanent magnet synchronous machine PWM Pulse width modulation RCP Rapid control prototyping SRTT Simulink Real-Time target TI Texas instruments UI User interface List of symbols i ds d-Axis stator current (A) T l Load torque (Nm) p Number of pole pairs J Rotor inertia (kg m 2 ) D Viscous friction coefficient (Nm s/rad) T 0 Static friction (Nm)

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“…The two main types of FOC schemes are indirect field-oriented control (IFOC) and direct field-oriented control (DFOC). These FOC structures are discussed by Liu et al (2015) and De Pelegrin et al (2016). A possible variant of the DFOC algorithm is the direct rotor field-oriented control (DRFOC), where the applied reference frame is fixed to the rotor flux.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Performance of Estimator-based Speed Sensorless Control of Induction Machines Using Extended and Unscented Kalman Filters

Horvath

Kuslits²

2018

Power Electronics and Drives

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This paper presents an estimator-based speed sensorless field-oriented control (FOC) method for induction machines, where the state estimator is based on a self-contained, non-linear model. This model characterises both the electrical and the mechanical behaviours of the machine and describes them with seven state variables. The state variables are estimated from the measured stator currents and from the known stator voltages by using an estimator algorithm. An important aspect is that one of the state variables is the load torque and, hence, it is also estimated by the estimator. Using this feature, the applied estimator-based speed sensorless control algorithm may be operated adequately besides varying load torque. In this work, two different variants of the control algorithm are developed based on the extended and the unscented Kalman filters (EKF, UKF) as state estimators. The dynamic performance of these variants is tested and compared using experiments and simulations. Results show that the variants have comparable performance in general, but the UKF-based control provides better performance if a stochastically varying load disturbance is present.

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A Model-Based Suboptimal Control to Improve Induction Motor Efficiency

Cited by 10 publications

References 20 publications

Performance analysis of three-phase induction motor for railway propulsion system

Performance analysis of three-phase induction motor for railway propulsion system

Model-based control algorithm development of induction machines by using a well-defined model architecture and rapid control prototyping

Dynamic Performance of Estimator-based Speed Sensorless Control of Induction Machines Using Extended and Unscented Kalman Filters

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