A novel rotor resistance identification method for an indirect rotor flux-orientated controlled induction machine system

Purpose Traction applications, e.g. the IMs are mainly operated by field-oriented control (FOC). This control technique requires an accurate knowledge of the machine’s parameters, such as the main inductance, the leakage inductances and the stator and rotor resistance. The accuracy of the parameters influences the precision of the calculated rotor flux and the rotor flux angle and the decoupling of the machine’s equations into the direct and quadrature coordinate system (dq-components). Furthermore, the parameters are used to configure the controllers of the FOC system and therefore influence the dynamic behavior and stability of the control. Design/methodology/approach In this paper, three different methods to calculate the machine’s parameters, in an automated and rapid procedure with minimal measuring expenditure, are analyzed and compared. Moreover, a method to configure a control that reduces the overall Ohmic losses of the machine in every torque speed operation point is presented. The machine control is configured only with the identified machine parameter. Findings Simulations and test bench measurements show that the evolutionary strategy is able to identify the electrical parameters of the machine in less time and with low error. Moreover, the controller is able to control the torque of the machine with a deviation of less than 2 per cent. Originality/value The most significant contribution of the research is the potential to identify the machine parameter of an induction motor and to configure an accurate control with these parameters.

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THE IDENTIFICATION OF INDUCTION MOTOR INTERNAL QUANTITIES

Acta Electrotechnica et Informatica ◽

10.15546/aeei-2021-0016 ◽

2021 ◽

Vol 21 (3) ◽

pp. 24-29

Author(s):

Marek FEDOR ◽

◽

Daniela PERDUKOVA ◽

Keyword(s):

Transfer Function ◽

Angular Speed ◽

Electromagnetic Torque ◽

Flux Vector ◽

Identification Method ◽

Rotor Resistance ◽

Linear Transfer Function ◽

Rotor Flux ◽

Voltage Frequency ◽

Master Control

In the presented work a new identification method of difficult measured internal quantities of IM, such as components of magnetic flux vector and electromagnetic torque, is proposed. Commonly measurable quantities of IM like stator currents, stator voltage frequency and mechanical angular speed are used for identification to determine a feedback effect of the rotor flux vector on vector of stator currents of IM. Based on this feedback it is also possible to identify actual value of the rotor resistance, which can alter during IM operation. This has a significant impact on precision of identified quantities as well as on master control of IM. Stability of the identification structure is guaranteed by position of roots of characteristic equation of its linear transfer function. Results obtained from simulation measurements confirm quality, effectivity, feasibility, and robustness of the proposed identification method.

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Diagnosis of the Induction Machine Using Advanced Signal Processing Methods

Algerian Journal of Signals and Systems ◽

10.51485/ajss.v3i3.70 ◽

2018 ◽

Vol 3 (3) ◽

pp. 143-150

Author(s):

Abdelghani CHAHMI

Keyword(s):

Induction Machine ◽

Detection Methods ◽

Diagnostic Tools ◽

Simulation Tools ◽

Electric Drives ◽

Efficient Simulation ◽

Squirrel Cage ◽

Rotor Resistance ◽

Three Phase ◽

Signal Processing Methods

This work is a part of the thematic of monitoring and fault diagnosis of the squirrel cage three-phase induction machine. The choice of this type of machine is justified by the growing success it has exhibited, mainly, in the electric drives with variable speed. Signal based detection methods are presented is validated in simulation. The proposed diagnosis approach requires only little experimental data, and more importantly it provides efficient simulation tools that allow characterizing faulty behavior.In this study, the proposed approach considers the value of rotor resistance as fixed for condition monitoring. This value in the diagnostic tools which one uses is not fixed contrary to the classical approaches of control of machine.

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Cascade Control of the Ground Station Module of an Airborne Wind Energy System

Energies ◽

10.3390/en14248337 ◽

2021 ◽

Vol 14 (24) ◽

pp. 8337

Author(s):

Ali Arshad Uppal ◽

Manuel C. R. M. Fernandes ◽

Sérgio Vinha ◽

Fernando A. C. C. Fontes

Keyword(s):

Wind Energy ◽

Sliding Mode ◽

External Disturbance ◽

Induction Machine ◽

Energy System ◽

Control Loop ◽

Successful Operation ◽

Ground Station ◽

Wind Energy System ◽

Rotor Flux

An airborne wind energy system (AWES) can harvest stronger wind streams at higher altitudes which are not accessible to conventional wind turbines. The operation of AWES requires a controller for the tethered aircraft/kite module (KM), as well as a controller for the ground station module (GSM). The literature regarding the control of AWES mostly focuses on the trajectory tracking of the KM. However, an advanced control of the GSM is also key to the successful operation of an AWES. In this paper we propose a cascaded control strategy for the GSM of an AWES during the traction or power generation phase. The GSM comprises a winch and a three-phase induction machine (IM), which acts as a generator. In the outer control-loop, an integral sliding mode control (SMC) algorithm is designed to keep the winch velocity at the prescribed level. A detailed stability analysis is also presented for the existence of the SMC for the perturbed winch system. The rotor flux-based field oriented control (RFOC) of the IM constitutes the inner control-loop. Due to the sophisticated RFOC, the decoupled and instantaneous control of torque and rotor flux is made possible using decentralized proportional integral (PI) controllers. The unknown states required to design RFOC are estimated using a discrete time Kalman filter (DKF), which is based on the quasi-linear model of the IM. The designed GSM controller is integrated with an already developed KM, and the AWES is simulated using MATLAB and Simulink. The simulation study shows that the GSM control system exhibits appropriate performance even in the presence of the wind gusts, which account for the external disturbance.

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Rotor resistance and speed identification using extended Kalman filter and fuzzy logic controller for induction machine drive

2012 International Conference on Multimedia Computing and Systems ◽

10.1109/icmcs.2012.6320298 ◽

2012 ◽

Cited By ~ 4

Author(s):

Moulay Rachid Douiri ◽

Mohamed Cherkaoui ◽

Sidi Mohamed Douiri

Keyword(s):

Fuzzy Logic ◽

Kalman Filter ◽

Extended Kalman Filter ◽

Fuzzy Logic Controller ◽

Induction Machine ◽

Rotor Resistance ◽

Machine Drive ◽

Speed Identification ◽

Induction Machine Drive

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Rotor flux oriented control of induction machine based drives with compensation for the variation of all machine parameters

Bulletin of the Polish Academy of Sciences Technical Sciences ◽

10.2478/bpasts-2013-0029 ◽

2013 ◽

Vol 61 (2) ◽

pp. 309-324 ◽

Cited By ~ 1

Author(s):

G. Extremiana ◽

G. Abad ◽

J. Arza ◽

J. Chivite-Zabalza ◽

I. Torre

Keyword(s):

Dynamic Performance ◽

Estimation Algorithm ◽

Model Parameters ◽

Electrical Machine ◽

Saturation Curve ◽

Machine Model ◽

Rotor Resistance ◽

Iron Losses ◽

Rotor Flux ◽

On Line

Abstract The performance of rotor flux oriented induction motor drives, widely used these days, relies on the accurate knowledge of key machine parameters. In most industrial drives, the rotor resistance, subject to temperature variations, is estimated on-line due to its significant influence on the control behaviour. However, the rest of the model parameters are also subject to slow variations, determined mainly by the operating point of the machine, compromising the dynamic performance and the accuracy of the torque estimation. This paper presents an improved rotor-resistance on-line estimation algorithm that contemplates the iron losses of the electrical machine, the iron saturation curve and the mechanical losses. In addition, the control also compensates the rest of the key machine parameters such as the leakage and magnetizing inductances and the iron losses. These parameters are measured by an off-line estimation procedure and stored in look up-tables used by the control. The paper begins by presenting the machine model and the proposed rotor flux oriented control strategy. Subsequently, the off-line parameter measurement procedure is described. Finally, the algorithm is extensively evaluated and validated experimentally on a 15 kW test bench

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The full-order state observer speed-sensorless vector control based on parameters identification for induction motor

Measurement and Control ◽

10.1177/0020294019827341 ◽

2019 ◽

Vol 52 (3-4) ◽

pp. 202-211 ◽

Cited By ~ 2

Author(s):

Bo Fan ◽

Zhumu Fu ◽

Leipo Liu ◽

Jiangtao Fu

Keyword(s):

Vector Control ◽

Adaptive System ◽

Control Method ◽

Reference Model ◽

Speed Sensorless ◽

Sensorless Vector Control ◽

Model Reference Adaptive System ◽

Rotor Resistance ◽

Rotor Flux ◽

Model Reference Adaptive

During the operation of speed-sensorless control system for induction motor, the stator and rotor resistance varies greatly with the change of temperature and the frequency of the rotor side, which affects the estimation of the stator flux and leads to the low accuracy of the speed estimation. A speed-sensorless vector control method based on parameters identification with the full-order adaptive state observer is proposed in this paper. In the model reference adaptive system of AC motor, the stator resistance and rotor flux are assigned as state variables to build the reference model, and a full-order flux observer is introduced to adjustable model. Lyapunov theory and Popov superstability theory are used to deduce the speed and rotor resistance adaptive rate. The feedback gain matrix is simplified to speed up the convergence rate of the system. The estimation values of speed and rotor resistance are taken as the proportional integral form, so that an interactive model reference adaptive system is constructed by speed and rotor resistance identification. While observing the rotor flux, it can not only ensure the accuracy of the reference model but also eliminate the disadvantages of the voltage model with integral terms, and the rotor speed can be estimated at the same time. The experimental results show that the accurate performance of speed and flux identification can meet the requirements of application; the proposed control method with the identification of speed and rotor resistance has little fluctuations phenomenon on motor torque in low speed and achieves better performance.

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