• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.268-272
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• 1989

To avoid the use of position sensor or flux sensor in a field oriented induction machine drive system, the terminal quantities are often used to estimate the rotor flux. Since the estimation involves the leakage inductance of the machine, the performance of such systems is sensitive to the variations of leakage. Since estimation of the stator flux is independent of the leakage, the steady state performance of the stator flux oriented system is insensitive to the leakage inductance. In this paper, the torque response of stator flux oriented system is compared to that of rotor flux oriented system by digital simulation. And induction motor sensor less speed control by stator flux oriented method is developed. The performance of the speed estimation is showed by digital simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.4
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• pp.645-650
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• 2007

This paper proposes a parameter estimation technique of a power transformer. Based on the combined equation, it estimates separately the primary and secondary leakage inductances using the least square method from the instantaneous voltages and currents in the steady state. The performance of the proposed technique was investigated by varying the cut-off frequency of the filter and the number of samples per cycle. The estimated values are obtained based on the average value for 41 cycle.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.209-214
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• 1999

New estimation and tuning schemes of inductance variations for rotor flux oriented (RFO) control of induction motor in field weakening region are presented. Stator transient inductance and stator self inductance are estimated. From estimated stator self inductance. magnetizing inductance is estimated and from estimated stator transient inductance, rotor leakage inductance is estimated. Simulation and experimental results prove the effectiveness of the proposed s scheme in constant torque and field weakening region.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.538-544
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• 2010

This paper proposes an estimation algorithm for the separate primary and secondary leakage inductances of a three phase $Y-\Delta$ transformer using least squares method. The voltage equations from the primary and secondary windings are combined into a differential equation to estimate the separate primary and secondary leakage inductances in order to use the line current of the delta winding. Separate primary and secondary leakage inductances are obtained by applying least squares method to the differential equation. The performance of the proposed algorithm is validated under transient states, such as magnetic inrush and overexcitation, as well as in the steady state with various cut-off frequencies of low-pass filter. The proposed technique can accurately generate separate leakage inductances both in the steady and transient states.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.3
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• pp.238-244
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• 2004

To monitor the torque of an induction motor using current, the accurate identification of the motor parameters is very important. In this study, the motor parameters such as rotor resistance, stator and rotor leakage inductance, mutual inductance are estimated for torque monitoring and indirect vector control. Estimated parameters are used to monitor the torque of vector controlled induction motor without any speed measuring sensor. Stator current is measured to estimate the magnetizing current which is used to calculate flux linkage, rotor velocity and motor torque. From the experiments, the proposed method shows a good estimation of the motor parameters and torque under the normal rotational speed.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.1
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• pp.7-12
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• 1999

In this paper, the analytical results on the maximum temperature rise estimation, taking account of the magnetizing current, are presented. Magnetizing current effects are considered for the maximum temperature rise estimation during quenches. By introducing the first order model of the infinite solenoids, we calculate the magnetizing and leakage inductances of the coaxial-wound-superconducting transformers. As the permeability of the transformer core increases, so does the magnetizing inductance, while the leakage inductances and the magnetizing current of the transformer go down. These varying permeability effects on maximum temperature rise estimation is applied to the superconducting transformers, of which specifications have already been published. The calculated results showed sufficient margins to the thermal damage.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.47-48
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• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.1
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• pp.13-20
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• 2020

Accurate parameters based on equivalent circuit are required for high-performance field-oriented control in a three-phase induction motor. In a normal case, stator resistance can be accurately measured using a measuring equipment. Except for stator resistance, all machine parameters on the equivalent circuit should be estimated with particular algorithms. In the viewpoint of traditional regions, the parameters of an induction motor can be identified through the no-load and standstill test. This study proposes an identification method that uses the d-axis model of the induction motor in a stationary frame with the predefined information on stator resistance. Mutual inductance is estimated on the rotational dq coordination similar to that in the traditional no-load experiment test. The leakage inductance and rotor resistance can be estimated simply by applying different voltages and frequencies in the d-axis model of the induction motor. The proposed method is verified through simulation and experimental results.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.1
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• pp.169-175
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• 2006

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.2
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• pp.185-190
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• 2010

This paper presents the estimation on switching technique via output power source analysis of power conversion unit in electric railway vehicle. The focus of this study suggested an alternative on critical problems by using head electric power(HEP). To achieve this, we have measured output power of HEP, and measurement devices set up at output of transformer connected HEP to analysis quality on output power source of head electric power(HEP) unit in electric railway vehicle. Using results of measurement of it, parameters are assumed for simulation to confirm estimation on switching technique. It is confirmed that switching technique is Selected Harmonic Elimination PWM(SHEPWM) and inverter switching frequency is less than 500[Hz]. Throughout experiment and simulation, it is estimated that switching technique used HEP is advanced SHEPWM and switching frequency is about 300[Hz]. Also leakage inductance in transformer is about $180[{\mu}H]$ less than $365[{\mu}H]$ known.