• Journal of Power Electronics
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• v.17 no.6
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• pp.1545-1552
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• 2017

Identifying the load and mutual inductance is essential for improving the power transfer capability and power transfer efficiency of Inductive Power Transfer (IPT) systems. In this paper, a steady-state load and mutual inductance identification method focusing on series-parallel compensated IPT systems is proposed. The identification model is established according to the steady-state characteristics of the system. Furthermore, two sets of identification results are obtained, and then they are analyzed in detail to eliminate the untrue one. In addition, the identification method can be achieved without extra circuits so that it does not increase the complexity of the system or the control difficulty. Finally, the feasibility of the proposed method has been verified by simulation and experimental results.

• Journal of Power Electronics
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• v.18 no.2
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• pp.492-501
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• 2018

In the rotor-flux oriented control used in induction motors, the electrical parameters of the motors should be identified. Among these parameters, the mutual inductance and rotor resistance should be accurately tuned for better operations. However, they are more difficult to identify than the stator resistance and stator transient inductance. The rotor resistance and mutual inductance can change in operations due to flux saturation and heat generation. When detuning of these parameters occurs, the performance of the control is degenerated. In this paper, a novel method for the concurrent identification of the two parameters is proposed based on recursive least square estimation and model reference adaptive control.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.199-202
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• 2000

The accurate identification of the motor parameters in crucially important to achieve high dynamic performance of induction motors. In this paper parameter auto-tuning algorithms for stator(rotor) resistance stator(rotor) leakage inductance mutual inductance and rotor inertia. Stator(rotor) resistance and stator(rotor) leakage inductance are identified based on the stationary coordinate and mutual inductance and rotor resistor on the scalar speed control and the transient motor terminal voltage. To demonstrate the practical significance of our results we present some experimented results.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.3
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• pp.282-290
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• 2001

The accurate identification of the motor parameters is crucially important to achieve high dynamic performance of induction motors. In this paper, th motor parameters such as stator(rotor) resistance, stator(rotor) leakage inductance, mutual inductance, and rotor inertia are measured in off-line. Stator(rotor) resistance and stator(rotor) leakage inductance are measured based on the stationary coordinate equations of induction motors. On the other hand, mutual inductance are measured under the scalar control. Finally, the inverse rotor time constant is identified in on-line using an extended kalman filter algorithm. To demonstrate the practical significance of the results, Some experimental results are presented.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.131-134
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• 2001

The accurate identification of the motor parameters is crucially important to achieve high dynamic performance of induction motors. In this paper, the motor parameters such as rotor resistance, stator(rotor) leakage inductance, mutual inductance are measured for torque monitoring and indirect vector control. To demonstrate the practical significance of the results, some experimental results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1253-1256
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• 1996

In this paper, a new nonlinear feedback linearization control scheme for induction motors is developed. The control scheme employs a fuzzy nonlinear identification scheme based on fuzzy basis function expansion to adoptively compensate the parameter variations, i.e. rotor resistance, mutual and self inductance etc. An important feature of the proposed control scheme is to incorporate the sliding mode controller into the scheme to speed up convergence rate. Simulation tests show the robust behavior of the proposed controller in the presence of the parameter uncertainties of the machine.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.239-244
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• 1998

We propose a nonlinear feedback controller that can control the induction motors with high dynamic performance by means of decoupling of motor speed and rotor flux. A new recursive adaptation algorithm for rotor resistance which can be applied to our nonlinear feedback controller is also presented in this paper. Some simulation results show that the adaptation algorithm for rotor resistance is robust against the variation of stator resistance and mutual inductance. In addition, it is computationally simple and has small estimation errors.

• 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.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.900-903
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• 2003

An identification method of induction motor parameters such as rotor time constant and mutual inductance at standstill condition is discussed assuming that stator resistance and leakage has already been obtained applying two different DC voltage and single phase voltage to the induction motor, respectively. This proposed scheme is implemented by means of Model Reference Adaptive Control (MRAC) technique, which uses a rotor flux equation in voltage model as a reference model and one in current model and is demonstrated through experiment.

• 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.