• Journal of Power Electronics
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• v.14 no.5
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• pp.1000-1007
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• 2014

This paper proposes an on-line rotor time constant estimation strategy for indirect field oriented induction machines. The performance of the indirect field oriented control is dependent especially on the rotor time constant whose value varies according to the temperature. The proposed method calculates the difference between the nominal rotor time constant and the real value from the d- and q-axis integration terms of a proportional integral (PI) current regulator and the demanded voltages of the induction machine to regulate the current in the steady state. Because the proposed strategy has a simple structure and is available in wide speed and torque ranges, the proposed method can be easily used in the industrial field. The effectiveness of proposed strategy is verified with simulations and a 7.5kW experimental setup.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.113-118
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• 2003

The proposed rotor time constant estimation method can be applied to the direct vector control system of induction motor with flux observer In this paper the flux observer proposed by Gopinath model are used. This paper presents a new scheme for on-line estimation of rotor time constant using estimated rotor flux phase and current model rotor flux phase. The major advantage of this method are its dynamic correction capability, simplicity and accuracy as well as independence from change in motor parameter. simulation results are presented which demonstrate the effectiveness of the on line rotor time constant estimation.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.225-229
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• 1998

If there is a mismatch between the controller programmed rotor time constant and the actual time constant of motor, the decoupling between the flux and torque is lost in an indirect rotor field oriented control. This paper presents a new estimation scheme for rotor time constant using artificial neural networks. The parameters of induction motor model organize 2 layer neural to be weight between neuron, which is proposed new in this paper. This method makes networks simple, so its brings not only the improvement in speed but simplification in calculation. Furthermore, it is possible to estimated rotor time constant real time through on-line learning without using off-line learning. The digital simulation and the experimental results to verify the effectiveness of the new method are described in this paper.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.5
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• pp.413-419
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• 2004

In the induction motor direct vector control system using the Gopinath model flux observer, the deterioration of the dynamic response due to the detuned rotor time constant is investigated. To solve this problem, the on line estimation algorithm of the rotor time constant using model reference adaptive control is proposed. The effect of the motor parameter variation on the rotor time constant estimation is analyzed through experiment. The estimation error due to the parameter variation converges within 5%. Thus applying the proposed algorithm to the Gopinath model flux observer, the robust direct vector control system of the induction motor to the parameter variation can be implemented.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.201-208
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• 1999

This paper presents the degradation of the system performance according to the vmiation of the rotor time constant. The algorithm for the on-line estimation of rotor time constant is proposed. which is applied to the consistent relationship between the tangent torque angle of the synchronous reference frame and that of stationary reference f frame. For the purpose of the validity of proposed algorithm. the computer simulation and the experiments have been p performed.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.216-218
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• 1995

In this article a neural network adaptive observer is proposed and applied to the case of induction motor control. The high performance vector control drives require exact knowledge of rotor flux. Because rotor time constant is needed to observe rotor flux, the accurate estimation of rotor time constant is important. For these problems, proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subject to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.188-191
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• 2002

This paper presents a method for on-line estimation of rotor time constant of induction motor. The proposed method applies a model reference adaptive system(MRAS) using rotor flux vector. The MRAS consists of two independent observers to estimate the rotor flux vector; one based on voltage equations of rotor flux vector, the other based on current equations of them. The MRAS utilizes concept of auxiliary variables to normalize observer output and decrease high-frequency components of its input. Experimental results verify the validity and usefulness of proposed method

• Journal of the Korean Society of Industry Convergence
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• v.2 no.2
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• pp.91-102
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• 1999

The paper describes a robust adaptive control algorithm for induction motor drive without speed sensor at low speed range. The control algorithm use only current sensors in a space vector pulse width modulation within loop control with rotor speed estimation and voltage source inverter. On-line rotor speed estimation is based on utilizing parallel model reference adaptive control system. MRAC of the modified flux model for flux and rotor speed estimator uses dual-adaptation mechanism, ${\omega}_r$ and ${\omega}_e$ scheme. The estimated flux components in the model can be compensated from the effects of offset errors on pure integrals. It can be compensated to the parameter variations and torque fluctuation with speed estimation in less then 10 rad/sec. In a simulation, the proposed induction motor control algorithm without speed sensor at very low speed range are shown to operate very well in spite of variable rotor time constant and fluctuating load without change the controller parameters. The suggested control strategy and estimation method have been validated by simulation study, and it proposed the designed system for the implementation using TI320C31 DSP/ASIC controller.

• Journal of Power Electronics
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• v.9 no.2
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• pp.188-197
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• 2009

This paper presents an adaptive flux observer to estimate stator flux linkage and stator inductances of an interior permanent-magnet synchronous machine considering magnetic saturation. The concept of static and dynamic inductances due to saturation is introduced in the machine model to describe the relationship between current and flux linkage and the relationship between their time derivatives. A flux observer designed in the stationary reference frame with constant inductance is analyzed in the rotor reference frame by a frequency-response characteristic. An adaptive algorithm for an on-line inductance estimation is proposed and a Lyapunov-based analysis is given to discuss its stability. The dynamic inductances are estimated by using Taylor approximation based on the static inductances estimated by the adaptive method. The simulation and experimental results show the feasibility and performance of the proposed technique.