• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.207-209
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.33-37
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• 2002

This paper presents a simple torque estimation method and the switching angle control of SRM using Neural Network. SRM has gaining much interest as industrial applications due to the simple structure and high efficiency. Adaptive switching angle control is essential for the optimal driving of a SRM because of the driving characteristic varies with the load and speed. The proper switching angle which can increase the efficiency was investigated in this paper Neural Network was adapted to regulate the switching angle and nonlinear inductance modelling. Experimental result shows the validity of the switching angle controller.

• 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.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.629-630
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• 2006

This paper describes a novel sensorless excitation position detecting method of Switched Reluctance Motor(SRM) drive. A suitable excitation pattern of each phases is determined by comparison of detecting current without an inductance estimation. The principle of the rotor position estimation is based on the detection of phase current according to rotor position. This sensorless method is very simple and gives efficient control of drive system. The suggested method is verified by experiments.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.558-561
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• 2005

This paper describes a novel method of detecting excitation position in switched reluctance motor(SRM) drive. Some strategies of position sensorless control methods for the motor include the measurement of phase current and applied pulse voltage in an unexcited phase is suggested. The principle of the estimation of a rotor position is based on the detection of inductance by pulse currents. This sensorless method is very simple to detect excitation position estimation and gives efficient control of drive system. Suggested method is verified by some simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.293-300
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• 2011

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance and adaptive fuzzy learning contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator and AFLC is confirmed by comparing to conventional algorithm.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.129-131
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• 2005

This paper deals with an electromagnetic analysis and control parameter estimation of a moving-coil linear oscillatory actuator (MCLOA). Analytical solutions for electromagnetic characteristics of the MCLOA are obtained from transfer relations derived in terms of a magnetic vector potential and two-dimensional (2-d) rectangular coordinate systems. And then, on the basis of 2-d analytical solutions, control parameters such as the thrust constant, the back-emf constant and winding inductances are estimated. Finally, analytical results for both electromagnetic characteristics and control parameters of the MCLOA are validated extensively by finite element (FE) analyses. In particular, test results such as static thrust, resistance and inductance measurements are given to confirm the analyses.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.2
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• pp.47-53
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• 2004

The salient pole rotor type single phase SRM (switched reluctance motor) uses radial and axial direction magnetic flux simultaneously. Therefore, the output power per unit volume is very high and the shaft length is shorter than other types of SRMs with the same output. Furthermore, it can be manufactured with low cost owing to its simple structure and driving circuit. The prototype was designed using the theory of the traditional rotating machine and 3D FEM analysis. On this paper, the experiment apparatus, which includes the fabricated prototype in previous researches, was fabricated to measure the current and voltage of the prototype. Then the flux linkage, inductance and magnetic co-energy were calculated using the experimental results. Finally, the measured magnetic co-energy was compared with the simulated magnetic co-energy.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.151-154
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• 2002

This paper presents an implementation of high-dynamic performance control system of Reluctance Synchronous Motor(RSM) drives for an industrial servo drive system with direct torque control(DTC). The estimation of the stator flux and torque are obtained by using flux observer which a saturated inductance Ld and Lq of d-q axises can be compensated by using the neural network from measuring the modulus and angle of the stator current space vector. To obtain fast torque response and maximum torque/current, the reference command flux is ensured by imposing Ids=Iqs. The control strategy is proposed to fast response and optimal efficiency for RSM drive. The developed digitally high-performance control system are shown a good response characteristic of control results and high performance features using 1.0kW RSM.

• Proceedings of the KIEE Conference
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• 2002.06a
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• pp.135-141
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• 2002

This paper presents an implementation of high-dynamic performance of position sensorless motion control system of Reluctance Synchronous Motor(RSM) drives for an industrial servo system with direct torque control(DTC), The problems of DTC for high-dynamic performance and maximum efficiency RSM drive due to a saturated stator linkage flux and nonlinear inductance curve with various load currents, The accurate estimation of the stator flux and torque are obtained using stator flux observer of which a saturated inductance Ld and Lq can be compensated by adapting from measurable the modulus and angle of the stator current space vector. To obtain fast torque response and maximum torque/current with varying load current, the reference command flux is ensured by imposing Ids=Iqs. This control strategy is proposed to fast response and optimal efficiency for RSM drive. In order to prove rightness of the suggested control algorithm, the actual experiment carried out at ${\pm}$20 and ${\pm}$1500 rpm. The developed digitally high-performance control system are shown some good response characteristic of control results and high performance features using 1.0kW RSM of which has 2.57 Ld/Lq salient ratio.