EPE Association: EPE-PEMC 2000 - Topic 07b: Sensing and Observing of Parameters

EPE-PEMC 2000 - Topic 07b: Sensing and Observing of Parameters
You are here: EPE Documents > 04 - EPE-PEMC Conference Proceedings > EPE-PEMC 2000 - Conference > EPE-PEMC 2000 - Topic 07: Sensing and Observing > EPE-PEMC 2000 - Topic 07b: Sensing and Observing of Parameters

   [return to parent folder]

   An Application of Genetic Algorithm to the Identification of Electrical Parameters of an Induction Motor
By Razik H., Rezzoug A. [View]
[Download]

Abstract: This paper describes a method to identify the electrical parameters of an induction motor. It is based on a genetic algorithm. This one does not require the evaluation of the gradient in order to minimise a mathematical function. This approach allows to find a global minimum; while being freed from local minima. This application shows the simple and effective algorithm. It is used to determine the electrical parameters of an electrical machine in this paper. In order to initialise the estimated parameters, the nameplate rating is used. The induction motor is excited thanks to an inverter. The experimental results confirm the effectiveness of this algorithm.

   Identification at Standstill of Induction Machines Including the Saturation Effects
By Peixoto Z.M.A., Seixas P.F.* [View]
[Download]

Abstract: This paper deals with an automatic identification procedure that enables the determination of all electrical parameters during the self-commissioning phase. Firstly, the tests are performed close to the nominal excitation condition and neglecting all model non-linearities. Subsequently, using different magnetizing currents and considering the effects of magnetic saturation on the machine model, the magnetizing inductance is estimated. Experimental results demonstrated the good performance of the proposed estimators.

   Identification of Induction Motor Parameters with Use of Neural Networks Taking into Account Main Flux Saturation Effect
By Balara D., Timko J. [View]
[Download]

Abstract: A method for identification of parameters of induction motor with saturation effect taken into account is presented in this paper. Adaptive identifier with structure similar to model of motor performs identification. This identifier can be regarded as a special neural network, therefore its adaptation is based on the gradient descent method and Back-Propagation well known in the neural networks theory. Parameters of electromagnetic and mechanical subsystems were identified, including the nonlinear magnetizing curve and friction characteristic. Testing was performed with simulations taking into account noise in measured quantities.

   Induction Machine DSP Based Vector Controller with On-Line Rotor Resistance Estimation
By Idžotiæ T., Erceg G., Ferega D. [View]
[Download]

Abstract: This thesis describes vector control system of induction machine using Digital Signal Processor (DSP). System is developed with DSP ADSP2101 and motion control coprocessor ADMC201 (Analog Devices). Control algorithm is based on orientation of magnetizing flux, rotor flux estimation and on-line identification of rotor resistance. Induction machine vector control system verification is performed experimentally (1.5kW, 380V, 4.3A) and with simulation on personal computer.

   The New Method for Estimation of Stator Winding Temperature and Thermal Protection of Low Voltage Induction Motor
By Raca D., Matic P.*, Vasic V. [View]
[Download]

Abstract: Novel concept of thermal protection relaying based on measurement of current and voltage of an induction machine is introduced and tested in this paper. This method is inexpensive and best suited for a low voltage induction motor in unregulated and regulated drives. It's advantages over actual methods are briefly described in the paper. Proposed method is based on a fact that conductor resistance increases linearly with temperature. It is easy to determine temperature from estimated stator winding resistance of a low voltage induction motor due to a low influence of a skin effect. Obviously this method does not rely on a thermal model of a motor. In this way uncertainties considering thermal model parameters ignorance are eliminated. Even more important advantage of this method over actual methods is that in this way the real average temperature of a stator windings is obtained no meter what caused temperature change. Simulations and experiments presented in this paper are conducted to investigate reliability of a method for wide range of regimes, parameter ignorance and different estimator setups.

EPE-PEMC 2000 - Topic 07b: Sensing and Observing of Parameters
You are here: EPE Documents > 04 - EPE-PEMC Conference Proceedings > EPE-PEMC 2000 - Conference > EPE-PEMC 2000 - Topic 07: Sensing and Observing > EPE-PEMC 2000 - Topic 07b: Sensing and Observing of Parameters
	[return to parent folder]

	An Application of Genetic Algorithm to the Identification of Electrical Parameters of an Induction Motor By Razik H., Rezzoug A.	[View] [Download]
Abstract: This paper describes a method to identify the electrical parameters of an induction motor. It is based on a genetic algorithm. This one does not require the evaluation of the gradient in order to minimise a mathematical function. This approach allows to find a global minimum; while being freed from local minima. This application shows the simple and effective algorithm. It is used to determine the electrical parameters of an electrical machine in this paper. In order to initialise the estimated parameters, the nameplate rating is used. The induction motor is excited thanks to an inverter. The experimental results confirm the effectiveness of this algorithm.

	Identification at Standstill of Induction Machines Including the Saturation Effects By Peixoto Z.M.A., Seixas P.F.*	[View] [Download]
Abstract: This paper deals with an automatic identification procedure that enables the determination of all electrical parameters during the self-commissioning phase. Firstly, the tests are performed close to the nominal excitation condition and neglecting all model non-linearities. Subsequently, using different magnetizing currents and considering the effects of magnetic saturation on the machine model, the magnetizing inductance is estimated. Experimental results demonstrated the good performance of the proposed estimators.

	Identification of Induction Motor Parameters with Use of Neural Networks Taking into Account Main Flux Saturation Effect By Balara D., Timko J.	[View] [Download]
Abstract: A method for identification of parameters of induction motor with saturation effect taken into account is presented in this paper. Adaptive identifier with structure similar to model of motor performs identification. This identifier can be regarded as a special neural network, therefore its adaptation is based on the gradient descent method and Back-Propagation well known in the neural networks theory. Parameters of electromagnetic and mechanical subsystems were identified, including the nonlinear magnetizing curve and friction characteristic. Testing was performed with simulations taking into account noise in measured quantities.

	Induction Machine DSP Based Vector Controller with On-Line Rotor Resistance Estimation By Idžotiæ T., Erceg G., Ferega D.	[View] [Download]
Abstract: This thesis describes vector control system of induction machine using Digital Signal Processor (DSP). System is developed with DSP ADSP2101 and motion control coprocessor ADMC201 (Analog Devices). Control algorithm is based on orientation of magnetizing flux, rotor flux estimation and on-line identification of rotor resistance. Induction machine vector control system verification is performed experimentally (1.5kW, 380V, 4.3A) and with simulation on personal computer.

	The New Method for Estimation of Stator Winding Temperature and Thermal Protection of Low Voltage Induction Motor By Raca D., Matic P., Vasic V.*	[View] [Download]
Abstract: Novel concept of thermal protection relaying based on measurement of current and voltage of an induction machine is introduced and tested in this paper. This method is inexpensive and best suited for a low voltage induction motor in unregulated and regulated drives. It's advantages over actual methods are briefly described in the paper. Proposed method is based on a fact that conductor resistance increases linearly with temperature. It is easy to determine temperature from estimated stator winding resistance of a low voltage induction motor due to a low influence of a skin effect. Obviously this method does not rely on a thermal model of a motor. In this way uncertainties considering thermal model parameters ignorance are eliminated. Even more important advantage of this method over actual methods is that in this way the real average temperature of a stator windings is obtained no meter what caused temperature change. Simulations and experiments presented in this paper are conducted to investigate reliability of a method for wide range of regimes, parameter ignorance and different estimator setups.