Synchronous generator model identification and parameter estimation from operating data

A novel technique to estimate and model parameters of a 460-MVA large steam turbine generator from operating data is presented. First, data from small excitation disturbances are used to estimate linear model armature circuit and field winding parameters of the machine. Subsequently, for each set of steady state operating data, saturable inductances L/sub ds/ and L/sub qs/ are identified and modeled using nonlinear mapping functions-based estimators. Using the estimates of the armature circuit parameters, for each set of disturbance data collected at different operating conditions, the rotor body parameters of the generator are estimated using an output error method (OEM). The developed nonlinear models are validated with measurements not used in the estimation procedure.     

Nonlinear inverse heat conduction problem of surface temperature estimation by calibration integral equation method

A calibration integral equation method is proposed for estimating the surface temperature in the context of a nonlinear inverse heat conduction problem. The temperature-dependent thermophysical properties and probe positioning are implicitly accounted in the integral equation formulation through calibration tests. A first kind Chebyshev expansion is applied to represent the temperature-dependent property transform function. The undetermined expansion coefficients associated with the Chebyshev expansion are then estimated through two calibration tests. Regularization of the ill-posed problem is achieved by the future-time method. The optimal regularization parameter is estimated using a phase plane and cross-correlation phase plane analyses. Numerical simulation for stainless steel yields highly favorable surface temperature prediction.     

On-line synchronous machine parameter estimation from smalldisturbance operating data

This paper presents a step-by-step system identification approach to estimate the parameters of a three-phase salient-pole synchronous machine rated at 5 kVA from online small disturbance responses. The machine equivalent circuit model linear parameters and the nonlinear saturated parameters are estimated. The estimation is performed using the maximum likelihood algorithm. Simulation studies based on the online measured small and large dynamic disturbances are performed to validate the accuracy of the identified machine model including the saturation     

Mouse megakaryocytes secrete acetylcholinesterase

Acetylcholinesterase (AchE), an essentially specific and early marker of rodent thrombocytic series, in several tissues acts both as a constituent of the cellular membrane and as a secretory enzyme. This study presents the ultrastructural transport and fate of this substance in the megakaryocytes of mouse bone marrow, using Tranum-Jensen and Behnke's adaptation of the indirect thiocholine method. It is shown that megakaryoblasts and megakaryocytes undergo a typical secretory cycle consisting of (1) enzyme synthesis and segregation on the endoplasmic reticulum and nuclear envelope, (2) enzyme concentration in AchE-vesicles and AchE-granules formed from the cisternae of the Golgi apparatus, and (3) discharge in the demarcation membrane system and extracellular space. The AchE-vesicles and granules appear to be hitherto unrecognized megakaryocytic organelles as they do not resemble alpha nor the dense granules, and their mode of formation and fate differ from those of primary lysosomes and peroxidase granules. Released platelets reveal AchE activity in the open canalicular system. The data are compatible with the hypothesis that by controlling acetylcholine concentration in hematopoietic tissues, the secretion of AchE by megakaryocytes can modulate the proliferative activity of megakaryocytes progenitors.     

Iteratively reweighted least squares for maximum likelihoodidentification of synchronous machine parameters from on-line tests

This paper presents a new approach for the statistical identification of synchronous-machine parameters from on-line test data that were recorded on a 202 MVA hydro-generator at Hydro-Quebec's La Grande 3 generating station. Data processing is performed to remove harmonics in noise-corrupted measurements. The time-domain parameter identification is carried out by means of our proposed maximum-likelihood estimation method, also called the iteratively reweighted least-squares algorithm. A comparison of the results with the ordinary weighted least-squares estimation, which is equivalent to the maximum-likelihood estimation only when the noise is white, shows the superiority of the proposed method. This procedure appears more convenient than previous schemes for parameter identification of the synchronous-machine linear equivalent-circuits, especially when the noise statistics are poorly known     

Performance analysis of fast reclosing transients in inductionmotors

Induction motors are used extensively in heavy industry. For these loads, this often requires reclosing on the motor before it reaches zero speed. However, if the supply voltage is applied before the motor reaches zero speed, the motor can be damaged due to excessive current and torque transients. This paper presents a performance analysis of fast reclosing transients in induction motors. It is shown that the optimum time instant for reclosing depends upon the supply voltage and load parameters. The results indicate that the maximum absolute value of instantaneous torque occurs in the first cycle and for every time cycle of supply voltage. In fact, there are at least one positive peak and one negative peak for the torque     

Stability Analysis of Load Sharing Control for Distributed Generation Systems

This paper discusses the small-signal stability analysis of the combined droop and average power method for load sharing control of multiple distributed generation systems (DGS) in a stand-alone ac supply mode. The small-signal model is developed and its accuracy is verified from simulations of the original nonlinear model. It is shown that the small-signal model accurately predicts the stability of the parallel systems.     

Sensorless direct torque control of induction motors used in electric vehicle

A three-phase squirrel-cage induction motor is used as a propulsion system of an electric vehicle (EV). The motor is controlled at different operating conditions using a direct torque control (DTC) technique combined with a new switching pattern producing low harmonics. The operating flux of the motor is chosen optimally for losses minimization and good dynamic response. Since speed estimation is sensitive to rotor resistance variations, the rotor resistance value is calculated and modified in real time continuously. Simulation and experimental results show that the proposed DTC is able to follow the reference speed (which may be only input reference of the system) with a reasonable dynamic and relatively low error.     

Torque ripple analysis of a PM brushless DC motor using finite element method

Three-phase permanent magnet brushless DC motors are widely used. As a function of the rotor position, the torque produced by these machines has a pulsating component in addition to the DC component. This pulsating torque has a fundamental frequency corresponding to six pulses per electrical revolution of the motor. The shape of the torque waveform and, thus, the frequency content of the waveform can be influenced by several factors in the motor design and construction. This paper addresses the various factors that influence the torque waveshape. It is shown that in addition to the basic induced electromotive force (EMF) waveshape, the magnetic saturation in the stator core, and the accuracy in the skewing are also key factors in determining the torque waveshape. Computer simulation using finite element technique has been conducted to study the torque waveform. Simulation results successfully duplicated the torque waveforms measured in experiments under different excitation currents.     

Study of Cogging Torque in Permanent Magnet Machines

Cogging torque is produced in a permanent magnet machine by the magnetic attraction between the rotor-mounted permanent magnets and the stator. It is an undesired effect that contributes to the machines' output ripple, vibration, and noise. This paper analyzes various cogging torque minimization techniques as applied to a permanent magnet machine used in an electric power steering system. A 6-pole, 18 slot, surface-mounted, rare earth type, brushless permanent magnet machine is analyzed. The resultant cogging torque values are computed using a two-dimensional finite element analysis package.