Improving dynamic aggregation of induction motor models

The authors describe the modeling of squirrel cage induction motors and the derivation of steady-state and dynamic models that can be utilized in harmonic penetration studies. They present the results of laboratory testing of three-phase and single-phase induction motors to estimate these static and dynamic models. Such models are extremely useful in: identifying effective control strategies to enhance efficiency of variable voltage/variable frequency motor drives; assessing machine performance with excitation voltage and frequency variations; and identifying nonlinear load impedance models of induction motor loads in harmonic penetration programs such as Cyme and Harmflo software. These models were utilized in deriving efficient open-loop control strategies based on optimized volt/hertz (V/sub m//f/sub s/) ratio characteristics for minimum input power, minimum losses, and maximum efficiency. >

A model of an induction motor with an asymmetric stator winding is developed; it may be represented as two phases connected in parallel or in series and displaced is space by some angle.

Current signature analysis of induction motor becomes very much popular for its Condition monitoring purpose. Most of these studies in recent years are focused on hardware. Though, to build an experimental set-up for fault emulating machines is not an easy task. It involves too much cost and risk of damage. Moreover, it is not possible to create different types of faults in the same machine. In this paper an accurate but simple model of 3-phase Induction motor is being proposed which describes the machine at low frequency as well as at high frequency for different types of fault situations. The model, based on DM, CM characteristics of the machine, is well suited for power frequency (50 Hz) and high frequency applications like adjustable speed drives (ASDs). A mechanical model of a three-phase induction machine is incorporated to this electrical model to make a universal model of dynamic squirrel cage induction motor for overall simulation. The proposed model has the feature to incorporate different types of electrical fault like, stator inter-turn fault, phase-to-phase and phase-to ground insulation fault etc. The premature conditions of the above faults can also be emulated.

This article examines several reduced-order models of squirrel-cage induction motors. The full-order model and its reduced-order models are used to calculate motor speed behavior during symmetrical voltage sags. The stability predicted by several reduced-order models of induction motors during symmetrical voltage sags with different depths and durations is also explored. Moreover, simulations of 36 motors of different power ratings are performed, and results are compared with simulations made with the classical fifth-order single-cage model and its corresponding reduced-order models. The main conclusion is that for speed stability evaluation purposes, even the reduced first-order double-cage model gives better results than the fifth-order single-cage model, which neglects the deep-bar effect.

A mathematical model of induction motor (IM) based on the second Kirchhoff’s law with Maxwell’s equation taken into account has been developed. A mathematical model of a three-phase induction motor with a short-circuited rotor in phase axes without taking into account the saturation of the magnetic circuit and the losses in steel has been elaborated. A nonlinear model of asynchronous motor in the state space in the rotating system (d-q) of coordinates synchronized with the stator flux and a simulation model of IM in MatLab/Simulink software, with the possibility of setting angular velocity of rotation and resistance torque, have also been developed. The model-oriented design of the control program is performed on the example of digital signal processors from Texas Instruments on the LAUNCHXL-F28379D board. This description of the dynamics provides a direct insight into the physical processes in IMs. The advantage of the considered mathematical description of electromechanical energy conversion processes in three-phase IM is that it uses instantaneous values of currents and voltages of stator and rotor winding phases as variables.

A unified approach to modeling and vector control of induction motors (IM) is presented. In comparison with the conventional method, which uses the concept of turn-ratio associated with energy conversion between stator and rotor of induction machine, the paper presents a unified framework for modeling and vector control of induction motors using state variables. The IM model representations and the associated vector control methods referring to various frames, including stator, rotor, and air gap flux frames, can be derived simply by selecting different state variables; thereby clearly identifying the relationship between machine modeling and vector control from the view point of control rather than energy conversion.

PurposeTo study the inclusion of inter‐bar (IB) currents in a multi‐slice finite element (FE) model of induction motors and in particular the effect of the associated skew discretisation. To validate the model experimentally.Design/methodology/approachBoth a classical uniform distribution and a gauss distribution of the slices and the lumped IB resistances are considered. Measurements on a 3 kW induction motor allows one to estimate its IB resistance and to validate the FE model.FindingsA gauss distribution of the slices allows one to use fewer slices and thus reduces the computational cost. The simulation results show that, at full load, skew changes the different loss components significantly, while the IB currents have a minor effect.Research limitations/implicationsThe direct measurement of the IB resistance is by no means trivial. In the frame of this paper, it was indirectly determined, namely by means of a short‐circuit test.Originality/valueThe gauss distribution of the slices and the IB resistance; the systematic study of the skew discretisation; the experimental determination of the IB resistance.

Fine-Grained Parallel and Distributed Spatial Stochastic Simulation of Biological Reactions

The most inclined fault in induction motors is bearing fault. This paper discusses in details the various causes of bearing faults. To diagnose these faults diverse techniques have already been developed. Comprehensive literature review on detection techniques of bearing faults in induction motor has been furnished in this paper. These are sorted into specific areas as per their approaches. An important focus of this paper is on modeling of induction motor under the bearing fault condition. This paper suggests that the model-based techniques are more advantageous compared to different experiment- based techniques. Any localized fault in bearing can be thought-about as eccentric fault that creates non-uniformity in the air-gap. This non-uniform air-gap affects the stator inductance and thereby stator currents. In a few research works the later approach has been tried.

A critical analysis on broken rotor bar fault in three-phase induction motor is presented in this manuscript. Core research is carried on model-based broken bars fault detection and diagnosis for induction motors. A wide variety of faulty induction motor models are available in the literature. Out of which the model induction motor models based reference frames are widely used in fault diagnosis. It is believed to be a novel contribution, as researchers haven't considered whether these faulty models behave similar behaviour in stationary, rotor, synchronous and arbitrary reference frames. As an extension, a newly modified broken rotor induction motor model is proposed in this manuscript. To validate proposed idea dynamic computations of models are carried on using MATLAB R2022a programming software. The novel idea is verified with extensive simulation studies with various induction motors. The results and observations are presented clearly in this manuscript.

This paper presents a generalized model of multi-phase induction motor drive using matlab/simulink. Multiphase induction motor (more than three phases) drives possess several advantages over conventional three-phase drives, such as lower torque pulsation, higher torque density, fault tolerance, stability, high efficiency and lower current ripple. When the number of phases increases, it is also possible to increase the power /torque per rms ampere for the same volume machine. In this paper, a generalized dq-axis model is developed in Matlab/Simulink for a multi-phase induction motor. The simulation results are presented for 5, 6, 7, 9 and 12 phase induction motor under varying load conditions. Transient response of the multi-phase induction motors are given for different number of phases.

The paper proposes a mathematical model of a three-phase induction motor with an asymmetrical twelve-zone winding of stator with parallel connection of subwindings. The mathematical model was developed using the theory of generalized electromechanical converter and contains equations of electrical equilibrium of six stator windings and three rotor windings. The equations for calculating the electromagnetic moment and the equations of motion of the induction motor with an asymmetrical twelve-zone stator winding rotor were obtained. The developed mathematical model in the form of cell-matrix equations has been implemented in MATLAB/Simulink.

This work presents a three-phase induction motor speed control methodology from its nominal operating point through a Gaussian linear regulator with integral action and disturbance rejection for systems subject to unknown inputs. The regulator uses an induction motor model that treats the load inertia variation as an unmanipulated external disturbance. The load and motor variables are estimated by a modified version of the Kalman filter (KF) for unknown inputs using electrical current and voltage measurements and a compatible motor model. Using estimates from KF, the integral of the speed deviation from the nominal value, and external disturbance treatment, the controller performs load variation rejection and speed regulation. Improved noise handling in measurements, unmeasured load estimation, speed regulation, and steady-state robustness to load changes are among the contributions of the proposed control methodology to the induction motor control and filtering literature. Performance is tested through computational simulation using a suitable induction motor model and a methodology that considers practical aspects of measurements and control applications.

In this paper, a simple mathematical model of induction motors in the field-oriented frame, including power losses, is presented. The parameter identification and influence of supply and load conditions on the induction motor parameters are discussed. Changes of motor parameters are expressed as polynomial functions of stator angular frequency, slip angular frequency and temperature of motor windings. Sensitivity of control systems with regard to the changes of motor parameters was decreased by applying open-loop adaptive control. Based on this model, a loss minimisation control algorithm is proposed. Experimental investigations were carried out on a laboratory model of an inverter-fed induction motor drive.

Current simulation tools for multibody dynamics are not problem dependent, they use the same modeling process to all cases regardless of their characteristics. In addition, real-time simulation of small multibody systems is achievable by existing simulation tools, however, real-time simulation of large and complex systems is not possible with existing methods. This is a challenge that needs to be addressed before further advances in mechanical simulation with hardware-in-the-loop and man-in-the-loop, as well as virtual prototyping are made possible. This paper addresses the issue of how the modeling process-dependent versus independent coordinates, and descriptor form versus state-space form of the equations of motion-affects the dynamic simulation of multibody systems and how it may be taken into account and added to the concept of intelligent simulation. With this new concept all the factors involved in the simulation process — modeling, equations, solution, etc. — are chosen and combined depending upon the characteristics of the system to be simulated. It is envisioned that this concept will lead to faster and more robust real-time simulators.