Indirect Vector Control of Linear Induction Motors Using Space Vector Pulse Width Modulation

Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.This research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)inverters.The framework under consideration is developed in four stages.To begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical dynamicmodel.The research presents a modified SVPWM inverter control scheme.By tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are derived.All the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control scheme.The reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data sets.For the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed range.The speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 s.The maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust ripple.Due to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications.

Speed Identification of Speed Sensorless Linear Induction Motor Based on MRAS

In the linear induction motor control system,the optical grating speed transducer is susceptible to strong magnetic field interference.What's more,it may reduce motor integration and raise device costs.Therefore a speed identification method to replace grating speed transducer is studied in this article.This speed identification method for linear induction motor mainly adopts Model Reference Adaptive Method(Abbreviated as MRAS)and Popov Hyperstability Theory.The research content of this paper can be divided into four parts.First,the mathematical model of the motor based on the model reference adaptive system structure is deduced.Second,the adaptive law of the estimated speed is solved by Popov hyper-stability theory,which ensures the stability of the system.Third,the simulation model of the linear induction motor speed identification control system based on model reference adaptation is built in the MATLAB environment.Finally,the simulation test and analysis are carried out.The simulation results show that the speed identification control system can track the actual speed of the linear induction motor well in the no-load operation and the load operation,and the stability of the system is guaranteed in the full speed range.

Model Predictive Control-Based Direct Torque Control for Matrix Converter-Fed Induction Motor with Reduced Torque Ripple

To reduce the torque ripple in motors resulting from the use of conventional direct torque control(DTC),a model predictive control(MPC)-based DTC strategy for a direct matrix converter-fed induction motor is proposed in this paper.Two new look-up tables are proposed,these are derived on the basis of the control of the electromagnetic torque and stator flux using all the feasible voltage vectors and their associated switching states.Finite control set model predictive control(FCS-MPC)has then been adopted to select the optimal switching state that minimizes the cost function related to the electromagnetic torque.Finally,the experimental results are shown to verify the reduced torque ripple performance of the proposed MPC-based DTC method.

Finite Control Set Model Predictive Torque Control Using Sliding Model Control for Induction Motors

Finite control set model predictive torque control(FCS-MPTC)has become increasingly prevalent for induction motors(IM)owing to its simple concept,easy incorporation of constraints and strong flexibility.In traditional FCS-MPTC speed controller design,a classical proportional integral(PI)controller is typically chosen to generate the torque reference.However,the PI controller is dependent on system parameters and sensitive to the load torque variation,which seriously affects control performance.In this paper,a model predictive torque control using sliding mode control(MPTC+SMC)for IM is proposed to enhance the robust performance of the drive system.First,the influence of the parameter mismatches for FCS-MPTC is analyzed.Second,the shortcomings of traditional PI controller are derived.Then,the proposed MPTC+SMC method is designed,and the MPTC+PI and MPTC+SMC are compared theoretically.Finally,experimental results demonstrate the correctness and effectiveness of the proposed MPTC+SMC.In comparison with MPTC+PI,MPTC+SMC has the better dynamic performance and stronger robust performance against parameter variations and load disturbance.

Field-weakening control system of induction motor based on model prediction

Considering the actual demand for high-speed operation of induction motors in industrial occasions,the characteristics of induction motors in different regions are analyzed,especially the field weakening characteristics of induction motors in high-speed operation are studied.A field weakening control method of induction motor based on model predictive control(MPC)algorithm is proposed,which can predict the future state of the controlled object,and then obtain the optimal control variables by colling optimization.The simulation results show that the field-weakening control method based on MPC algorithm has faster response speed,stronger robustness and better control performance than the traditional control methods.

Efficiency of Model Induction Motor Using Various Non-Oriented Electrical Steels

The performance of a 3-phase 6-pole 400 W inverter-drive induction motor was investigated using a variety of non-oriented electrical steels for stator core at PWM inverter fundamental wave frequencies of 30 to 300 Hz. There existed an optimum Si content of the material depending on the tooth flux density. Both reduction of material thickness and stress-relief annealing of the stator core improved the motor efficiency. The influence of Si content on the efficiency was small at lower PWM frequencies, while at higher frequencies the motor efficiency increased with increasing Si content. The Cu loss WC increased and the Fe loss Wi counteractiveiy decreasedwith increasing Si content at lower frequencies; while at higher frequencies Wi had dominant effect on the efficiency. Newly developed materials RMA, having lower Fe losses after stress-relief annealing and higher flux densities with lower Si contents, showed motor efficiencies superior to conventional J1S grade materials with comparable Fe losses.

Modeling and simulation of induction motor drive system to investigate and mitigate of PWM inverter’s adverse effects

Modeling and simulation of induction motor drive system to investigate and mitigate the adverse effects of PWM inverter based on analysis, modeling and simulation are presented. The estimation of conducted disturbances and other adverse effects of PWM inverter by simulation offer a considerable gain from the economic point of view. For an accurate model of the motor drive system including mains, rectifier, inverter, motor and its long cables, the high frequency parasitic current paths are taken into account. The novel model and its parasitic values for three-phase induction motor system are presented. Finally a new solution for suppressing EMI, common mode voltage, leakage current, bearing current and shaft voltages is proposed and the results show the excellent performances of proposed solution including active and passive filters.

Dynamic Modelling of Submersible Pump Based Solar Water-Pumping System with Three-Phase Induction Motor Using MATLAB

The main purpose of this paper is to design and model a water-pumping system using a submersible multi-stage centrifugal pump driven by a three-phase induction motor. The system is intended for pumping water to the surface from a deep well using three power supply systems: a general network, a photo-voltaic (PV) system, and a PV system with a battery bank. These systems are used to compare two three-phase induction motors—namely, a motor with a drive and another one without a drive. The systems dynamic models are simulated in MATLAB/Simulink and the results compared with the manufacturer’s data for validation purposes. The simulation results generally show system dynamics and expected performance over a range of operation.

Induction Motor Modeling Based on a Fuzzy Clustering Multi-Model—A Real-Time Validation

This paper discusses a comparative study of two modeling methods based on multimodel approach. The first is based on C-means clustering algorithm and the second is based on K-means clustering algorithm. The two methods are experimentally applied to an induction motor. The multimodel modeling consists in representing the IM through a finite number of local models. This number of models has to be initially fixed, for which a subtractive clustering is necessary. Then both C-means and K-means clustering are exploited to determine the clusters. These clusters will be then exploited on the basis of structural and parametric identification to determine the local models that are combined, finally, to form the multimodel. The experimental study is based on MATLAB/SIMULINK environment and a DSpace scheme with DS1104 controller board. Experimental results approve that the multimodel based on K-means clustering algorithm is the most efficient.

Study on maximum efficiency control strategy for induction motor

Two new techniques for efficiency-optimization control(EOC) of induction motor drives were proposed. The first method combined Loss Model and "golden section technique", which was faster than the available methods. Secondly, the low-frequency ripple torque due to decrease of rotor flux was compensated in a feedforward manner. If load torque or speed command changed, the efficiency search algorithm would be abandoned and the rated flux would be established to get the best transient response. The close agreement between the simulation and the experimental results confirmed the validity and usefulness of the proposed techniques.

Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller

In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.

Synchronization of Robot Manipulators Actuated By Induction Motors with Velocity Estimator

A complete modeling(including the actuator dynamics)of a robot manipulator that uses three-phase induction motors is presented in this paper.A control scheme is designed to synchronize robot manipulators actuated by induction motors under a masterslave scheme in the case where the joint velocity of the slave robots is estimated.All of the research on the synchronization of robot manipulators assumes the use of ideal actuators to drive the joints;for that reason,in this work,a three-phase induction motor is considered to be a direct-drive actuator for each joint.An entire model of the mated system is obtained by a combination of the dynamics of the induction motor and robot manipulator.Thus,the synchronization control algorithm for a master-slave scheme in both the joint space and workspace of robot manipulators driven by induction motors is developed.An observer based on the entire model is proposed to estimate the joint velocity of the slave robot manipulators.Through the Lyapunov criterion,a stability analysis of the synchronization control with a velocity estimator is detailed.The analytical results show the synchronization and estimation errors are globally,uniformly,and ultimately bounded.Simulations with multiple robots demonstrate the performance of the proposed control algorithm.

The Low-Frequency Oscillation Restrain Method Research of Converter-Fed Multi-Phase Induction Motor Propulsion system

The inverter-fed induction motor drive system may become unstable at low frequencies and light load, and phase current and speed of the induction motor may oscillate periodically, which will threaten safety and reliability of the system. This paper chooses nine-phase induction motor simulated propulsion system as the research object, small disturbance model of three-phase induction motor is built, and average equivalent model of the converter is built by introducing switch function. On the basis above, small disturbance mathematic model of the whole system is obtained. As for the limitation of parameters adjustment method of restrain low-frequency oscillation, the restrain method combining current close-loop with dead-time compensation is put forward. Finally, the proposed restrain method is verified respectively on the built simulation and experimental analogue platform. And the simulation and experimental results indicate that the proposed method can not only satisfy the requirement of low-frequency oscillation restraining, but also be expanded widely, and the stability of the system can get improved greatly.

A Loss-model-based Efficiency Optimization Control Method for Induction Traction System of High-speed Train under Emergency Self-propelled Mode

Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.

Overview of Model Predictive Control for Induction Motor Drives

Model predictive control(MPC)has attracted widespread attention in both academic and industry communities due to its merits of intuitive concept,quick dynamic response,multi-variable control,ability to handle various nonlinear constraints,and so on.It is considered a powerful alternative to field oriented control(FOC)and direct torque control(DTC)in high performance AC motor drives.Compared to FOC,MPC eliminates the use of internal current control loops and modulation block,hence featuring very quick dynamic response.Compared to DTC,MPC uses a cost function rather than a heuristic switching table to select the best voltage vector,producing better steady state performance.In spite of the merits above,MPC also presents some drawbacks such as high computational burden,nontrivial weighting factor tuning,high sampling frequency,variable switching frequency,model/parameter dependence and relatively high steady ripples in torque and stator flux.This paper presents the state of the art of MPC in high performance induction motor(IM)drives,and in particular the progress on solving the drawbacks of conventional MPC.Finally,one of the improved MPC is compared to FOC to validate its superiority.It is shown that the improved MPC has great potential in the future high performance AC motor drives.

Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

The high-frequency(HF)modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system.In this study,a physics informed neural network-based HF modeling method,which has the merits of high accuracy,good versatility,and simple parameterization,is proposed.The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy.The per phase circuit structure is symmetric concerning its phase-start and phase-end points.This symmetry enables the proposed model to be applicable for both star-and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa.Motor physics knowledge,namely per-phase impedances,are used in the artificial neural network to obtain the values of the circuit elements.The parameterization can be easily implemented within a few minutes using a common personal computer(PC).Case studies verify the effectiveness of the proposed HF modeling method.

An MRAS method for sensorless control of induction motor over a wide speed range

This paper addresses the problem of wide speed range sensorless control of induction motor.The proposed method is based on model reference adaptive system (MRAS),in which the current model serves as the adjustable model,and a novel hybrid model integrating the modified voltage model (MVM) and high-frequency signal injection method (HFSIM) are established to serve as the reference model.The HFSIM works together with MVM to improve the performance of the rotor speed and rotor flux position estimation at low speed,whereas at high speed,the MVM acts alone.In addition,a rotor resistance online estimation scheme is proposed to update the rotor resistance contained in the adjustable model and to ensure the estimation accuracy further.Experimental results show that the proposed MRAS method is very effective from low to high speed range,including zero speed.

Adaptive Neuro Fuzzy Inference System Based Decoupled Control for Neutral Point Clamped Multi Level Inverter Fed Induction Motor Dri

The presence of an integrator in a reference model of a rotor flux-based model reference adaptive system(RF-MRAS)and non-linearity of the inverter in the output voltage degrade the speed response of the sensorless operation of the electric drive system in terms of DC drift,initial value issues,and inaccurate voltage acquisition.To improve the speed response,a compensating voltage component is supplemented by an amending integrator.The compensating voltage is a coalition of drift and offset voltages,and reduces DC drift and initial value issues.During low-speed operation,inaccurate voltage acquisition distorts the stator voltage critically,and it becomes considerable when the stator voltage of the machine is low.Implementing a three-level neutral point clamped inverter in speed-sensorless decoupled control of an induction motor improves the performance of the drive with superior quality of inverter output voltage.Further,the performance of the induction motor drive is improved by replacing the proportional-integral(PI)controller in the adaption mechanism of RF-MRAS with an adaptive neuro-fuzzy inference system(ANFIS)controller.A prototype model of the three-level neutral point clamped inverter(3L-NPC)-fed induction motor drive is fabricated in a laboratory,and its performance for a RF-MRAS,modified RFMRAS,and modified RFMRAS using ANFIS are compared using different benchmark tests.

Modular Approach for Investigation of the Dynamic Behavior of Three-Phase Induction Machine at Load Variation

In This paper, a modular approach for investigation of the dynamic behavior of three phase induction motor is developed and described in details. This model has been built up, systematically, by means of basic function blocks found with MATLAB/SIMULINK. This model is described in similar but modular approach as in electrical machines theory. The motor model includes multi-level blocks solving equations for each motor part or component. This approach enables the researcher to calculate or investigate any motor variables;voltage, current, flux, speed and torque. This model could also be used for a wide range of horse power needed in scientific research and numerical applications. A q-d axis based model is proposed to analyze the transient performance of three-phase squirrel cage induction motor using stationary reference frame. Constructional details of various sub-models for the induction motor are given and their implementation in SIMULINK is outlined. Direct-online starting under different load conditions of a 3 hp induction motor (as case study) is also studied. The motor stator voltage, the stator and rotor currents, the developed torque and rotor speed are, numerically, calculated and plotted for different operating conditions.

Zero-Sequence Current Suppression Strategy for Open-End Winding Permanent Magnet Synchronous Motor Based on Model Predictive Control

Compared with the traditional three-phase star connection winding,the open-end winding permanent magnet synchronous motor(OW-PMSM)system with a common direct current(DC)bus has a zero-sequence circuit,which makes the common-mode voltage and the back electromotive force(EMF)harmonic generated by the inverters produce the zero-sequence current in the zero-sequence circuit,and the zero-sequence current has great influence on the operation efficiency and stability of the motor control system.A zero-sequence current suppression strategy is presented based on model predictive current control for OW-PMSM.Through the mathematical model of OW-PMSM to establish the predictive model and the zero-sequence circuit model,the common-mode voltage under different voltage vector combinations is fully considered during vector selection and action time calculation.Then zero-sequence loop constraints are established,so as to suppress the zero-sequence current.In the end,the control strategy proposed in this paper is verified by simulation experiments.