Study on Rotor IGBT Chopper Control for Induction Motor Drive

Rotor chopper control is a simple and effective drive method for induction motor. This paper presents a novel IGBT chopper topology,which can both adjust rotor resistance and protect IGBT efficiently. Investigation on the quasi transient state of the rotor rectifying circuit is made, and a nonlinear mapping between the equivalent resistance and the duty cycle is deduced. Furthermore, the method for determining the magnitude of the external resistor is introduced.

Energy Efficient Control of Three-Phase Induction Motor Drive

Induction motors are extensively used in industrial and household appliances and consume more than 50% of the total generated electrical energy. The need for energy conservation is increasing the requirements for saving the electrical energy. It is therefore important to optimize the efficiency of electrical drive systems under certain operating conditions. This paper proposes a new control scheme based on search method taking advantage of the fact, that at a certain torque and speed (operating point) there is only one value of stator voltage that operates the motor at optimum efficiency. Simulation performed and results are presented.

A Digital Phase Locked Loop Speed Control of Three Phase Induction Motor Drive: Performances Analysis

This paper deals with performance analysis and implementation of a three phase inverter fed induction motor (IM) drive system. The closed loop control scheme of the drive utilizes the Digital Phase Locked Loop (DPLL). The DPLL is safely implemented all around the well known integrated circuit DPLL 4046. An ex-perimental verification is carried out on one kw scalar controlled IM system drives for a wide range of speeds and loads appliance. This presents a simple and high performance solution for industrial applications.

Implementation of Adaptive Neuro Fuzzy Inference System in Speed Control of Induction Motor Drives

A new speed control approach based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to a closed-loop, variable speed induction motor (IM) drive is proposed in this paper. ANFIS provides a nonlinear modeling of motor drive system and the motor speed can accurately track the reference signal. ANFIS has the advantages of employing expert knowledge from the fuzzy inference system and the learning capability of neural networks. The various functional blocks of the system which govern the system behavior for small variations about the operating point are derived, and the transient responses are presented. The proposed (ANFIS) controller is compared with PI controller by computer simulation through the MATLAB/SIMULINK software. The obtained results demonstrate the effectiveness of the proposed control scheme.

Modern Multilevel Control Technique Used in Electric and Hybrid Drive System with Induction Motors

The mathematical model of the modem induction traction motor （TRIM and cutting magnetic circuit traction motor）, supplied with IPM inverter with different control technique is presented in the paper. In electric and hybrid vehicle are applied： FLMC （Fuzzy Logic Mode Control）, SLMC （Sliding Mode Control）, NRMC （Neural Regulator Control）, and Direct Power and Torque Control for Space Vector Modulated inverter （DPTC SVM）. In the special solution of the electric and hybrid vehicle are also applied a Random Switching Frequency Modulation. The control of hybrid vehicle should assure the realization of established transport-assignments in the definite time, at the optimum of energy consumption. One can this realize using. The multi criteria control system. Some results of the computer simulations are presented in the paper. Results of numerical calculation were verified for laboratory model of the electric and hybrid wheel vehicles traction motor.

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.

Microcontroller-Based Variable Speed Drive for Three-Phase Induction Motor in Cooling Applications

This paper presents an electronic VSD （variable speed drive） for three-phase IM （induction motor） using a microcontroller. The VSD is designed for cooling applications where the 1M is coupled to a cooling fan. The drive receives temperature feedback from objects to be cooled and output a corresponding frequency to the IM. A prototype of the VSD is constructed to control a 175 W, four pole, squirrel cage three-phase IM. The heart of the control circuit is a low-cost microchip＇s PICI6F777 microcontroller which is programmed using C language to generate variable frequency SPWM （sinusoidal pulse width modulation） switching signals. These switching signals are fed to an 1GBT inverter. The VSD constructed can be switched between two modes of speed control＂ automatic temperature-controlled mode and manual user-controlled mode. Cost savings using the prototype are demonstrated.

Three-level inverter configuration with common mode voltage elimination for induction motor drive (To continue)

The multiplicity of vector combinations for vectors of combined three-level inverters plays an important role, when deciding on the modulation scheme, to obtain minimum switching per inverter vector change, as described in the next Section. This is not possible with reduced common-mode three-level inverter structure, obtained with a five-level cascaded H-bridge configuration, as the space vectors locations do not exhibit multiplicity. Moreover, the proposed configuration requires only two power supplies, whereas the scheme with the five-level H-bridge configuration requires six isolated power supplies.

Three-level inverter configuration with common mode voltage elimination for induction motor drive

The multiplicity of vector combinations for vectors of combined three-level inverters plays an important role, when deciding on the modulation scheme, to obtain minimum switching per inverter vector change, as described in the next Section. This is not possible with reduced common-mode three-level inverter structure, obtained with a five-level cascaded H-bridge configuration, as the space vectors locations do not exhibit multiplicity. Moreover, the proposed configuration requires only two power supplies, whereas the scheme with the five-level H-bridge configuration requires six isolated power supplies.

Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor

This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.

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.

Sensorless Vector Control of Parallel-Connected Multiple Induction Motors Fed by a Single Inverter

A method of improving the stability of multiple-motor drive system fed by a 3-leg single inverter has been devised that employs the averages and differences of estimated parameters for field-oriented control. The parameters of each motor (stator current, rotor flux, and speed) are estimated using adaptive rotor flux observers to achieve sensorless control. The validity and effective of the proposed method have been demonstrated through simulations and experiments.

An Approximate High Gain Observer for Speed-sensorless Estimation of Induction Motors

Rotor speed estimation for induction motors is a key problem in speed-sensorless motor drives. This paper performs nonlinear high gain observer design based on the full-order model of the induction motor. Such an effort appears nontrivial due to the fact that the full-model at best admits locally a non-triangular observable form(NTOF), and its analytical representation in the NTOF can not be obtained. This paper proposes an approximate high gain estimation algorithm, which enjoys a constructive design, ease of tuning, and improved speed estimation and tracking performance. Experiments demonstrate the effectiveness of the proposed algorithm.

Sensorless Vector Control of Induction Generators for Variable-Speed Wind Turbines Using Micro-2407

A sensorless vector-control strategy for an induction generator in a grid-connected wind energy conversion system is presented. The sensorless control system is based on a model reference adaptive system (MRAS) to estimate the rotational speed. In order to tune the MRAS observer and compensate for the parameter variation and uncertainties, a separate estimation of the speed is obtained from the rotor slot harmonics using an algorithm for spectral analysis. This algorithm can track fast dynamic changes in the rotational speed, with high accuracy. Two back to back pulse width modulated (PWM) inverters are used to interface the induction generator with the grid. The front-end converter is also vector controlled. The dc link voltage is regulated using a PI fuzzy controller. The proposed sensorless control strategy has been experimentally verified on a 2.5-kW experimentally set up with an induction generator driven by a wind turbine emulator. The emulation of the wind turbine is performed using a novel strategy that allows the emulation of high-order wind turbine models, preserving all of the dynamic characteristics. The experimental results show the high level of performance obtained with the proposed sensorless vector-control method.

SINAMICS—the high efficiency drive technology for rolling mills

In the Metals Industry,interruption-free processes to produce high-quality end products are a prerequisite. The main drives together with the mill stands play a key role in the success of rolling mills.The crucial demands placed on the drive system are:high-dynamic performance of drive and its control system,ability to handle the process related overloads,smooth running,high availability,high efficiency,easy serviceability and ability to integrate seamlessly with the automation systems.With numerous reference installations and many years of experience Siemens VAI has the wider expertise and the portfolio to provide the right drive for every application. This paper examines the latest innovation,SINAMICS drive technology,for both new drive applications as well as for modernizing the existing drives in rolling mill applications like hot strips mills,plate mills,cold rolling mills,and long rolling mills.

Modified Sliding Mode Observer-based Direct Torque Control of Six-phase Asymmetric Induction Motor Drive

In this study,a six-phase induction asymmetric induction motor(SPAIM)was examined,whose performance surpasses that of its three-phase counterpart,with regard to the torque density,torque pulsation,fault tolerance,power rating per inverter lag,and noise characteristics.Speed-encoder-less direct torque control(DTC)for SPAIM with virtual voltage vectors(VVVs)and a modified sliding mode observer(MSMO)are described.The SPAIM model was developed using a stationaryα-βframe for DTC.The conventional DTC of the SPAIM drive is a simple extension of DTC for a 3-Φmotor drive that yields higher distortion in the stator currents.To mitigate the large amount of distortion in the stator current,VVVs were used to significantly reduce the harmonic content in the stator currents.Furthermore,to overcome the large amount of chattering observed in the case of a traditional sliding mode observer,particularly under low-speed operation,the MSMO was employed to reduce chattering even under low-speed operation.The performance of the proposed observer was verified under all the operating conditions suitable for the propulsion mode of an electric vehicle using Matlab/Simulink,and the results were experimentally validated.

考虑逆变器谐波耦合的牵引传动系统机电耦合振动特性研究

作为牵引传动系统能量转换的关键部件,牵引电机在电气激励作用下会受到各种冲击载荷和周期激振力的作用,从而产生机电耦合振动,威胁牵引传动系统的可靠运行。对此,基于双惯量模型对牵引传动系统机电耦合振动特性开展研究。首先,建立牵引电机的双惯量模型,依据此模型对其固有频率进行计算,并介绍了机械传动系统的同频受迫振动模态。其次,根据逆变器的开关特性,着重分析了脉宽调制(PWM)导致的边带谐波转矩对机电耦合同频共振的影响,探索逆变器的频率耦合产生的间谐波对机电耦合系统的影响。接着,以传递函数的形式对考虑双惯量负载的牵引传动系统进行建模,从频域角度对系统机电耦合共振特性进行理论分析。最后,利用硬件在环测试对所分析结果进行验证。

间接矩阵变换器-双异步电机调速系统的模型预测控制权重因数整定

间接矩阵变换器-双异步电机调速系统结构复杂,传统模型预测电压控制中权重因数整定困难。该文提出一种基于层次分析评估的权重因数整定方法,通过对物理量纲、双电机、网侧与电机侧统合将权重因数数量减少至1个,并引入层次分析评估法来实时调整权重因数以满足各种工况的要求,使系统在宽运行范围、多功率流模态下均具有良好的网侧电能质量与电机调速性能。通过仿真和实验证明,采用该文提出的方法,可保证在多种工况下网侧功率因数接近1,网侧电流正弦,电机定子电流畸变小、电机动态调速性能良好。而且,相比于传统的简化模型预测电压控制方法,该文所提出的方法权重因数整定简单易实现,网侧电流质量更好。

Robust Predictive Current Control of Induction Motors Based on Linear Extended State Observer

Model predictive current control can achieve fast dynamic response and satisfactory steady-state performance for induction motor(IM)drives.However,many motor parameters are required to implement the control algorithm.Consequently,if the motor parameters used in the controller are not accurate,the performance may deteriorate.In this paper,a new robust predictive current control is proposed to improve robustness against parameter mismatches.The proposed method employs an ultra-local model to replace the mathematical model of the IM.Additionally,to improve the control performance,a linear extended state observer is developed for disturbance estimation.Experimental tests confirm that satisfactory tracking performance can still be obtained although the motor parameters may not be accurately set in the controller.

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.