Rotor field oriented control strategy of multiphase induction motor

This paper introduces multiphase induction motor drives system under sensorless conditions, which is simulated and analyzed by utilizing its multiple control freedoms in the mode of high frequency signal injection. In this method, because nine phase induction motor have four orthogonal d-q planes compared to traditional three phase induction motor, so high harmonic plane can be used for other applications, for example, extracting rotor position based on high frequency injection signal technique. In the multiphase induction motor, inductance value is smaller in the high harmonic plane contrast to fundamental plane, in other words, it can get larger current signal amplitude under the same voltage amplitude, reducing the difficulty of the position signal extraction. changing rotor slot numbers will affect the air-gap length distribution, and it can be concluded that there is a saliency in the d 7 -q 7 plane through modulation of rotor slots. The module is simulated in the environment of simulink and ansoft.

In this paper, a control scheme for multiphase induction motor drives is presented and assessed. This control scheme ensures the operation of a multiphase drive under an open-circuit phase fault that can occur in one or more phases at the same time. A fault-tolerant control strategy is developed. The mathematical analysis is based on the space vector representation of the multiphase system and is valid either in transient or steady-state operating conditions. The feasibility of the drive is verified by means of experimental tests carried out on a prototype of seven-phase induction motor.

Rotor field oriented control strategy of multiphase induction motor

Control of high performance induction motors: theory and practice

In the recent days, for the traction and electric vehicle (EV) applications, multiphase machines with pole phase modulation (PPM) technique have been proposed. The smoother operation during pole changeovers as well as steady‐state operations is a significant constraint while adopting the PPM‐based multiphase induction motor (PPMIM) drives for EV and traction applications. So, in this paper, the PPMIM dynamic model and associated vector control are proposed for attaining a smoother operation of the machine. The machine modelling equations and transformation matrices are implemented in an arbitrary reference frame by considering the different pole phase combinations. Based on the modelling equations, the indirect field‐oriented control (IFOC) is proposed for PPMIM drives by reflecting the associated changes in parameters for different pole phase modes. In the IFOC, for regulating the d ‐axis and q‐ axis current components, single PI control loops have been implemented for all pole‐phase combinations. The proposed IFOC scheme is robust and applicable for adopting any type of pulse width modulation. The experimental, as well as simulation results, are given to illustrate the potentiality of the proposed dynamic model and IFOC. The PPMIM machine performance during the steady state as well as pole changeovers in different pole phase modes are analyzed and associated. Simulation and experimental results are presented.

In order to improve the operation performance of AC drive system, a combined control strategy for matrix converter fed induction motor drive system is proposed, which implements both space vector modulation of matrix converter and direct field oriented control of induction motor. Using this combined control strategy, it is possible to combine the advantages of matrix converter and the advantages of vector control technique and realize high performance control of induction motor. Applied with Matlab/Simulink, the simulation of the matrix converter with such strategy is carried out and the results of simulation are presented. Inductive load simulation is carried out on this matrix converter prototype. The simulation results verify the workability of the vector control strategy for matrix converter and the control performance of AC drive system is improved.

This research paper presents a novel method for the speed control of induction motors without using a speed sensor. The rotor speed can be accurately computed using an optimal control observer named the Kalman filter designed in this research paper. This replaces a speed sensor and eliminates the difficulty of the sensor installation in many applications. This research paper presents an advanced field oriented control of induction motors, based on a specific d-q coordinate model with the d-coordinate chosen to be in line with the rotor flux and the q-coordinate chosen to be 90⁰ lagging. The position of the rotor flux can be accurately computed using the Kalman filter. This eliminates the position sensors required accurately to monitor the flux. This research paper shows that as a result of this specific d-q transformation, the motor torque is proportional to the product of the rotor flux and the q-coordinate stator current. This significantly simplifies the induction motor control, such that the rotor flux is simply controlled by regulating the flux-related d-coordinates stator current and the motor torque is controlled just by regulating the q-coordinate stator current. This research paper presents a computational efficient recursive algorithm for Kalman filter which is specifically designed for the induction motor control. The Kalman filter provides the minimum variance state estimation and tolerates induction motor modelling and measurement errors. The Kalman filter can process all available measurements regardless of their precision (only two input current measurements required for the motor control), and provides a quick and optimal estimate of the variables of interest (the rotor speed and flux selected as outputs), as well as achieves a fast convergence. This research paper presents the digital signal processor (DSP) implementation of the field oriented control of induction motors using Kalman filter. The hardware requirements and all software modules are detailed. The experimental verification of the control method designed in this research paper is provided. Typical measurements are given to demonstrate the efficiency of the novel control presented in this research paper.

In recent years, AC induction motors have replaced DC motor. The most important reason for this is that DC motors have a mechanical brush and commutator system that is subject to wear and tear over time. While DC motor drivers need a lot of maintenance due to this system, induction motors do not require almost any maintenance since this system is not available. In recent years, technological advances in the field of multiphase induction motors have led to a significant evolution. A lot of research has been done around the world and a lot of new and interesting developments have been reported to the literature. This paper provides information about six-phase induction. In addition, what kind of advantages the concept of multiphase provides and how this structure is formed contains information about them. The six-phase induction motor will be simulated through the MATLAB/SIMULINK package program and compare with three phase induction motor. Both motors were run in simulation using the same parameters. At the end of the simulation, current, moment and speed graphs of the six-phase induction motor and three-phase induction motor will be drawn according to time. The study also included equations used during modeling and equivalent circuits belonging to a six-phase induction motor. It has been graphically shown that a six-phase induction motor is more advantageous than a three-phase motor. For example, in six-phase induction motors, the transition time to a continuous state is shorter. In addition, while the frequency of torque vibration increases, its amplitude decreases, the current value of each phase decreases, the stator copper losses are less than the three-phase induction motor. In motors, usually the power needed is divided by the number of phases. So the more phases there are, the greater the power carrying capacity. Today, multi-phase induction motor drives are used in special applications such as electric vehicles, space technology, aerospace applications, as moving power on ships, electric trains, which require high reliability and power.

Use of induction motor (IM) at it's highest efficiency is a big demanding task because of their complex mathematical model and non linear features during saturation. These elements make the control of IM strenuous and call for the use of high performance control algorithm such as field orientation control. This paper introduces a speed controller, particularly at minimum speeds by utilizing Fuzzy logic controller (FLC) for indirect field-oriented control (IFOC) of induction motor (IM) drives fed by a four-switch three-phase (FSTP) inverter. From suggested viewpoint, the IM drive is used with a FSTP inverter as an alternative for the conventional six-switch three-phase (SSTP) inverter. Utter IFOC programme includes the FLC of IM drives with the suggested FSTP inverter is raised in MATLAB/Simulink. By considering the good dynamic performance, cost minimization and low total harmonic distortion (THD), FSTP inverters are comparable with SSTP inverters. The dynamic performance and robustness of proposed FLC with the FSTP inverter fed IM drive is verified with PI controller. It is established that the suggested FLC is further powerful than the PI controller under speed tracking and load disturbances

This work compares the use of direct torque and flux control (DTFC) and model predictive control (MPC) for induction motor (IM) control. These two strategies are fundamentally different in operation since (i) DTFC decides the current control action based on a switching table constructed using a simplified model of the IM, whereas (ii) MPC decides the current control action by on-line minimization of a cost function that uses the available inverter output voltages as optimization variables. Emphasis is given in this work to the reconfiguration of the control action after voltage source inverter faults. We assume that the fault can be suitably detected and isolated and that the inverter can be reconfigured after the specific fault to continue operation, albeit with a reduced set of achievable output vectors. Based on this reduced set of vectors, we propose to reconfigure the induction motor control algorithm by (i) instructing DTFC to use a reconfigured switching table or (ii) providing the reduced set of inverter vectors as the reconfigured constraint set of optimization variables for MPC. Simulation results show that MPC considerably outperforms DTFC at a modest increment of computational cost. Moreover, this increment is less pronounced under fault since the number of optimization variables is reduced.

This paper displays a unique adaptable Neuro-Fuzzy Controller (NFC)-based speed control for three-phase induction motor drive. The suggested NFC integrates fuzzy logic idea with a four-layer Artificial Neural Network (ANN). Speed and change in speed are sent as input to Neuro-Fuzzy Controller and it winds up noticeably fit for real-time electromechanical drives. The complete simulation model for indirect vector control of induction motor including the suggested NFC is developed. Induction motor assumes an imperative part in the field of electric drives. Without genuine controlling of the speed, it is difficult to accomplish required errand for specific application. AC motors are solid, less cost, reliable, and maintenance free. In light of absence of capacity of regular control strategies like PID and PI controllers to work in a broad range of operations, AI-based controllers are extensively utilized as a part of the industry like Neural Networks, Fuzzy Logic, and Neuro-Fuzzy controller. The principle issue with the typical fuzzy-based controllers is that the parameters related with the membership functions and the rules depend predominantly on instinct of the specialists, fuzzy logic cannot naturally get the rules utilized for settling on the decision, however, great at clarifying the decision. To overcome from this issue, Neuro-Fuzzy Controller [ability to learn without anyone else alongside decision-making] is recommended. Keeping in mind the end goal to prove the predominance of the proposed Neuro-Fuzzy Controller, the results of the suggested NFC technique is compared with the results of PI controller. NFC-based control of induction motor will end up being more trustworthy than other conventional control techniques.

Induction motor is a cast of alternating current motor where charge endures allotted to the rotor close-at-hand deputation of conductive charge. These motors are broadly applied in industrial claim due to they are arduous along with adhere no contacts. The speed controller of deltoid phase induction motor is applied to alleviate the aberration of speed. The central constructivist of this paper is to accrue the performance of speed sensorless control of three phase induction motor. To increase its performance, this paper presents a modified method for speed controller of an indirect vector-controlled induction motor drive using cloud computing technique. Our methodology depends on speed sensorless scheme to obtain the speed signal feedback; the speed estimator is based on model reference adaptive control that uses the stator current and rotor flux as state variables for estimating the speed. In this method, the stator current error is represented as a function of first degree of the estimated speed error. An analysis and simulation of the tried algorithm is birthed and applied easing a TMS320C31 floating-point notational alert Processor. And accumulate the action of the three phase induction motor we conceived our appraisals affixed to the accountant based on cloud computing tactics. This intelligent policy uses the guidelines of the speed controller efficiently. Simulation and experimental results depicted that the motor speed is decelerated articulately to destine its illusion apprise without above and inferior smack and with about zero steady state error. The apprised accelerate alert and its dispatching buoy amassed off line from burlesque. After effects display an advantageous affinity among the accounted speed alert and it's dispatching allocated as well as aped speed flares.

The induction motor drive is simple in construction, rugged, safe, low-maintenance, and are variable speed motor drive but the cost has increased while making variable speed drive with use of modern control schemes. Therefore, researchers are discovering ways to reduce the cost while achieving variable speed control. One way is by getting rid of speed sensor in the motor shaft. It can reduce program complexity and improve reliability while minimizing the cost. The recent trend in the sensorless control of induction motor drive is to achieve successful reference tracking of estimated speed at low or zero speed. The vector control due to decoupled control of stator flux and rotor torque in induction motor is widely applied for speed control. In this paper, a sensorless vector control of induction motor with fuzzy-based rotor-flux MRAS topology is proposed. The fuzzy logic controller in the speed estimator block has achieved tremendous improvement in the speed estimation at low and even zero speed proving it to be superior to other sensorless control methods. The controller parameter calculation methods are also presented. The model is simulated in MATLAB/SIMULINK software. The results showed satisfactory improvement in the system performance especially at low or even zero speed.

The traditional V/f control method ignores the stator resistance and the leakage inductance voltage drop. And it is started according to the principle that the ratio of stator voltage to frequency is constant. But under low and intermediate frequency conditions, there is a large starting current and current oscillation during the startup process. In this paper, a E/f control method is proposed for a nine-phase induction motor. Based on the DSP + FPGA programming, the real electromotive force of the motor is fed back by the detection coil. According to the principle that the ratio of electromotive force to frequency is constant, the nine-phase induction motor is started by directly controlling the electromotive force. And the experiment proves that using this control method to start a nine-phase induction motor can effectively suppress starting current oscillation.

Conventional PI controller has overshoot effect at the transient period of the speed response curve. Most of the controllers of Induction Motor (IM) for industrial applications have been designed based on PI controller without consideration of core loss (CL) and stray load loss (SLL). In order to obtain the precise performance of torque as well as speed and flux, the mentioned losses should be considered for designing the control system. Conventionally, the gain of PI controllers is chosen by trial and error method which needs a lot of computational time. Fuzzy Logic Controller (FLC) is suitable for nonlinear system such as IM. In this paper, a FLC based speed controller is designed to control the speed of the IM taking CL and SLL into account. Simulations are carried out by using MATLAB/SIMULINK. The simulations result shows that the controller is capable to control the speed of IM without any overshoot and steady-state error effect.