Low Speed Performance Operation of Induction Motors Drives Using Low-Resolution Speed Sensor

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.

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 paper proposes a propulsion control algorithm considering End-effect of a linear induction motor (LIM) used in a magnetic levitation train. Indirect field oriented control (IFOC) technique is one of the popular control techniques widely applied to LIM drive control. The main idea of IFOC in a LIM is the decoupling of the flux and torque. Therefore, IFOC has a higher dynamic characteristic than the scalar control [1]. The LIM applied to the magnetic levitation trains should control the thrust force and also take into account the normal force for levitation stabilization. When the LIM is driven, normal force is inevitable. The normal force is a function of the speed, the slip frequency and the current of the train. In the rotary type induction motor, the normal force is canceled due to its symmetrical structure. Therefore, IM could operate in a low slip and high efficiency range. However, in the case of LIM, a high attraction force is generated in a low slip region, which cause the instability of the levitation system. Therefore, the propulsion control for magnetic levitation trains must operate in a higher slip region than the slip used in conventional IFOC. In this paper, the slip characteristics of the LIM are analyzed to improve the efficiency and safety of the magnetic levitation train by FEM analysis. A constant slip frequency propulsion control algorithm is proposed for operation in the analyzed slip region. The proposed algorithm can be controlled by separating magnetic flux and thrust from IFOC. The proposed algorithm is verified in 250 kW test bench. The results of FEM analysis according to speed and slip at constant voltage condition are shown on Fig. 1. The dotted lines of Indirect Field Oriented Control(IFOC) and Constant Slip Indirect Field Oriented Control(CSIFOC) are shown on the figure. The slip of the IFOC is low and that leads to operate near the maximum thrust and efficiency. However, the normal force of LIM is also increase, which could not be allowed in maglev application. On the other hand, when CSIFOC is performed considering normal force, the slip is higher than the conventional algorithm. Although the CSIFOC is not operated in maximum thrust slip, the normal force could be greatly reduced. Fig.2 (a) shows the CSIFOC algorithm considering the end-effect of the linear induction motor. In general IFOC, the d-axis current reference is calculated through the magnetic flux reference value, and the q-axis is calculated based on thrust. However, the CSIFOC for the LIM generates the d-axis and q-axis current references along with the slip frequency and thrust. Fig. 2 (b) shows the waveform of the experimental results based on the general IFOC and the proposed algorithm. Both IFOC and CSIFOC were tested with the same rate pattern of the same load. It is confirmed that CSIVC has larger slip than conventional IFOC and low normal force in all regions. In this paper, a constant slip frequency IFOC algorithm is proposed considering the end effect of LIM used for magnetic levitation trains. The efficiency, thrust and normal force according to the speed and slip through the FEM analysis of the LIM were analyzed and the slip condition suitable for the magnetic levitation train is proposed. In addition, a current reference generation algorithm based on the thrust and slip is proposed in the IFOC considering the end effect to operate under the proposed slip condition. In the full paper, the detailed formulas of the proposed algorithm are developed and will be verified through simulation and experimental results.

Indirect vector control or Indirect Field Oriented Control (IFOC) is known to produce high performance in induction Motor (IM) drives by decoupling rotor flux and torque producing current components of stator current. The most commonly used controller for the vector control of ac motor is Proportional- Integral (P-I) controller. However, the P-I controller has some disadvantages such as high starting overshoot, sensitivity to controller gains and sluggish response to sudden disturbances. So, the Integral-Proportional (I-P) controller is proposed as speed controller for induction motor drives to overcome the disadvantages of the P-I controller. Simulation results are presented and analyzed for both the controllers and it is observed that Integral-Proportional (I-P) controllers give better responses than the traditional P-I controllers for the Indirect Field Oriented Control (IFOC) of ac motor drives.

Speed Tracking of Indirect Field Oriented Control Induction Motor Using Neural Network

Induction Motor in Electrical drive system at a accelleration speed for example in electric cars have a hard speed setting is set on a wide range, causing an inconvenience for motorists and a fast response is required any change of speed. It is necessary for good system performance in control motor speed and torque at low speed or fast speed response, which is operated by Indirect Field Oriented Control (IFOC). Speed control on IFOC methods should be better to improving the performance of rapid response in the induction motor. In this paper presented a method of incorporation of Fuzzy Logic Controller and Backstepping (Fuzzy-Backstepping) to improve the dynamically response speed and torque in Induction Motor on electric car, so we get smoothness at any speed change and braking as well as maximum torque of induction motor. Test results showed that Fuzzy-Backstepping can increase the response to changes speed in electric car. System testing is done with variations of the reference point setting speed control system, the simulation results of the research showed that the IFOC method is not perfect in terms of induction motor speed regulation if it’s not use speed control. Fuzzy-Backstepping control is needed which can improve the response of output, so that the induction motor has a good performance, small oscillations when start working up to speed reference.Keywords: Fuzzy-Backstepping, IFOC, induction motor

This paper presents the use of local sensitivity analysis techniques to study which output signal of several proposed in the literature can lead to better performance of on-line tuning for rotor time constant variations using model reference adaptive control (MRAC) in indirect field oriented control (IFOC) of induction motors. The expectation is that the output with the highest sensitivity to rotor time constant should be the more suitable for IFOC controller MRAC tuning. We derive the output relative sensitivity functions for steady state operation for active power, reactive power, electromagnetic torque, and the ratio of reactive power and torque to rotor time constant and study their variability as a function of slip frequency. The relative sensitivity functions are used to study their usefulness for rotor time constant tuning. No signal can give uniform satisfactory sensitivity properties over the full range of machine operation. Suggestions are given on how to tackle this issue.

The speed control of induction motors can be divided into two distinct strategies, depending on the type of dynamics that is required: scalar control (static control of the torque) and vector control (dynamic control of the torque) (Blaabjerg et al. 2005; Bose, 2000, 2006; Filote et al. 2009; Holtz, 2002; Leonhard, 1990; Umanand & Bhat, 1995; Vas, 1998). Since the couple and flux levels depend on the motor behavior to frequency and voltage applied to it, maintaining the flux constant is strongly required in scalar control (V/f control). Despite the simplicity and the low cost implementation of the control method, it still presents the disadvantage of poor torque dynamics. Vector control reassesses one of the advantages of direct current (dc) drives, which is the separation of speed and couple loops. According to its structure and to its own functioning principle, the dc drive is naturally field oriented, hence, the separation of the speed and current loops. In the case of vector controllers of induction motor, the magnitude and phase stator current are controlled in accordance with the flux vector. There are three vector control strategies according to the type of drive-controlled flux: stator flux, rotor flux and air gap flux. We can determine the magnitude and position of the rotor flux by using flux sensors (direct field-oriented control), estimators or observers (indirect field-oriented control) and by measuring some electrical and mechanical measurable states of electrical drives induction motor systems. When the rotor flux estimation is performed after measuring only the electrical measurable states (voltages and stator currents), in this case we have a sensorless vector control system. The implementation of the direct field-oriented control requires the measurement or calculation of the flux space vector (magnitude and position). The measurement of the air gap flux requires the use of some Hall sensors (Umanand & Bhat, 1995), which requires specially constructed induction motor. On one hand, they are very sensitive to temperature and mechanical vibrations. The flux signal is highly distorted by slot harmonics (Kreindler, 1994), whose spectrum and amplitude depend on the rotor speed (hence, the difficulty to be filtered). The implementation of the indirect field-oriented control requires the identification of rotor flux instantaneous position, and the calculus of stator current prescribed value in sensorless vector control system (Gadue et. al. 2009; Griva et al. 1997; Lascu et al. 2004). The

In this paper, a new approach has been proposed to control induction motor drives using a PI controller. The induction motor drive system is fed by a current-controlled voltage source inverter (VSI) and indirect field oriented control (IFOC) method has been used to control the three-phase command currents. During simulation proccess, the stator three-phase real currents are sensed from sensors inside the motor and regulated by hystersis controllers with comparison of the command currents obtained from the block proceeding the IFOC. The PI controller presented in this paper, has improved stability of the induction motor drive effectively. A neural network has been designed as a numerical controller to replace the original PI based cotroller to verify the results gained from the simulink.

In this chapter, a method is studied to estimate the rotor resistance for indirect field-oriented control (IFOC) of induction motor drive. In model reference adaptive system (MRAS)-based sensorless speed estimation techniques, usually, the rotor speed estimation is achieved by assuming the rotor resistance to remain unchanged during the operation. However, in practice, the rotor resistance of the motor varies with time depending on the drive’s temperature. This variation in rotor resistance accounts for error in the estimation of the rotor speed of the sensorless MRAS scheme-based induction motor speed estimator. To minimize this error caused due to rotor resistance variation, a rotor resistance estimation method is provided. To verify the feasibility and accuracy of the given method, a three-phase induction motor is being used. From the simulation results obtained, it can be observed that the proposed method provides an accurate estimation of rotor resistance, and simultaneous rotor speed estimation is achieved with lesser effects of rotor resistance variation.

A fuzzy self-tuning hybrid fuzzy controller for indirect field oriented control (IFOC) induction motor drives will be presented in this paper. The developed hybrid fuzzy control law consists of proportional-integral (PI) control at steady state, PI-type fuzzy logic control (FLC) at transient state, a simple switching mechanism between steady and transient states, and fuzzy self-tuning for tuning of their coefficients to have high performance and robustness drive under steady and transient conditions. The importance of the presented hybrid fuzzy controller will be highlighted by comparing the performance of fuzzy self-tuning hybrid fuzzy controller with PI controller, for IFOC induction motor drives. It will be displayed that the presented induction motor drive has both less steady state error and better behavior in transient state; moreover, it is robust to load disturbance, the inertia variation, and robust to rotor resistance variation. Simulation results will be presented confirming the above-mentioned claims.

This paper is dedicated to exploring real-time parameter identification approaches and their integration with deadbeat-direct torque and flux control (DB-DTFC) without additional torque ripple. Using the voltage model at medium- and high-speed ranges, DB-DTFC is insensitive to parameters. Performance degrades at low speeds with the rotor time constant errors, because the current model is utilized for flux linkage estimation. Two different real-time parameter estimation approaches are developed, including a flux observer-based model reference adaptive system (MRAS) and a pulsating flux injection-based method. Both are experimentally evaluated for how well they mitigate DB-DTFC performance degradation at low speed. For the MRAS-based method, the fundamental components are used for parameter convergence, which does not induce additional torque ripple. For the injection-based method, traditional d -axis pulsating voltage vector injection used in indirect field-oriented control (IFOC) yields significant torque ripple, particularly at high speed. The proposed pulsating flux injection scheme used in DB-DTFC excites the same magnitude of current harmonics and induces no additional torque ripple over a wide speed range.

In order to eliminate the effect of parameter variation on field-oriented control for induction motor drive, an adaptation algorithm for tuning the rotor time-constant is proposed. Based on the adaptive observation of the rotor flux linkages, the rotor time-constant is adapted to obtain an exact indirect-field-oriented control (IFOC). In this proposed algorithm, a related function to the variation of the rotor time-constant is designed, then the accurate slip frequency needed for IFOC is obtained from this error function through a PI-type (proportional-integral) filter. Furthermore, a novel variable structure speed control with integral sliding surface is proposed under the adaptive field-oriented operation. By means of the variable structure speed control, the dynamics of motor speed have the property of an exponentially convergent rate. Using the proposed adaptive field-oriented control and the variable structure speed control, the IFOC is robust to the variation of the rotor time-constant and the speed control is insensitive to parameter uncertainty and load disturbance. Finally, some simulation and experimental results are presented to validate the effectiveness.

Rotor flux oriented field orientation control of induction motor without a speed sensor has been the research topic for quite a few years because of various advantages. However, the estimation rotor flux in the low speed range is difficult and motor parameter dependent. The stator resistance variation can cause error in stator and rotor flux calculation especially in the low speed region. In this paper an effective and simple fuzzy-logic based technique is proposed by which the stator resistance can be easily computed online for improvement of the drive performance in the low sped region. This method id simple effective and can be easily implemented with a micro controller or a DSP based system and needs no external signal injection. The simulation results and some experiments very much validate the proposed concept

The multiphase motors due to their reliability find new areas of application in the industry and transportation. Developing of any system with multiphase motors at first requires elaborate model of the system, define control mode and controllers. The model of control system for the sixphase drive is based on its conventional d-q mathematical model and indirect field-oriented control. Simulink model of six-phase drive with indirect field-oriented control and simulated with two types PID and PID fuzzy controllers. The simulation results, reflecting step response and provided speed reference law as well as load application at constant speed, are presented and analyzed. Fuzzy controller with 49 rules is considered and applied. Six-phase electric drive with field-oriented control at well-tuned PID controller has good step response specifications: settling time 0.13 s at starting without load, step response has no overshoot, small about 1% short time decrease of speed at load of 5 Nm application. The system employing PID fuzzy controller shows slightly better results in response to torque application: the decrease in speed 1% is eliminated in shorter time. Simulation results indicate the robustness of both systems with six-phase drive to disturbance and provide high quality transient specifications at provided reference speed.