Intelligent vector-frequency control system for asynchronous electric motors

The traditional direct torque control (DTC) of asynchronous motor has the disadvantages of the flux linkage, large torque ripple and instable switching frequency. To solve the above problems, a new scheme of modulating direct torque control system by adaptive fuzzy PI was put forward. According to the principle of fuzzy control, the regulator can perform the real-time optimization of PI parameters, realizing the good dynamic and static performance of system. In order to verify the feasibility and effectiveness of this scheme, this paper builds a simulation model of direct torque control system based on adaptive fuzzy PI control regulator by using MATLAB and Simulink. The simulation results show that compared with the traditional direct torque control system, the direct torque control system modulated by adaptive fuzzy PI has the merits of obvious reducing in flux and torque ripple, significant improvement on control performance.

To reduce traditional direct torque control (DTC) system low speed control precision and the large torque ripple in low speed, a fuzzy control system of DTC was proposed. On the basis of conventional PI regulator, a fuzzy speed PI regulator was designed according to speed error and its rate of change, which could adjust the proportional coefficient k <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf> and integral coefficient k <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</inf> dynamically to adapt the system to the speed variations, and advanced the self-adaptation of speed. In voltage vector fuzzy controller model, the stator flux angle, the stator flux error, and the torque error are reasonably fuzzified into several fuzzy subsets to optimize selection of the voltage vector and decrease the torque ripple. The experimental results show that the proposed fuzzy control system not only can ensure swift speed response, small overshooting, and high steady speed precision, but also can effectively decrease torque ripple in low speed. Additionally, the system improves the observation precision of the stator flux and enhances the robustness of the whole system.

In this paper, the torque ripple problem of six-phase asymmetrical brushless DC motor (BLDCM) is studied. First, the basic structure of BLDCM is introduced, and the operation principle of six-phase asymmetrical BLDCM that is studied in the thesis is expounded. Then, the principle of direct torque control (DTC) system of BLDCM is also discussed, and the improved system is proposed, including using the torque hysteresis loop and opening current hysteresis loop, and choosing the improved voltage vector to make the PWM-ON-PWM modulation. Finally, the DTC system simulation model is built, and the system is also tested by the experiment. According to the results of experiment and simulation, the DTC system designed in this thesis can control the six-phase asymmetrical BLDCM stably and reliably, and the problem of high frequency and torque ripple is solved well.

Direct Torque Control (DTC) is known to generate a fast and robust response in asynchronous engines. Yet, during steady state, observable flux, torque and current pulsations arise. This paper presents a study of modified direct torque control applied to a three-phase high performance asynchronous motor. The proposed strategy is based on PI regulators instead of the hysteresis comparators to control both the stator flux and torque whose parameters are determined from modulus and symmetrical optimum criterions. Since the performance of a feedback control system relies on the accuracy of the response signal, an estimator of stator flux and torque is presented. The control system benefits from the advantages of field oriented control (FOC) and conventional direct torque control (DTC) while avoiding some of the disadvantages of either of the two control methods. Performances of the asynchronous motor control are checked by simulations under MATLAB/SIMULINK software.

The study of algorithms switching voltage vectors, provides new possibilities in asynchronous motors with direct torque control. The article presents two methods of changing the angle of the voltage sector containing the voltage vector, in order to increase the speed of torque response and the flow of values, when the reverse is large or very small, will improve the quality of the control system. This will improve the quality of the electric drive at start-up and change the speed of the motor. At the same time, there are two new selector tables for flexible installers in the engine torque management options. The simulation result in Matlab ensures the quality of this method. The performance is shown in the stator stream, electromagnetic torque and in the speed of the motor in accordance with the set values.

To improve the performance of extra-low speed in direct torque control (DTC) system, this paper applies wavelet neural network (WNN) to constitute flux observer by deep researching nonlinear mathematic model of stator flux of asynchronous motor. Furthermore, in order to improve rapidity and real time characteristics of WNN flux observer, the paper applies ant colony algorithm (ACA) with embedded deterministic searching strategy to optimize dilation factor, translation factor and output weight of WNN. The paper compares this method with wavelet neural network flux observer optimized by gradient descent algorithm. Simulation shows that the former not only can reduce the node numbers of hidden layers and quicken the convergence rate of WNN, but also can improve on-line identification precision of flux observer, so it can effectively improve low speed performance of DTC system.

The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

Direct torque control (DTC) systems for open-end winding permanent magnet synchronous motors (OEW-PMSM) with common DC bus generate zero sequence currents (ZSC) and large torque ripple, resulting in increased system loss and poor operating characteristics. In this paper, a DTC based on five level torque hysteresis (FLTH) is proposed to improve the system performance. Firstly, an online calculation and selection strategy based on switch table is designed to suppress ZSC. By analyzing the composition of zero sequence voltage and using the double vector method to suppress it, the ZSC can totally be suppressed in theory, without affecting the system performance. On this basis, this paper proposes to add FLTH to DTC to reduce torque ripple. FLTH can not only effectively use many voltage vectors, but also reduce torque ripple. In the case study, the torque ripple rate has been reduced by 53%. Through simulation and experiment, the conventional DTC and the FLTH DTC are compared, and the results prove the validity of the proposed strategy.

In this paper, a direct torque and stator flux vector control system is presented. The principle of this method was proposed by Takahashi and Noguchi in 1985. In contrast to the field oriented control, no coordinate transformation and current control loop is required. In practical application, however, problems occur with starting and operation in the zero speed region. This paper shows how, by introducing an additional carrier signal to the torque controller input, a robust start and improved operation in the low speed region can be achieved. The simulation and experimental results which illustrate the performances of the proposed system are presented. Also, nomograms for controller design are given. >

To solve the strong randomicity and slow convergence of the Particle Swarm Optimization(PSO) algorithms, two new particle’s position renewal formulas were analyzed on the basis of extrapolation in mathematics. A new modified PSO algorithms (called Leading PSO algorithms) was put forward. The Direct Torque Control(DTC) System was built in the environment of Matlab(Simulink). The weight and threshold values of BP Neural Network were trained using the modified PSO algorithms. Some disadvantages such as slow convergence speed and easily plunging into the local solution were avoided effectively. The simulation result shows that the system works well, and the rotor speed identifier has great static and dynamic performance.

The electric motors and its control technology are key components of hybrid electric vehicles (HEVs). Control of the electric motor is a fundamental issue for traction application in electric vehicles and HEVs. This paper presents the design, development and implementation of a hybrid vehicle using both an electric motor and petrol engine to increase efficiency and decrease carbon footprint. Initially, a prototype of a HEV is designed and the performance values are calculated, before a control system is developed and implemented to control the DC motor speed using a microcontroller as the vehicle’s electronic control unit along with simple proportional integral derivative (PID) control using speed as a feedback mechanism. The prototype made incorporated voltage, current, speed and torque sensors for feedback resulting in a closed loop control system which successfully matched the speed input of a user-controlled pedal sensor. A user interface was developed to show the driver of the vehicle key variables such as the revolutions per minute (RPM) of the motor, the speed of the vehicle along with the current being drawn, and the voltage applied to the motor with overall power. To output a variable voltage from the Arduino, a digital output was used with pulse width modulation (PWM) capabilities in order to provide a variable DC voltage to the speed controller.

This paper presents a new solution, which can completely remove the DC offset and compensate the steady-state error for voltage model flux estimation in an induction motor (IM) direct torque control (DTC) system. The voltage model flux estimator has been paid more attention for its clear concept and simple signal processing, however, the integration drift associated with the inherent initial value error and DC offset input, especially in low speed region, can not be completely eliminated by the conventional low-pass-filter (LPF), in addition, LPF also brings steady-state amplitude and phase errors. Based on Bode plots analysis of some existing integrators, a new integrator with a first-order LPF and a high-pass-filter (HPF) in series is proposed to replace the pure integrator. The filters have adaptive cutoff frequency so as to suit various conditions. With the time phasor method, an error compensation formula is derived, which makes it simpler and easier for the new integrator to be applied to the digital control system. The new integrator with error compensation not only completely eliminates the integration drift, but also realizes errorless flux estimation in steady state. Both the simulation and experimental results on a prototype of 4kW IM DTC system show that the performance of the system especially in low speed region has been improved remarkably. This also verifies the effectiveness of the new integrator.

This paper propose a improved direct torque control(DTC) system for improving operation of five-phase squirrel-cage induction motor(IM). A five-phase IM drives present unique characteristics due to the additional degrees of freedom and also drives possess many others advantage compared with the traditional three-phase motor drive system, such as reducing a amplitude of torque pulsation and increasing the reliability. In order to maximize the torque per ampere, the proposed motor has concentrated windings and the produced back-electromotive force(EMF) is almost trapezoidal, and the motor is supplied with the combined sinusoidal plus third harmonic of currents, there is necessary to controlled 3rd harmonic current. Also a DTC method is advantageous when it is applied to the five-phase IM, because the five-phase inverter provides 32 space vectors in comparison to 8 space voltage vectors into the three-phase inverter drive system. For presenting the superior performance of the proposed DTC, experimental results of speed control are presented using a 32-bit fixed point TMS320F2812 DSP with 1.5[hp] IM.

This paper presents a modern control system for three phase high performance interior permanent magnet motor drives. The control system combines the advantages of vector control and direct torque control and overcomes some of the implementation drawbacks of either of the methods. The system uses a current control loop in connection with a switching table. A brain emotional learning based intelligent controller (BELBIC) is employed in the system which provides excellent performance under different operating conditions. BELBIC is based on the emotion processing mechanism in human's brain providing actions based on sensory inputs and emotional cues. A comprehensive evaluation of an IPM motor performance under the proposed control system proves the effectiveness of the system and its partial superiority over either vector control or direct torque control despite its relatively simple structure.

This paper proposes a variable speed wind generation system using a direct torque controlled interior permanent magnet synchronous generator. The proposed system has no wind speed and generator position sensors, and thus, it is considered that the proposed system has cost and reliability advantages. The proposed direct torque control (DTC) system in wind power generation has several advantages over conventional current control. First, DTC is well suited for the maximum power point tracking (MPPT) control that is implemented by controlling the generator torque. Second, the method of flux-weakening to maintain the terminal voltage at the limiting value of the converter is simple. Finally, a novel method is proposed for torque limiting, which makes it easy to maintain the armature current at the limiting value. The proposed method accomplishes current limiting using the reactive torque, which is calculated as the inner product of the flux and current. This does not require generator parameters such as magnet flux and inductances. Experimental results demonstrate the effectiveness of the proposed system using a wind turbine emulator instead of the actual wind turbine.