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.

Enhanced Fuzzy Logic Control Model and Sliding Mode Based on Field Oriented Control of Induction Motor

In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

LOW COST IMPLEMENTATION OF SPEED SENSORLESS INDUCTION MOTOR CONTROL USING STATOR FLUX ORIENTATION

The control platform of the induction motor （IM） with low costs is developed by using DSP MC56F8013 with a good performance/price rtaio. The control algorithm for the speed sensorless IM is studied based on the stator flux orientation （SFO）. The algorithm structure is simple to be implemented and cannot be influenced by motor parameters, The improved stator flux estimation is used to compensate errors caused by the low pass filter （LPF）. A new speed regulator is designed to ensure the system working with the maximal torque in the transient state. The system simulation and the prototype experiment are made. Results show that the con- trol system has good dynamic and static performance.

INDUCTION MOTOR SPEED CONTROL SYSTEM BASED ON FUZZY NEURAL NETWORK

A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teaching controller are described. The parameters of the membership function are regulated by an on-line learning algorithm. The speed responses of the system under the condition, where the target functions are chosen as I qs and ω, are analyzed. The system responses with the variant of parameter moment of inertial J, viscous coefficients B and torque constant K tare also analyzed. Simulation results show that the control scheme and the controller have the advantages of rapid speed response and good robustness.

Speed Sensorless Vector Control of Induction Motor Based on Reduced Order Extended Kalman Filter

A speed sensorless vector control system of induction motor with estimated rotor speed and rotor flux using a new reduced order extended Kalman filter is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm and good performance of speed control, and verify the usefulness of the proposed algorithm.

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.

Adaptive Gain Tuning Rule for Nonlinear Sliding-mode Speed Control of Encoderless Three-phase Permanent Magnet Assisted Synchronous Motor

In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor(PMa-Syn RM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-k W PMa-Syn RM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.

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.

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.

Linearizing Control of Induction Motor Based on Networked Control Systems

A new approach to speed control of induction motors is developed by introducing networked control systems （NCSs） into the induction motor driving system. The control strategy is to stabilize and track the rotor speed of the induction motor when the network time delay occurs in the transport medium of network data. First, a feedback linearization method is used to achieve input-output linearization and decoupling control of the induction motor driving system based on rotor flux model, and then the characteristic of network data is analyzed in terms of the inherent network time delay. A networked control model of an induction motor is established. The sufficient condition of asymptotic stability for the networked induction motor driving system is given, and the state feedback controller is obtained by solving the linear matrix inequalities （LMIs）. Simulation results verify the efficiency of the proposed scheme.

Vector control of induction motor based on fractional-order intelligent-integral speed controller

To improve dynamic and static performances and robustness of the induction motor speed control system based on vector control,an improved fractional-order intelligent proportional integral(IPIλ)controller was applied to the speed controller of the vector control system,which combined the intelligent fractional integral with the proportion according to the variation of deviation.Compared with proportional integral(PI)and fractional-order proportional integral(FOPI)controllers,the IPIλcontroller achieved better control performance.The stimulation results indicate that the IPIλcontroller can not only track the given speed quickly and accurately,but also have better anti-interference and robustness for load and parameters variations.

Wide speed range for traction motor in braking force of electric braking control system

A vehicle stopping method using an electric brake until a traction motor is stopped is studied. At the moment of vehicle stop, electric brake is changed to control mode where torque is reduced at a low speed. Gradient is controlled by estimating the load torque of motor, thereby traction motor is not rotated after stop. In addition, coasting operation and brake test are performed from normal-opposite operation and start using a small-scale model comprising the inertial load equipment and the power converter. Further, traction motor is made to be equipped with a suspension torque. Pure electric braking that makes traction motor stop by an air brake at the time of stop is also implemented. Constant torque range and constant power range are expanded during braking so that braking force is secured with the electric brakes even in high speed region. Therefore, vehicle reduction effect can be expected by reducing parts related with an air brake which is not used frequently by using a pure electric brake in the M car in wide speed region. Further, maintenance of brake system can be reduced. Besides, ride comfort of passenger in the electric rail car, energy efficiency improvement, and noise reduction effect can be additionally expected. Further, an improved brake method that uses only an electric brake till motor stop is proposed by comparing those in the blending brake that uses an air brake while reducing brake torque at vehicle stop.

Decoupling Control of 5 Degrees of Freedom Bearingless Induction Motors Using α-th Order Inverse System Method

A 5-degrees-of-freedom bearingless induction motor is a multi-variable,nonlinear and strong-coupled system．In order to achieve rotor suspension and operation steadily,it is necessary to realize dynamic decoupling control among torque and suspension forces．In the paper,a method based on α-th order inverse system theory is used to study dynamic decoupling control．Firstly,the working principles of a 3-degrees-of-freedom magnetic bearing and a 2-degrees-of-freedom bearinglees induction motor are analyzed, the radial-axial force equations of 3-degrees-of-freedom magnetic bearing,the electromagnetic torque equation and radial force equations of the 2-degrees-of-freedom bearingless induction motor are given,and then the state equations of the 5-degrees-of-freedom bearingless induction motor are set up．Secondly,the feasibility of decoupling control based on dynamic inverse theory is discussed in detail,and the state feedback linearization method is used to decouple and linearize the system．Finally,linear control system techniques are applied to these linearization subsystems to synthesize and simulate．The simulation results have shown that this kind of control strategy can realize dynamic decoupling control among torque and suspension forces of the 5-degrees-of-freedom bearingless induction motor,and that the control system has good dynamic and static performance．

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.

Virtual Speed Sensorless Desired Control Strategy of Maglev Single-sided Linear Induction Motors

单边短初级长次级直线感应电机己普遍应用于低速磁悬浮的驱动系统。由于在动态纵向边端效应影响下等效电路不对称，单边直线感应电机（single-sided linear inductionmotor，SLIM）的一些参数非线性变化。传统的应用于旋转电机的无速度传感器方法不再适用。首先分析了SLIM的M／T轴等效电路，选择次级磁链作为速度观测器状态变量。根据李雅普诺夫系统稳定性判据，推导出适用于SLIM的无速度传感器辨识；然后，采用反馈广义积分观测器控制稳态辨识速度的双幅脉振幅值；引入虚拟期望变量（virtualdesiredvariable，VDV）法，利用估算速度参与SLIM的恒滑差频率矢量控制。仿真与实验对所提控制算法的有效性和实用性进行了验证，所得结论可为磁悬浮的无速度传感器控制提供参考。

Nonlinear Control of an Induction Motor Using a Reduced-Order Extended Sliding Mode Observer for Rotor Flux and Speed Sensorless Estimation

This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.

High Performance Control of Matrix Converter Fed Induction Motor Drive System

Matrix converter fed motor drive is superior to pulse width modulation inverter drives since it not only provides bi-directional power flow,sinusoidal input/output currents,unity input power factor,but also allows a compact design due to the lack of DC-link capacitors for energy storage.In this paper,model and control of matrix converter fed induction motor drive system are analyzed.A combined control strategy is simplified and improved,which realizes space vector pulse width modulation of matrix converter and rotor flux oriented vector control technique for induction motor drive simultaneously.This control strategy combines the advantages of matrix converter with the good drive performance of vector control technique.Experimental results demonstrate the feasibility and effectiveness of the proposed control strategy.

Design and Development of a Vector Control System of Induction Motor Based on Dual CPU for Electric Vehicle

A vector control system for electric vehicle (EV) induction motor drive system is designed and developed. Its hardware system based on dual CPU(microcomputer 80C196KC and DSP TMS320F2407) is implemented. The fundamental mathematics equations of induction motor in the general synchronously rotating reference frame ( M T frame) used for vector control are achieved by coordinate transformation. Rotor flux equation and torque equation are deduced. According to these equations, an induction motor mathematical model and rotor flux observer model are built separately. The rotor flux field oriented vector control method is implemented based on these models in system software, some of the simulation results with Matab/Simulink are given. The simulation results show that the vector control system for EV induction motor drive system has better static and dynamic performance, and the rotor flux field oriented vector control method was practically verified.

Application of Diagonal Recurrent Neural Network toDC Motor Speed Control Systems

A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.