Performance and Safety Improvement of Induction Motors based on Testing and Evaluation Standards

The induction motor,which converts electrical energy into mechanical energy,has been recognized as the cornerstone of industrialization.The rotor of an induction motor can be either a squirrel cage rotor or a wound-type rotor,both existing as magnetless topologies.Three-phase squirrel cage induction motors are frequently utilized in industrial drives because they are dependable,have high starting torque,are selfstarting and affordable.Single-phase induction motors,on the other hand,are commonly used for small loads such as domestic appliances in form of modest fans,pumps and electric power tools.In South Africa,there have been reports of fires and explosions resulting in live and property loss because of induction motors that have not been thoroughly tested or are incorrectly labelled in terms of ratings,electrical safety and performance.The goal of this study is targeted at preventing end-user injuries and failures caused by non-compliant induction motors,by evaluating locally manufactured/imported induction motors based on tests and evaluation from standards(IEC and SANS).The study is conducted using experimental procedures at the Explosion Prevention Technology and Rotating Machines(EPT and RM)laboratory,South African Bureau of Standards(SABS),South Africa.The main finding from the study shows differences in the nameplate characteristics of various induction motors which could have detrimental effects such as production and operational downtime in their end-use industries,at later stages.

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.

Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors

Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control.

Fault Diagnosis of Industrial Motors with Extremely Similar Thermal Images Based on Deep Learning-Related Classification Approaches

Induction motors(IMs)typically fail due to the rate of stator short-circuits.Because of the similarity of the thermal images produced by various instances of short-circuit and the minor interclass distinctions between categories,non-destructive fault detection is universally perceived as a difficult issue.This paper adopts the deep learning model combined with feature fusion methods based on the image’s low-level features with higher resolution and more position and details and high-level features with more semantic information to develop a high-accuracy classification-detection approach for the fault diagnosis of IMs.Based on the publicly available thermal images(IRT)dataset related to condition monitoring of electrical equipment-IMs,the proposed approach outperforms the highest training accuracy,validation accuracy,and testing accuracy,i.e.,99%,100%,and 94%,respectively,compared with 8 benchmark approaches based on deep learning models and 3 existing approaches in the literature for 11-class IMs faults.Even the training loss,validation loss,and testing loss of the eleven deployed deep learning models meet industry standards.

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.

Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors

Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller.

TWO DOF POSITIONING STAGE USING LINEAR ULTRASONIC MOTORS

A two degrees of freedom （DOF） positioning stage using novel linear ultrasonic motors is presented. The stage mainly consists of two linear ultrasonic motors, linear guides and tables. It can realize the long stroke and reversible controlled motion in two directions. The wheel-shape linear ultrasonic motor applied in the stage utilizes two fourth-bending modes of non-uniform beam in orthogonal directions. Quick response, no backlash, high resolution, power-off self-braking, and long stroke are the attractive characteristics of the linear positioning stage. Experimental results show that z and y-direction tables can reach the destination without overshoot and the error is less than 2μm by using two linear encoders with a resolution of 1 μm. In the open-loop mode, the positioning stage achieves 1μm resolution at 0. 25 ms driving time.

ELLIPTIC MOTIONS ON MODAL CONVERSION ULTRASONIC MOTORS

The forming of elliptic motions on the modal conversion ultrasonic motors （MCUMs） is discussed. The principles of the modal conversion are investigated based on the coupling with the stator and the rotor, and using an independent coupler. The elliptical locus observed on the longitudinal-torslonal vibration converter with oblique slits is analyzed by using vibration theory. A method for the modal conversion is proposed by using the local mode of a substructure On a main structure. The method can be used to design the modal conversion type ultrasonic motors.

Controller Design for Induction and Brushless Motors Using Matlab with Digital Signal Processor (DSP)

The automation process is a very important pillar for Industry 4.0.One of the first steps is the control of motors to improve production efficiency and generate energy savings.In mass production industries,techniques such as digital signal processing(DSP)systems are implemented to control motors.These systems are efficient but very expensive for certain applications.From this arises the need for a controller capable of handling AC and DC motors that improves efficiency and maintains low energy consumption.This project presents the design of an adaptive control system for brushless AC induction and DC motors,which is functional to any type of plant in the industry.The design was possible by implementing Matlab software and tools such as digital signal processor(DSP)and Simulink.Through an extensive investigation of the state of the art,three models needed to represent the control system have been specified.The first model for the AC motor,the second for the DC motor and the third for the DSP control;this is done in this way so that the probability of failure is lower.Subsequently,these models have been programmed in Simulink,integrating the three main models into one.In this way,the design of a controller for use in AC induction motors,specifically squirrel cage and brushless DC motors,has been achieved.The final model represents a response time of 0.25 seconds,which is optimal for this type of application,where response times of 2e-3 to 3 seconds are expected.

Speed Control of Travelling Wave Type Ultrasonic Motors Using Artificial Neural Network

Ultrasonic motor (USM) is a newly developed motor, and it has some excellent performances and useful features, therefore, it has been expected to be of practical use. However, the driving principle of USM is different from that of other electromagnetic type motors, and the mathematical model is complex to apply to motor control. Furthermore, the speed characteristics of the motor have heavy nonlinearity and vary with driving conditions. Hence, the precise speed control of USM is generally difficult. This paper proposes a new speed control scheme for USM using an artificial neural network. An accurate tracking response can be obtained by random initialization of the weights of the network owing to the powerful on line learning capability. Two prototype ultrasonic motors of travelling wave type were fabricated, both having 100 mm outer diameters of stator and piezoelectric ceramic. The usefulness and validity of the proposed control scheme are examined in experiments.

Impulsive control of permanent magnet synchronous motors with parameters uncertainties

The permanent magnet synchronous motors （PMSMs） may have chaotic behaviours for the uncertain values of parameters or under certain working conditions, which threatens the secure and stable operation of motor-driven. It is important to study methods of controlling or suppressing chaos in PMSMs. In this paper, robust stabilities of PMSM with parameter uncertainties are investigated. After the uncertain matrices which represent the variable system parameters are formulated through matrix analysis, a novel asymptotical stability criterion is established. Some illustrated examples are also given to show the effectiveness of the obtained results.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

Current research in broken rotor bar （BRB） fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estima- tion cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the fre- quencies of the fundamental and fault characteristic com- ponents with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Comparison of Two Novel MRAS Based Strategies for Identifying Parameters in Permanent Magnet Synchronous Motors

Two model reference adaptive system （MRAS） estimators are developed for identifying the parameters of permanent magnet synchronous motors （PMSM） based on the Lyapunov stability theorem and the Popov stability criterion, respectively. The proposed estimators only need online measurement of currents, voltages, and rotor speed to effectively estimate stator resistance, inductance, and rotor flux-linkage simultaneously. The performance of the estimators is compared and verified through simulations and experiments, which show that the two estimators are simple, have good robustness against parameter variation, and are accurate in parameter tracking. However, the estimator based on the Popov stability criterion, which can overcome parameter variation in a practical system, is superior in terms of response speed and convergence speed since there are both proportional and integral units in the estimator, in contrast to only one integral unit in the estimator based on the Lyapunov stability theorem. In addition, the estimator based on the Popov stability criterion does not need the expertise that is required in designing a Lyapunov function.

IBPSO-Based MUSIC Algorithm for Broken Rotor Bars Fault Detection of Induction Motors

In spectrum analysis of induction motor current, the characteristic components of broken rotor bars（BRB） fault are often submerged by the fundamental component. Although many detection methods have been proposed for this problem, the frequency resolution and accuracy are not high enough so that the reliability of BRB fault detection is a ected. Thus, a new multiple signal classification（MUSIC） algorithm based on particle swarm intelligence search is developed. Since spectrum peak search in MUSIC is a multimodal optimization problem, an improved bare?bones particle swarm optimization algorithm（IBPSO） is proposed first. In the IBPSO, a modified strategy of subpopulation determination is introduced into BPSO for realizing multimodal search. And then, the new MUSIC algorithm, called IBPSO?based MUSIC, is proposed by replacing the fixed?step traversal search with IBPSO. Meanwhile, a simulation signal is used to test the e ectiveness of the proposed algorithm. The simulation results show that its frequency precision reaches 10-5, and the computational cost is only comparable to that of traditional MUSIC with 0.1 search step. Finally, the IBPSO?based MUSIC is applied in BRB fault detection of an induction motor, and the e ectiveness and superiority are proved again. The proposed research provides a modified MUSIC algorithm which has su cient frequency precision to detect BRB fault in induction motors.

Torque Distribution of Electric Vehicle with Four In-Wheel Motors Based on Road Adhesion Margin

With the worsening of energy crisis and environmental pollution,electric vehicles with four in?wheel motors have been paid more and more attention. The main research subject is how to reasonably distribute the driving torque of each wheel. Considering the longitudinal motion,lateral motion,yaw movement and rotation of the four wheels,the tire model and the seven DOF dynamic model of the vehicle are established in this paper. Then,the torque distribution method is proposed based on road adhesion margin,which can be divided into anti ? slip control layer and torque distribution layer. The anti?slip control layer is built based on sliding mode variable structure control,whose main function is to avoid the excessive slip of wheels caused by road conditions. The torque distribution layer is responsible for selecting the torque distribution method based on road adhesion margin. The simulation results show that the proposed torque distribution method can ensure the vehicle quickly adapt to current road adhesion conditions,and improve the handling stability and dynamic performance of the vehicle in the driving process.

Mode switching control strategy of dual motors coupled driving on electric vehicles

Based on analyzing the structure and working principle on electric vehicles （EVs） with dual motors coupled by planetarY gears, the control strategy of mode switching was proposed. The power interruption problem on EVs with automatic mechanical transmission （AMT） shifting was resolved. Based on the speed-torque characteristics of the planetary gears and the principle of the auxiliary motor＇ s zero speed braking, control features of mode switching were introduced. The mode shifting between the main motor mode and dual motors coupled driving were studied. Matlab/Simulink was adopted as a platform to develop the simulation model of EVs with dual motors drive system and 3 gears AMT. Simulation results demonstrated that the power interruption of dual motors drive system was solved during mode switching. The power requirements of EVs were satisfied, too.

Feedback control of two-headed Brownian motors in flashing ratchet potential

We presented a detailed investigation on the movement of two-headed Brownian motors in an asymmetric potential under a feedback control. By numerical simulations the direct current is obtained. The current is periodic in the initial length of spring. There is an optimal value of the spring constant. And the dependence of the current on the opposing force is reversed. Then we found that when the change of the temperature and the opposing force have optimal values, the Brownian motors can also obtain the optimal efficiency.

The properties of Sn-Zn-Al-La fusible alloy for mitigation devices of solid propellant rocket motors

The Al and La elements are added to the Sn9Zn alloy to obtain the fusible alloy for the mitigation devices of solid propellant rocket motors. Differential scanning calorimetry(DSC), metallographic analysis,scanning electron microscopy(SEM), energy dispersive spectroscopy(EDS), tensile testing and fracture analysis were used to study the effect of Al and La elements on the microstructure, melting characteristics, and mechanical properties of the Sn9Zn alloy. Whether the fusible diaphragm can effectively relieve pressure was investigated by the hydrostatic pressure at high-temperature test. Experimental results show that the melting point of the Sn9Zn-0.8Al0·2La and Sn9Zn-3Al0·2La fusible alloys can meet the predetermined working temperature of ventilation. The mechanical properties of those are more than 35% higher than that of the Sn9Zn alloy at-50°C-70°C, and the mechanical strength is reduced by 80% at 175°C. It is proven by the hydrostatic pressure at high-temperature test that the fusible diaphragm can relieve pressure effectively and can be used for the design of the mitigation devices of solid propellant rocket motors.

Analytical calculation of electromagnetic, torque for surface mounted permanent magnet brushless motors

With the air gap magnetic field distribution of surface mounted permanent magnet （PM） motors obtained using an analytical technique, the instantaneous electromagnetic torque and its corresponding components are investigated with the Maxwell stress tensor method. Accurate results can easily be achieved using the proposed method without using the tedious finite element analysis （FEA）. In this paper, the electromagnetic torque of a surface mounted PM motor with two phases energized is decomposed into four torque components. This technique is useful not only for the design and optimization of the permanent magnet motor, but also for the choice of control strategy.

Broken Rotor Bar Fault Detection of Induction Motors Using a Joint Algorithm of Trust Region and Modified Bare-bones Particle Swarm Optimization

A precise detection of the fault feature parameter of motor current is a new research hotspot in the broken rotor bar(BRB) fault diagnosis of induction motors. Discrete Fourier transform(DFT) is the most popular technique in this field, owing to low computation and easy realization. However, its accuracy is often limited by the data window length, spectral leakage, fence e ect, etc. Therefore, a new detection method based on a global optimization algorithm is proposed. First, a BRB fault current model and a residual error function are designed to transform the fault parameter detection problem into a nonlinear least-square problem. Because this optimization problem has a great number of local optima and needs to be resolved rapidly and accurately, a joint algorithm(called TR-MBPSO) based on a modified bare-bones particle swarm optimization(BPSO) and trust region(TR) is subsequently proposed. In the TR-MBPSO, a reinitialization strategy of inactive particle is introduced to the BPSO to enhance the swarm diversity and global search ability. Meanwhile, the TR is combined with the modified BPSO to improve convergence speed and accuracy. It also includes a global convergence analysis, whose result proves that the TR-MBPSO can converge to the global optimum with the probability of 1. Both simulations and experiments are conducted, and the results indicate that the proposed detection method not only has high accuracy of parameter estimation with short-time data window, e.g., the magnitude and frequency precision of the fault-related components reaches 10^(-4), but also overcomes the impacts of spectral leakage and non-integer-period sampling. The proposed research provides a new BRB detection method, which has enough precision to extract the parameters of the fault feature components.