Robust fault tolerant control of induction motor system

Research into fault tolerant control (FTC, a set of techniques that are developed to increase plant availability and reduce the risk of safety hazards) for induction motors is motivated by practical concerns including the need for enhanced reliability, improved maintenance operations and reduced cost. Its aim is to prevent that simple faults develop into serious failure. Although, the subject of induction motor control is well known, the main topics in the literature are concerned with scalar and vector control and structural stability. However, induction machines experience various fault scenarios and to meet the above requirements FTC strategies based on existing or more advanced control methods become desirable. Some earlier studies on FTC have addressed particular problems of 3-phase sensor current/voltage FTC, torque FTC, etc. However, the development of these methods lacks a more general understanding of the overall problem of FTC for an induction motor based on a true fault classification of possible fault types.In order to develop a more general approach to FTC for induction motors, i.e. not just designing specific control approaches for individual induction motor fault scenarios, this thesis has carried out a systematic research on induction motor systems considering the various faults that can typically be present, having either “additive” fault or “multiplicative” effects on the system dynamics, according to whether the faults are sensor or actuator (additive fault) types or component or motor faults (multiplicative fault) types.To achieve the required objectives, an active approach to FTC is used, making use of fault estimation (FE, an approach that determine the magnitude of a fault signal online) and fault compensation. This approach of FTC/FE considers an integration of the electrical and mechanical dynamics, initially using adaptive and/or sliding mode observers, Linear Parameter Varying (LPV, in which nonlinear systems are locally decomposed into several linear systems scheduled by varying parameters) and then using back-stepping control combined with observer/estimation methods for handling certain forms of nonlinearity.In conclusion, the thesis proposed an integrated research of induction motor FTC/FE with the consideration of different types of faults and different types of uncertainties, and validated the approaches through simulations and experiments

A Fault-Tolerant Control Architecture for Induction Motor Drives in Automotive Applications

International audienceThis paper describes a fault-tolerant control system for a high-performance induction motor drive that propels an electrical vehicle (EV) or hybrid electric vehicle (HEV). In the proposed control scheme, the developed system takes into account the controller transition smoothness in the event of sensor failure. Moreover, due to the EV or HEV requirements for sensorless operations, a practical sensorless control scheme is developed and used within the proposed fault-tolerant control system. This requires the presence of an adaptive flux observer. The speed estimator is based on the approximation of the magnetic characteristic slope of the induction motor to the mutual inductance value. Simulation results, in terms of speed and torque responses, show the effectiveness of the proposed approach

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines

A Sensorless Direct Torque Control Scheme Suitable for Electric Vehicles

International audienceIn this paper a sensorless control is proposed to increase the efficiency of a Direct Torque Control (DTC) of an induction motor propelling an Electric Vehicle (EV). The proposed scheme uses an adaptive flux and speed observer that is based on a full order model of the induction motor. Moreover, it is evaluated on an EV global model taking into account the vehicle dynamics. Simulations were first carried out on a test vehicle propelled by a 37-kW induction motor to evaluate the consistency and the performance of the proposed control approach. The commonly used European drive cycle ECE-15 is adopted for simulation. The obtained results seem to be very promising. Then, the proposed control approach was experimentally implemented, on a TMS320F240 DSP-based development board, and tested on 1-kW induction motor. Experimental results show that the proposed control scheme is effective in terms of speed and torque performances. Indeed, it allows speed and torque ripple minimization. Moreover, the obtained results show that the proposed sensorless DTC scheme for induction motors is a good candidate for EVs propulsion

Performance Comparison of Different Speed Estimation Techniques in Sensorless Vector Controlled Induction Motor Drives

Field-oriented control and direct torque control are fast becoming necessities of modern industrial setups for induction motor drive control. Induction motors are considered as the beginning part to create any electrical drive system to be subsequently utilized for several industrial requirements. So now a day due to its high application the need to control the performance of the induction motor is gaining importance. In modern control system, IM is analyzed by different mathematical models mainly depending on its applications. Vector control method is suitably applied to induction machine in 3-phase symmetrical or in 2-phase unsymmetrical version. For vector control IM is realized as DC motor having its characteristics. This dissertation work is aimed to give a detailed idea about the speed control and variations in an induction motor through vector control technique thereby showing its advantage over the conventional scalar method of speed control. It also focusses on the speed estimation techniques for sensorless closed loop speed control of an IM relying on the direct field-oriented control technique. The study is completed through simulations with use of MATLAB/Simulink block sets allowing overall representation of the whole control system arrangement of the Induction motor. The performance of different sensorless schemes and comparison between them on several parameters like at low speed, high speed etc. is also provided emphasizing its advantages and disadvantages. The analysis has been carried out on the results obtained by simulations, where secondary effects introduced by the hardware implementations have not been considered. The simulations and the evaluations of different control techniques are executed using parameters of a 50 HP, 60 Hz induction motor which is fed by an inverter

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

Machine Learning based Early Fault Diagnosis of Induction Motor for Electric Vehicle Application

Electrified vehicular industry is growing at a rapid pace with a global increase in production of electric vehicles (EVs) along with several new automotive cars companies coming to compete with the big car industries. The technology of EV has evolved rapidly in the last decade. But still the looming fear of low driving range, inability to charge rapidly like filling up gasoline for a conventional gas car, and lack of enough EV charging stations are just a few of the concerns. With the onset of self-driving cars, and its popularity in integrating them into electric vehicles leads to increase in safety both for the passengers inside the vehicle as well as the people outside. Since electric vehicles have not been widely used over an extended period of time to evaluate the failure rate of the powertrain of the EV, a general but definite understanding of motor failures can be developed from the usage of motors in industrial application. Since traction motors are more power dense as compared to industrial motors, the possibilities of a small failure aggravating to catastrophic issue is high. Understanding the challenges faced in EV due to stator fault in motor, with major focus on induction motor stator winding fault, this dissertation presents the following: 1. Different Motor Failures, Causes and Diagnostic Methods Used, With More Importance to Artificial Intelligence Based Motor Fault Diagnosis. 2. Understanding of Incipient Stator Winding Fault of IM and Feature Selection for Fault Diagnosis 3. Model Based Temperature Feature Prediction under Incipient Fault Condition 4. Design of Harmonics Analysis Block for Flux Feature Prediction 5. Flux Feature based On-line Harmonic Compensation for Fault-tolerant Control 6. Intelligent Flux Feature Predictive Control for Fault-Tolerant Control 7. Introduction to Machine Learning and its Application for Flux Reference Prediction 8. Dual Memorization and Generalization Machine Learning based Stator Fault Diagnosi

Non-intrusive efficiency estimation of inverter-fed induction machines

Motorised loads using induction machines use approximately 60% of the electricity globally. Most of these systems use three-phase induction motors due to their robustness and lower cost. They are often installed in continuously operating industrial plants/applications that require no operational interruptions. Whilst most of these induction machines are supplied from ideally sinusoidal supplies, applications are emerging where induction machines are fed from non-sinusoidal supplies. In particular, pulse width modulated inverters realize efficient control of induction machines in many automated industrial applications. From an energy management perspective, it is vital to continually assess the efficiency of induction machines in order to initiate replacement or economic repair. It is therefore of paramount importance that reliable and non-intrusive techniques for efficiency estimation of induction machines be investigated, that consider sinusoidal and non-sinusoidal supplies. This work proposes a non-intrusive efficiency estimation technique for inverter–fed induction motors that is based on harmonic regression analysis, harmonic equivalent circuit parameter estimation and harmonic loss analysis using limited measured data. Firstly, considerations for inverter-fed induction motor equivalent circuit modelling and parameter estimation techniques suitable for non-intrusive efficiency estimation are presented and the selection of one equivalent circuit for analysis is justified. Measured data is obtained from two different induction motors on a flexible 110kW test rig that utilises an HBM Gen 7i data acquisition system. By measuring voltage, current and input power at the supply terminals of the inverter-fed motor, the fundamental equivalent circuit parameters are estimated using population based incremental learning algorithm and compared with those obtained from the IEC 60034-2-1 Standard. The harmonic parameters are estimated using the bacterial foraging algorithm basing on the input impedance of the motor at each harmonic order. A finite harmonic loss analysis is carried out on the tested induction motors. The proposed techniques and harmonic loss analysis provide accurate efficiency estimates of within 1.5% error when compared to the direct method. Lastly, a related non-intrusive efficiency estimation technique is proposed that caters for a holistic loss contribution by all harmonics. The efficiency results from the proposed techniques are compared to those obtained from the IEC-TS 60034-2-3 Technical Specification and a direct method. The estimated efficiencies are comparable to those measured by the Technical Specification and a direct method within 2% error when tested on 37kW and 45kW PWM inverter-fed motors across the loading range. Furthermore, this work conducts a comprehensive non-intrusive rotor speed estimation comparative analysis in order to recommend the best technique(s), in terms of intrusiveness, accuracy and computational overhead. Errors of less than 1% have been reported in literature and experimental verification when using vibration analysis, Motor Current Signature Analysis (MCSA), Rotor Slot Harmonic (RSH) and Rotor Eccentricity Harmonic (REH) analysis techniques in inverter-fed IMs

Maximum torque-per-Amp control for traction IM drives: theory and experimental results

A novel maximum torque per Ampere (MTPA) controller for induction motor (IM) drives is presented. It is shown to be highly suited to applications that do not demand an extremely fast dynamic response, for example electric vehicle drives. The proposed MTPA field oriented controller guarantees asymptotic torque (speed) tracking of smooth reference trajectories and maximises the torque per Ampere ratio when the developed torque is constant or slow varying. An output-feedback linearizing concept is employed for the design of torque and flux subsystems to compensate for the torque-dependent flux variations required to satisfy the MTPA condition. As a first step, a linear approximation of the IM magnetic system is considered. Then, based on a standard saturated IM model, the nonlinear static MTPA relationships for the rotor flux are derived as a function of the desired torque, and a modified torque-flux controller for the saturated machine is developed. The flux reference calculation method to achieve simultaneously an asymptotic field orientation, torque-flux decoupling and MTPA optimization in steady state is proposed. The method guarantees singularity-free operation and can be used as means to improve stator current transients. Experimental tests prove the accuracy of the control over a full torque range and show successful compensation of the magnetizing inductance variations caused by saturation. The proposed MTPA control algorithm also demonstrates a decoupling of the torque (speed) and flux dynamics to ensure asymptotic torque tracking. In addition, a higher torque per Ampere ratio is achieved together with an improved efficiency of electromechanical energy conversion