Semi-Analytical Approach Towards Design and Optimization of Induction Machines for Electric Vehicles

Electric machine design is a comprehensive task depending on the several factors, such as material resource limitations and economic factors. Therefore, an induction machine is a promising candidate because of the absence of magnetic material in the rotor. However, the conventional design approach can neither reflect the advances of the induction machine(IM) design nor exploit the trade-offs between design factors and the multi-physics nature of the electrical machine. Therefore, proposing fast and accurate novel methods to design, develop and analyze IMs using electromagnetic field oriented approaches is competitive to the old-fashion numerical methods. To achieve improved IM design from a baseline design to an optimal design, this dissertation: (1) Investigates the challenges of the high speed IM design specified for the electric vehicle application at the rated operating condition considering electromagnetic boundaries for the reasonable saturation level within a compact volume; (2) Proposes a new design approach of IM using modified equivalent circuit parameters to reduce spatial harmonics because of slotting effect and skewing effect; and also presents the importance of the 3-D analysis over 2-D analysis while developing the IM; (3) Proposes a novel electromagnetic field oriented mathematical model considering the slotting effect and axial flux variation because of skewing rotor bars to evaluate the IM performance with a lower and precise computational effort; (4) developed baseline IM is optimized with genetic algorithm incorporated in proposed subdomain model to improve the torque-speed profile. In order to further simplify the optimization procedure, a parametric and sensitivity based design approach is implemented to reduce the design variables. To evaluate the proposed optimal IM with extended constant power region and high torque density within a compact volume using novel 3-D subdomain model, the machine has been prototyped and tested from low to high speed under no-load and loaded condition. Electrical circuit parameter variation is demonstrated and compared to the one simulated in the FEA environment. This innovation can be applied to a family of electric machines with various topologies

Advanced Power Loss Modeling and Model-Based Control of Three-Phase Induction Motor Drive Systems

Three-phase induction motor (IM) drive systems are the most important workhorses of many industries worldwide. This dissertation addresses improved modeling of three-phase IM drives and model-based control algorithms for the purpose of designing better IM drive systems. Enhancements of efficiency, availability, as well as performance of IMs, such as maximum torque-per-ampere capability, power density, and torque rating, are of major interest. An advanced power loss model of three-phase IM drives is proposed and comprehensively validated at different speed, load torque, flux and input voltage conditions. This model includes a core-loss model of three-phase IMs, a model of machine mechanical and stray losses, and a model of power electronic losses in inverters. The drive loss model shows more than 90% accuracy and is used to design system-level loss minimization control of a motor drive system, which is integrated with the conventional volts-per-hertz control and indirect field-oriented control as case studies. The designed loss minimization control leads to more than 13% loss reduction than using rated flux for the testing motor drive under certain conditions. The proposed core-loss model is also used to design an improved model-based maximum torque-per-ampere control of IMs by considering core losses. Significant increase of torque-per-ampere capability could be possible for high-speed IMs. A simple model-based time-domain fault diagnosis method of four major IM faults is provided; it is nonintrusive, fast, and has excellent fault sensitivity and robustness to noise and harmonics. A fault-tolerant control scheme for sensor failures in closed-loop IM drives is also studied, where a multi-controller drive is proposed and uses different controllers with minimum hand-off transients when switching between controllers. A finite element analysis model of medium-voltage IMs is explored, where electromagnetic and thermal analyses are co-simulated. The torque rating and power density of the simulated machine could be increased by 14% with proper change of stator winding insulation material. The outcome of this dissertation is an advanced three-phase IM drive that is enhanced using model-based loss minimization control, fault detection and diagnosis of machine faults, fault-tolerant control under sensor failures, and performance-enhancement suggestions

A Versatile workbench simulator: Five-phase inverter and PMa-SynRM performance evaluation

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Thispaperpresents the design and structure of aversatileworkbench simulator forevaluating the performance of a five-phase inverter andPermanent Magnet assisted Synchronous Reluctance Motor(PMa-SynRM). The simulatorallows for adding variations tothe modulationtechniques, changingthe inverter structure’s semiconductordevice, and calculatingtheinverter’spower losses. Itcanalso facilitate observingthe current, voltage,andthe jointtemperature ofthe semiconductors devices. Furthermore,wecanobtain a perform that is close to anactualPMa-SynRM, dependingon the desired conditionsof speed and torque. The workbench simulator wasdevelopedby combining three software: Matlab/Simulink, PLECSand Altair Flux.Postprint (author's final draft

Analytical prediction of the electromagnetic torques in single-phase and two-phase AC motors

The single-phase and two-phase versions of AC motors can be modelled by means of the two-axis (d-q) theory with sufficient accuracy when the equivalent circuit parameters are correctly estimated. This work attempts to present a unified approach to the analytical prediction of the electromagnetic torque of these machines. Classical d-q axes formulation requires that the reference frame should be fixed on the frame where the asymmetries arise, i.e. the stator and rotor. The asynchronous torques that characterize the induction motors are modelled in a stationary reference frame, where the d-q axes coincide with the physical magnetic axes of the stator windings. For the permanent magnet motors, that may exhibit asymmetries on both stator and rotor, the proposed solution includes: a series of frame transformations, followed by symmetrical components decomposition. As in single-phase and two-phase systems the homopolar component is zero; each symmetrical component – negative and positive – is further analysed using d-q axes theory. The superposition principle is employed to consider the magnets and rotor cage effects. The developed models account for the most important asymmetries of the motor configuration. These are, from the stator point of view, different distribution, conductors' dimensions and number of effective turns, non-orthogonal magnetic axes windings and from the rotor point of view, asymmetrical rotor cage, variable reluctance, and permanent magnets effect. The time and space harmonics effect is ignored. Test data are compared with the computed data in order to observe how the simplifying assumptions affect the level of accuracy. The analytical prediction methods make possible torque computation according to the nature of the torque being computed, namely, induction, reluctance and excitation (permanent magnet). The results are available for quasi steady-state, steady-state (rated or synchronous speed) and dynamic analyses. All the developed mathematical models can be used in preliminary design for further optimisation and accurate estimation in complex numerical models. Another important feature of the analytical models for single-phase and two-phase AC motors, is that they can be directly implemented in any suitable electrical drives control strategy.reviewe

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

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

Accurate Induction Machines Efficiency Mapping Computed by Standard Test Parameters

The extensive electrification process that is taking hold in several applications makes increasingly necessary the virtualization of electric components for energetic and performance assessments during the system design stage. For this purpose, this paper proposes a straightforward methodology for computing the efficiency maps of induction machines operated in wide torque-speed ranges. The modeling approach is based on the induction machine equivalent circuit defined in the rotor dq coordinates. The procedure allows computing a set of efficiency maps at different machine temperatures and supply voltage levels, both for motor and generator operation modes. The equivalent circuit parameters at different frequencies and voltages are determined by means of the well-known no-load and locked-rotor tests, thus including in the modelling the machine nonlinearities, skin effect and the iron losses. The proposed methodology has been validated on a 10 kW, 4-pole induction machine. The comparison between computed and experimental efficiency maps for different operating conditions, confirm the validity of the proposed methodology

Performance Analysis of Doubly Excited Brushless Generator with Outer Rotor for Wind Power Application

In this paper, a novel doubly excited brushless generator (DEBG) with outer radial laminated magnetic barrier rotor (RLMB-rotor) for wind power application was designed and analyzed. The DEBG has 10 rotor pole numbers with outer rotor. Its performance was investigated using the 2D transient finite element method. The magnetic fields, torque capability, end winding voltage characteristics, radial magnetic force and energy efficiency were analyzed. All studies in this paper show that the simplicity, reliability, high efficiency and low vibration and noise of the DEBG with outer rotor were attractive for variable speed constant frequency (VSCF) wind power generation system