Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

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

Multi-physics Model Of Key Components In High Efficiency Vehicle Drive

Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are crucial technologies for the automotive industry to meet society’s demands for cleaner, more energy efficient transportation. Meeting the need to provide power which sustains HEVs and EVs is an immediate area of concern that research and development within the automotive community must address. Electric batteries and electrical motors are the key components in HEV and EV power generation and transmission, and their performance plays very important role in the overall performance of the modern high efficiency vehicles. Therefore, in this dissertation, we are motivated to study the electric batteries, interior permanent motor (IPM), in the context of modern hybrid electric/electric drive systems, from both multi-physics and system level perspectives. Electrical circuit theory, electromagnetic Finite Element Analysis (FEA), and Computational Fluid Dynamic (CFD) finite volume method will be used primarily in this work. The work has total of five parts, and they are introduced in the following. Firstly, Battery thermal management design is critical in HEV and EV development. Accurate temperature distribution of the battery cells during vehicle operation is required for achieving optimized design. We propose a novel electrical-thermal battery modeling technique that couples a temperature dependent battery circuit model and a physics-based CFD model to meet this need. The electrical circuit model serves as a heat generation mechanism for the CFD model, and the CFD model provides the temperature distribution of the battery cells, which can also impact the heat generation of the electrical battery model. In this part of work, simulation data has been derived from the model respective to electrical performance of the battery as well iv as the temperature distribution simultaneously in consideration of the physical dimensions, material properties, and cooling conditions. The proposed model is validated against a battery model that couples the same electrical model with a known equivalent thermal model. Secondly, we propose an accurate system level Foster network thermal model. The parameters of the model are extracted from step responses of the CFD battery thermal model. The Foster network model and the CFD model give the same results. The Foster network can couple with battery circuit model to form an electric-thermal battery model for system simulation. Thirdly, IPM electric machines are important in high performance drive systems. During normal operations, irreversible demagnetization can occur due to temperature rise and various loading conditions. We investigate the performance of an IPM using 3d time stepping electromagnetic FEA considering magnet’s temperature dependency. Torque, flux linkage, induced voltage, inductance and saliency of the IPM will be studied in details. Finally, we use CFD to predict the non-uniform temperature distribution of the IPM machine and the impact of this distribution on motor performance. Fourthly, we will switch gear to investigate the IPM motor on the system level. A reduced order IPM model is proposed to consider the effect of demagnetization of permanent magnet due to temperature effect. The proposed model is validated by comparing its results to the FEA results. Finally, a HEV is a vehicle that has both conventional mechanical (i.e. internal combustion engine) and electrical propulsion systems. The electrical powertrain is used to work with the conventional powertrain to achieve higher fuel economy and lower emissions. v Computer based modeling and simulation techniques are therefore essential to help reduce the design cost and optimize system performance. Due to the complexity of hybrid vehicles, multidomain modeling ability is preferred for both component modeling and system simulation. We present a HEV library developed using VHDL-AMS

Performance of Induction Machines

Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure. The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines. Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications

On the Modeling, Analysis and Development of PMSM: For Traction and Charging Application

Permanent magnet synchronous machines (PMSMs) are widely implemented commercially available traction motors owing to their high torque production capability and wide operating speed range. However, to achieve significant electric vehicle (EV) global market infiltration in the coming years, the technological gaps in the technical targets of the traction motor must be addressed towards further improvement of driving range per charge of the vehicle and reduced motor weight and cost. Thus, this thesis focuses on the design and development of a novel high speed traction PMSM with improved torque density, maximized efficiency, reduced torque ripple and increased driving range suitable for both traction and integrated charging applications. First, the required performance targets are determined using a drive cycle based vehicle dynamic model, existing literature and roadmaps for future EVs. An unconventional fractional–slot distributed winding configuration with a coil pitch of 2 is selected for analysis due to their short end–winding length, reduced winding losses and improved torque density. For the chosen baseline topology, a non–dominated sorting genetic algorithm based selection of optimal odd slot numbers is performed for higher torque production and reduced torque ripple. Further, for the selected odd slot–pole combination, a novel star–delta winding configuration is modeled and analyzed using winding function theory for higher torque density, reduced spatial harmonics, reduced torque ripple and machine losses. Thereafter, to analyze the motor performance with control and making critical decisions on inter–dependent design parameter variations for machine optimization, a parametric design approach using a novel coupled magnetic equivalent circuit model and thermal model incorporating current harmonics for fractional–slot wound PMSMs was developed and verified. The developed magnetic circuit model incorporates all machine non–linearities including effects of temperature and induced inverter harmonics as well as the space harmonics in the winding inductances of a fractional–slot winding configuration. Using the proposed model with a pareto ant colony optimization algorithm, an optimal rotor design is obtained to reduce the magnet utilization and obtain maximized torque density and extended operating range. Further, the developed machine structure is also analyzed and verified for integrated charging operation where the machine’s winding inductances are used as line inductors for charging the battery thereby eliminating the requirement of an on–board charger in the powertrain and hence resulting in reduced weight, cost and extended driving range. Finally, a scaled–down prototype of the proposed PMSM is developed and validated with experimental results in terms of machine inductances, torque ripple, torque–power–speed curves and efficiency maps over the operating speed range. Subsequently, understanding the capabilities and challenges of the developed scaled–down prototype, a full–scale design with commercial traction level ratings, will be developed and analyzed using finite element analysis. Further recommendations for design improvement, future work and analysis will also be summarized towards the end of the dissertation

An Interface Design for Axial Induction Motor

Asynchronous motors have been used extensively in the industry since the first discovery. Although the general working principles do not change, they can be made geometrically in the form of cylinders, spheres, cones and even discs. One of these geometries is known as axial flux machine topology which has a disc structure. Axial flux machines are remarkable in terms of their high efficiency, high power density and advantage in terms of compact structures. In this study, extended literature search of axial flux induction motor is given. In addition to the literature, axial induction motor design interface has been created by using MATLAB GUI software. This interface can communicate with ANSYS Maxwell. Thus, the dimensioning values of the machine calculated via the interface can be drawn automatically in Ansys Maxwell and it can perform numerical analysis. The obtained torque, current and efficiency data were evaluated

Magnetic noise reduction of in-wheel permanent magnet synchronous motors for light-duty electric vehicles

This paper presents study of a multi-slice subdomain model (MS-SDM) for persistent low-frequency sound, in a wheel hub-mounted permanent magnet synchronous motor (WHM-PMSM) with a fractional-slot non-overlapping concentrated winding for a light-duty, fully electric vehicle applications. While this type of winding provides numerous potential benefits, it has also the largest magnetomotive force (MMF) distortion factor, which leads to the electro-vibro-acoustics production, unless additional machine design considerations are carried out. To minimize the magnetic noise level radiated by the PMSM, a skewing technique is targeted with consideration of the natural frequencies under a variable-speed-range analysis. To ensure the impact of the minimization technique used, magnetic force harmonics, along with acoustic sonograms, is computed by MS-SDM and verified by 3D finite element analysis. On the basis of the studied models, we derived and experimentally verified the optimized model with 5 dBA reduction in A-weighted sound power level by due to the choice of skew angle. In addition, we investigated whether or not the skewing slice number can be of importance on the vibro-acoustic objectives in the studied WHM-PMSM.Postprint (published version

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

Two wheel speed robust sliding mode control for electric vehicle drive

Nowadays the uses of electrical power resources are integrated in the modern vehicle motion traction chain so new technologies allow the development of electric vehicles (EV) by means of static converters-related electric motors. All mechanical transmission devices are eliminated and vehicle wheel motion can be controlled by means of power electronics. The proposed propulsing system consists of two induction motors (IM) that ensure the drive of the two back driving wheels. The proposed control structure-called independent machines- for speed control permit the achievement of an electronic differential. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling independently, every driving wheel to turn at different speeds in any curve. This paper presents the study and the sliding mode control strategy of the electric vehicle driving wheels

Model predictive current control of switched reluctance motor with inductance auto-calibration

The thesis is composed of three papers, which investigate the application of Model Predictive Controller (MPC) for current control of Switched Reluctance Motor (SRM). Since the conventional hysteresis current control method is not suitable for high power SRM drive system with low inductance and limited switching frequency, MPC is a promising alternative approach for this application. The proposed MPC can cope with the measurement noise as well as uncertainties within the machine inductance profile. In the first paper, a MPC current control method for Double-Stator Switched Reluctance Motor (DSSRM) drives is presented. A direct adaptive estimator is incorporated to follow the inductance variations in a DSSRM. In the second paper, the Linear Quadratic (LQ) form and dynamic programming recursion for MPC are analyzed, afterwards the unconstrained MPC solution for stochastic SRM model is derived. The Kalman filter is employed to reduce the variance of measurement noises. Based on Recursive Linear-Square (RLS) estimation, the inductance profile is calibrated dynamically. In the third paper, a simplified recursive MPC current control algorithm for SRM is applied for embedded implementation. A novel auto-calibration method for inductance surface estimation is developed to improve current control performance of SRM drive in statistic terms. --Abstract, page iv