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

Sensorless Control of Switched-Flux Permanent Magnet Machines

This thesis investigates the sensorless control strategies of permanent magnet synchronous machines (PMSMs), with particular reference to switched-flux permanent magnet (SFPM) machines, based on high-frequency signal injection methods for low speed and standstill and the back-EMF based methods for medium and high speeds

Study of rotor position estimation algorithm based on back-EMF voltage for dual-winding fault-tolerant permanent magnet motor

An improved position estimation of the sensorless control system with online parameter identification based on back-Electromotive Force (EMF) voltage is presented for the dual-winding fault-tolerant permanent magnet motor (FTPMM). In this control system, the rotor position is estimated by the flux linkage and the back-EMF which are generated by each phase winding. By introducing phase-locked loop technology to compensate the steady-state error of the system and online identification of motor parameters which is using the least-square method with forgetting factor, more accurate position estimation can be obtained. The current vector fault-tolerant control strategy improves the fault tolerance of the system and makes it strong robust stability. The simulation results have shown that the accurate position data can be acquired both under healthy condition and single-phase fault condition. Then, the hardware experimental results show the feasibility and validity of the proposed algorithm

Sensorless position estimation in fault-tolerant permanent magnet AC motor drives with redundancy.

Safety critical applications are heavily dependent on fault-tolerant motor drives being capable of continuing to operate satisfactorily under faults. This research utilizes a fault-tolerant PMAC motor drive with redundancy involving dual drives to provide parallel redundancy where each drive has electrically, magnetically, thermally and physically independent phases to improve its fault-tolerant capabilities. PMAC motor drives can offer high power and torque densities which are essential in high performance applications, for example, more-electric airplanes. In this thesis, two sensorless algorithms are proposed to estimate the rotor position in a fault-tolerant three-phase surface-mounted sinusoidal PMAC motor drive with redundancy under normal and faulted operating conditions. The key aims are to improve the reliability by eliminating the use of a position sensor which is one of major sources of failures, as well as by offering fault-tolerant position estimation. The algorithms utilize measurements of the winding currents and phase voltages, to compute flux linkage increments without integration, hence producing the predicted position values. Estimation errors due measurements are compensated for by a modified phase-locked loop technique which forces the predicted positions to track the flux linkage increments, finally generating the rotor position estimate. The fault-tolerant three-phase sensorless position estimation method utilizes the measured data from the three phase windings in each drive, consequently obtaining a total of two position estimates. However, the fault-tolerant two-phase sensorless position estimation method uses measurements from pairs of phases and produces three position estimates for each drive. Therefore, six position estimates are available in the dual drive system. In normal operation, all of these position estimates can be averaged to achieve a final rotor angle estimate in both schemes. Under faulted operating conditions, on the other hand, a final position estimate should be achieved by averaging position estimates obtained with measurements from healthy phases since unacceptable estimation errors can be created by making use of measured values from phases with failures. In order to validate the effectiveness of the proposed fault-tolerant sensorless position estimation schemes, the algorithms were tested using both simulated data and offline measured data from an experimental fault-tolerant PMAC motor drive system. In the healthy condition, both techniques presented good performance with acceptable accuracies under low and high steady-state speeds, starting from standstill and step load changes. In addition, they had robustness against parameter variations and measurement errors, as well as the ability to recover quickly from large incorrect initial position information. Under faulted operating conditions such as sensor failures, however, the two-phase sensorless method was more reliable than the threephase sensorless method since it could operate even with a faulty phase.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 201

General Torque Enhancement Approach for a Nine-Phase Surface PMSM with Built-in Fault Tolerance

The paper investigates maximum possible torque improvement in a two-pole surface permanent magnet synchronous machine (PMSM) with a reduced magnet span, which causes production of highly non-sinusoidal back-EMF. It contains a high third and fifth harmonics, which can be used for the torque enhancement, using stator current harmonic injection. Optimal magnet span is studied first and it is shown that with such a value the machine would be able to develop an insignificantly lower maximum torque than with the full magnet span. Next, field-oriented control (FOC) algorithm, which considers all non-fundamental EMF components lower than the machine phase number, is devised. Using maximum-torque per Ampere (MTPA) principles, optimal ratios between fundamental and all other injected components are calculated and then used in the drive control. The output torque can be in this way increased up to 45% with respect to the one obtainable with fundamental current only. Alternatively, for the same load torque, stator current RMS value can be reduced by 45%. Last but not least, a method for position sensor fault mitigation is introduced. It is based on the alternative use of a back-EMF harmonic for rotor position estimation, instead of the torque enhancement. Experimental verification is provided throughout for all the relevant aspects

Parameter estimation for VSI-Fed PMSM based on a dynamic PSO with learning strategies

© 1986-2012 IEEE.A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key parameter estimation for permanent magnet synchronous machines (PMSMs), where the voltage-source inverter (VSI) nonlinearities are taken into account in the parameter estimation model and can be estimated simultaneously with other machine parameters. In the DPSO-LS algorithm, a novel movement modification equation with variable exploration vector is designed to effectively update particles, enabling swarms to cover large areas of search space with large probability and thus the global search ability is enhanced. Moreover, a Gaussian-distribution-based dynamic opposition-based learning strategy is developed to help the pBest jump out local optima. The proposed DPSO-LS can significantly enhance the estimator model accuracy and dynamic performance. Finally, the proposed algorithm is applied to multiple parameter estimation including the VSI nonlinearities of a PMSM. The performance of DPSO-LS is compared with several existing PSO algorithms, and the comparison results show that the proposed parameters estimation method has better performance in tracking the variation of machine parameters effectively and estimating the VSI nonlinearities under different operation conditions

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

General Torque Enhancement Approach for a Nine-Phase Surface PMSM with Built-in Fault Tolerance

The paper investigates maximum possible torque improvement in a two-pole surface permanent magnet synchronous machine (PMSM) with a reduced magnet span, which causes production of highly non-sinusoidal back-EMF. It contains a high third and fifth harmonics, which can be used for the torque enhancement, using stator current harmonic injection. Optimal magnet span is studied first and it is shown that with such a value the machine would be able to develop an insignificantly lower maximum torque than with the full magnet span. Next, field-oriented control (FOC) algorithm, which considers all non-fundamental EMF components lower than the machine phase number, is devised. Using maximum-torque per Ampere (MTPA) principles, optimal ratios between fundamental and all other injected components are calculated and then used in the drive control. The output torque can be in this way increased up to 45% with respect to the one obtainable with fundamental current only. Alternatively, for the same load torque, stator current RMS value can be reduced by 45%. Last but not least, a method for position sensor fault mitigation is introduced. It is based on the alternative use of a back-EMF harmonic for rotor position estimation, instead of the torque enhancement. Experimental verification is provided throughout for all the relevant aspects