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

High-frequency issues using rotating voltage injections intended for position self-sensing

The rotor position is required in many control schemes in electrical drives. Replacing position sensors by machine self-sensing estimators increases reliability and reduces cost. Solutions based on tracking magnetic anisotropies through the monitoring of the incremental inductance variations are efficient at low-speed and standstill operations. This inductance can be estimated by measuring the response to the injection of high-frequency signals. In general however, the selection of the optimal frequency is not addressed thoroughly. In this paper, we propose discrete-time operations based on a rotating voltage injection at frequencies up to one third of the sampling frequency used by the digital controller. The impact on the rotation-drive, the computational requirement, the robustness and the effect of the resistance on the position estimation are analyzed regarding the signal frequency

Low-cost, high-resolution, fault-robust position and speed estimation for PMSM drives operating in safety-critical systems

In this paper it is shown how to obtain a low-cost, high-resolution and fault-robust position sensing system for permanent magnet synchronous motor drives operating in safety-critical systems, by combining high-frequency signal injection with binary Hall-effect sensors. It is shown that the position error signal obtained via high-frequency signal injection can be merged easily into the quantization-harmonic-decoupling vector tracking observer used to process the Hall-effect sensor signals. The resulting algorithm provides accurate, high-resolution estimates of speed and position throughout the entire speed range; compared to state-of-the-art drives using Hall-effect sensors alone, the low speed performance is greatly improved in healthy conditions and also following position sensor faults. It is envisaged that such a sensing system can be successfully used in applications requiring IEC 61508 SIL 3 or ISO 26262 ASIL D compliance, due to its extremely high mean time to failure and to the very fast recovery of the drive following Hall-effect sensor faults at low speeds. Extensive simulation and experimental results are provided on a 3.7 kW permanent magnet drive

Sensorless Rotor Position Estimation For Brushless DC Motors

Brushless DC motor speed is controlled by synchronizing the stator coil current with rotor position in order to acquire an accurate alignment of stator rotating field with rotor permanent-magnet field for efficient transfer of energy. In order to accomplish this goal, a motor shaft is instantly tracked by using rotating rotor position sensors such as Hall effect sensors, optical encoders or resolvers etc. Adding sensors to detect rotor position affects the overall reliability and mechanical robustness of the system. Therefore, a whole new trend of replacing position sensors with sensorless rotor position estimation techniques have a promising demand. Among the sensorless approaches, Back-EMF measurement and high frequency signal injection is the most common. Back-EMF is an electromotive force, directly proportional to the speed of rotor revolutions per second, the greater the speed motor acquires the greater the Back-EMF amplitude appears against the motion of rotation. However, the detected Back-EMF is zero at start-up and does not provide motor speed information at this instant. There-fore, Back-EMF based techniques are highly unfavourable for low speed application specially near zero. On the other hand, signal injection techniques are comparatively developed for low or near zero motor speed applications and they also can estimate the on-line motor parameters exploiting the identification theory on phase voltages and currents signals. The signal injection approach requires expensive additional hardware to inject high frequency signal. Since, motors are typically driven with pulse width modulation techniques, high frequency signals are naturally already present which can be used to detect position. This thesis presents rotor position estimation by measuring the voltage and current signals and also proposes an equivalent permanent-magnet synchronous motor model by fitting thedata to a position dependent circuit model

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

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