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 Passive Control Algorithms for Medium to High Power Synchronous Motor Drives

This study is focused on the definition of sensorless algorithms for Surface-Mounted Permanent Magnet Synchronous Motors (SM-PMSM) and Electrically Excited Synchronous Motors (EESM). Even if these types of motors are rather different from a constructive point of view, they have some common issues regarding sensorless drives. Indeed, SM-PMSMs, which are usually used for low-medium power applications, have a low rotor anisotropy, therefore it is complicated to use sensorless active methods (which are based on high-frequency voltage injection), due to the low signal to noise ratio. On the other hand, active methods on high-power EESM have the drawback of high torque ripple. For these reasons, both for SM-PMSM and EESM, it is interesting to define and use sensorless passive algorithms (i.e., based on observers and estimators). The drawback of such algorithms is that their performance deteriorates significantly in the low-speed region. The aim of this thesis is to define a robust sensorless passive algorithm that could work in a wide speed region and that could start the motor from standstill even with a high load torque. The initial objective of the work is to find, among the various algorithms proposed in the technical literature, the most promising one. For this purpose, four different algorithms are selected. They are chosen considering the most recent articles presented in the technical literature on high reputable journals. Since many improvements are proposed in the literature for the different algorithms, the most recent ones are candidates for being the ones with higher performance. Even if the experimental tests of the four different algorithms are shown in the literature, it is difficult to evaluate a priori which offers the best performance. As a matter of facts, for each algorithm different tests are carried out (e.g., different speed and torque profiles). In addition to that, motor sizing and features are different. Moreover, the test bench characteristics can significantly affect sensorless performance. As an example, inverter features and non-linearities (e.g., switching frequency, dead times, parasitic capacitance) and current measures (e.g., noise, linearity, bias) play a key role in the estimation of rotor position. The added value of this thesis is to perform a fair comparison of the four algorithms, performing the same tests with the same test bench. Additional tests are performed on the most performing algorithm. Even if this sensorless technique is already proposed in the technical literature, a methodology for observer gain tuning is not shown, which is proposed, instead, in this thesis. Moreover, the algorithm is enhanced by adding a novel management of direct axis current, which ensures the stability during fast transient from medium-high speed to low speed. The algorithm is tested with different test benches in order to verify the control effectiveness in various operating conditions. As a matter of facts, it is tested at first in the University of Genoa PETRA Lab on two different test benches. The first test bench is composed of two coupled motors, in which the braking motor could realize different torque profiles (linear torque, quadratic torque and constant torque), whereas in the second test bench the motor is coupled with an air compressor, which is a demanding load since high and irregular torque is applied at standstill. After the test at the University of Genoa, the algorithm is implemented in Phase Motion Control and Physis drive and tested on a six-meter diameter fan. Regarding the EESMs, for these type of motor is necessary to estimate the stator flux amplitude and angle. Indeed, the stator angle is usually used to perform the Park transformations in the FOC scheme and the stator flux amplitude is used to control the excitation current. In this study, the RFO is adapted for estimating the stator flux of an EESM. Regarding the control for EESM, it is tested on a simulative model for high-power motors provided by NIDEC ASI and tested on a small-scale test bench at the University of Genoa

Rotor Position Identification for Brushless DC motor

Permanent magnet BLDC motors are characterized by a central magnetic core, called the rotor, and fixed electric coils (usually six) equally spaced in a ring around the core, called the stator. Motor movement is controlled by alternately energizing and de-energizing the stator coils to create a rotating magnetic field that propels the rotor. In order for this process to work correctly, BLDC motors required a technology called electronic commutation, in which the coil currents must be very carefully synchronized to rotor position to ensure that the rotating field is correctly aligned with the permanent magnetic field in the rotor. Usually rotor position is measured by external sensors such as Hall-effect sensors and optical encoders and these external sensors increase the system cost and reduces reliability. In order to control the price and make it more reliable this thesis propose to infer the rotor position from voltage and current measurement of motor. The most common approaches to sensorless control are based on the measurement of the electromotive force (back-EMF), that is induced by the rotor motion. As the back-EMF is nearly zero at very low speed and at stationary position, and can not be measured. Therefore a separate algorithm is required for start-up and control at low speed. The other method of sensorless control involves the inference of rotor position from the variation in inductance caused by rotor position. This thesis presents a prototype system for sensorless control of BLDC motors over the entire speed range of the motor, including stall (zero speed) conditions using the voltage and current signals from the motor

Modelling and practical set-up to investigate the performance of permanent magnet synchronous motor through rotor position estimation at zero and low speeds

This thesis provides a study for the rotor position estimation in SM-PMSMs, particularly at zero and low speeds. The method for zero rotor speed is based on injection of three high frequency voltage pulses in the motor stator windings. Then, the voltage responses at the motor terminals are exploited to extract the rotor position. Two approaches, modelling and practical implementations, are presented. The obtained results have showed a verification of a high-resolution position estimation (a position estimation of 1 degree angle), a simplicity and cost effective implementation and a no need for current sensors is required to achieve the estimation process. It should be noticed that the implementation of rotor position estimation at zero speed is only attended when the rotor is at standstill or very low speed. Therefore, the motor driver is not expected to be active at this condition. Thereby, the zero speed estimation does not provide a robust torque control. In future, this should be taking into consideration to overcome this drawback and to make the estimator more reliable. At low speed running, the primary goal is to start spinning the under test motors, and then the rotor position estimation is achieved. The motor spinning is based on adopting a virtual injected signal to generate the voltage components, Vα and Vβ, of the space vector pulse width modulation technique. Then, generating the eight space vectors is conducted through storing the standard patterns of the six space vector sectors in a memory structure together with the timing sequences of each sector. The presented strategy of motor running includes a proposed motor speed control scheme, which is based on controlling the frequency of the power signal, at the inverter output, through controlling the timing period of execution the power delivery program. The thesis presents a proposed method to achieve the estimation goal depends on tracking the magnetic saliency on one motor line voltage. Thereby, the rotor position estimation The introduced proposed method, for rotor position estimation at zero speed, verifies the following contributions: - Presents a simple and cost effective zero speed rotor position estimator for the motor under test. - The aimed resolution in this thesis is an angle 1 degree. IV - Adopting solely the measuring of motor terminal voltages. Eliminating the detection of the rotor magnet polarity as a necessary technique for completing the position estimation. At low speed running, the following contributions are verified: - Rather than a real frequency signal, a virtual injected signal is adopted to generate the voltage components, Vα and Vβ of the space vector pulse width modulation technique. - The proposed method for generating the eight space vectors is based on storing the standard patterns of the six sectors in a memory structure together with the timing sequence. - The strategy of motor speed control is based on controlling the period of execution the power delivery program. - The strategy of low speed rotor position employs one motor line voltage from which the low speed estimation is achieved

Induction motor bearing fault detection using a sensorless approach

Continuous condition assessment of induction motors is very important due to its potential to reduce down-time and manpower needed in industry. Rolling element bearing faults result in more than 40% of all induction motor failures. Vibration analysis has been utilized to detect bearing faults for years. However, vibration sensors and expert vibration interpretation are expensive. This limitation prevents widespread monitoring of continuous bearing conditions in induction motors, which provides better performance compared to periodic monitoring, a typical practice for motor bearing maintenance in industry. A strong motivation exists for finding a costeffective approach for the detection of bearing faults. Motor terminal signals have attracted much attention. However, not many papers in the literature address this issue as it relates to bearing faults, because of the difficulties in effective detection. In this research, an incipient bearing fault detection method for induction motors is proposed based on the analysis of motor terminal voltages and currents. The basic idea of this method is to detect changes in amplitude modulation between the spatial harmonics caused by bearing faults and the supply fundamental frequency. This amplitude modulation relationship can be isolated using the phase coupling property. An Amplitude Modulation Detector (AMD), developed from higher order spectrum estimation, correctly captures the phase coupling and isolates these modulation relationships. In this research, in-situ bearing damage experiments are conducted so that the accelerated life span of the bearing can be recorded and investigated. Experimental results shown in this dissertation are based on different power supplies, load levels, VSI control schemes, and motor operating conditions. Taking the mechanical vibration indicator as a reference for fault detection, the proposed method is demonstrated to be effective in detecting incipient bearing faults in induction motors. If motors are operating at near steady state conditions, then experimental results show that the bearing fault detection rate of the proposed approach is 100%, while no false alarms are recorded

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

Analysis of electrical signatures in synchronous generators characterized by bearing faults

Synchronous generators play a vital role in power systems. One of the major mechanical faults in synchronous generators is related to bearings. The popular vibration analysis method has been utilized to detect bearing faults for years. However, bearing health monitoring based on vibration analysis is expensive. One of the reasons is because vibration analysis requires costly vibration sensors and the extra costs associated with its proper installation and maintenance. This limitation prevents continuous bearing condition monitoring, which gives better performance for rolling element bearing fault detection, compared to the periodic monitoring method that is a typical practice for bearing maintenance in industry. Therefore, a cost effective alternative is necessary. In this study, a sensorless bearing fault detection method for synchronous generators is proposed based on the analysis of electrical signatures, and its bearing fault detection capability is demonstrated. Experiments with staged bearing faults are conducted to validate the effectiveness of the proposed fault detection method. First, a generator test bed with an in- situ bearing damage device is designed and built. Next, multiple bearing damage experiments are carried out in two vastly different operating conditions in order to obtain statistically significant results. During each experiment, artificially induced bearing current causes accelerated damage to the front bearing of the generator. This in-situ bearing damage process entirely eliminates the necessity of disassembly and reassembly of the experimental setup that causes armature spectral distortions. The electrical fault indicator is computed based on stator voltage signatures without the knowledge of machine and bearing specific parameters. Experimental results are compared using the electrical indicator and a vibration indicator that is calculated based on measured vibration data. The results indicate that the electrical indicator can be used to analyze health degradation of rolling element bearings in synchronous generators in most instances. Though the vibration indicator enables early bearing fault detection, it is found that the electrical fault indicator is also capable of detecting bearing faults well before catastrophic bearing failure