New Hybrid Sensorless Speed of a Non-Salient Pole PMSG Coupled to Wind turbine Using a Modified Switching Algorithm

©2019 ISA. Published by Elsevier Ltd. All rights reserved. his manuscript is made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence (CC BY-NC-ND 4.0). For further details please see: https://creativecommons.org/licenses/by-nc-nd/4.0/The paper focuses on the design of position and speed observers for the rotor of a non-salient pole permanent magnet synchronous generator (NSPPMSG) coupled to a wind turbine. With the random nature of wind speed this observer is required to provide a position and speed estimates over a wide speed range. The proposed hybrid structure combines two observers and a switching algorithm to select the appropriate observer based on a modified weighting coefficients method. The first observer is a higher-order sliding mode observer (HOSMO) based on modified super twisting algorithm (STA) with correction term and operates in the medium and nominal wind speed ranges. The second observer is used in the low speed range and is based on the rotor flux estimation and the control by injecting a direct reference current different to zero. The stability of each observer has been successfully assessed using an appropriate Lyapunov function. The simulation results obtained show the effectiveness and performance of the proposed observer and control scheme.Peer reviewe

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 control for limp-home mode of EV applications

PhD ThesisOver the past decade research into electric vehicles’ (EVs) safety, reliability and availability has become a hot topic and has attracted a lot of attention in the literature. Inevitably these key areas require further study and improvement. One of the challenges EVs face is speed/position sensor failure due to vibration and harsh environments. Wires connecting the sensor to the motor controller have a high likelihood of breakage. Loss of signals from the speed/position sensor will bring the EV to halt mode. Speed sensor failure at a busy roundabout or on a high speed motorway can have serious consequences and put the lives of drivers and passengers in great danger. This thesis aims to tackle the aforementioned issues by proposing several novel sensorless schemes based on Model Reference Adaptive Systems (MRAS) suitable for limp-home mode of EV applications. The estimated speed from these schemes is used for the rotor flux position estimation. The estimated rotor flux position is employed for sensorless torque-controlled drive (TCD) based on indirect rotor field oriented control (IRFOC). The capabilities of the proposed schemes have been evaluated and compared to the conventional back-Electromotive Force MRAS (back-EMF MRAS) scheme using simulation environment and a test bench setup. The new schemes have also been tested on electric golf buggies. The results presented for the proposed schemes show that utilising these schemes provide a reliable and smooth sensorless operation during vehicle test-drive starting from standstill and over a wide range of speeds, including the field weakening region. Employing these new schemes for sensorless TCD in limp-home mode of EV applications increases safety, reliability and availability of EVs

Current derivative estimation for sensorless motor drives

The work presented in this thesis aims to improve the performance of the Fundamental PWM sensorless control technique by proposing a new way to estimate current derivatives in the presence of high frequency oscillations. The Fundamental PWM technique offers performance across the entire speed range (including zero speed). The method requires current derivative measurements when certain PWM (Pulse Width Modulation) active and null vectors are applied to the machine. However the switching action of the active devices in the inverter and the associated large dv/dt result in current and current derivative waveforms being affected by high frequency oscillations which prevent accurate measurement of the current derivative. Other approaches have allowed these oscillations to decay before attempting to take a derivative measurement. This requires that the PWM vectors are applied to the machine for a time sufficient to allow the oscillations to decay and a derivative measurement to be made (the minimum pulse width). On some occasions this time is longer than the time a vector would have normally been applied for (for example when operating at low speed) and the vectors must be extended and later compensated. Vector extension introduces undesirable current distortion, audible noise, torque ripple and vibration. In this thesis the high frequency oscillations and their sources are investigated and a method of using Artificial Neural Networks to estimate current derivatives using only a short window of the transient current response is proposed. The method is able to estimate the derivative directly from phase current measurements affected by high frequency oscillations and thus allows a reduction in the minimum pulse width to be achieved (since it is no longer necessary to wait for the oscillations to fully decay) without the need for dedicated current derivative sensors. The performance of the technique is validated with experimental results

Current derivative estimation for sensorless motor drives

The work presented in this thesis aims to improve the performance of the Fundamental PWM sensorless control technique by proposing a new way to estimate current derivatives in the presence of high frequency oscillations. The Fundamental PWM technique offers performance across the entire speed range (including zero speed). The method requires current derivative measurements when certain PWM (Pulse Width Modulation) active and null vectors are applied to the machine. However the switching action of the active devices in the inverter and the associated large dv/dt result in current and current derivative waveforms being affected by high frequency oscillations which prevent accurate measurement of the current derivative. Other approaches have allowed these oscillations to decay before attempting to take a derivative measurement. This requires that the PWM vectors are applied to the machine for a time sufficient to allow the oscillations to decay and a derivative measurement to be made (the minimum pulse width). On some occasions this time is longer than the time a vector would have normally been applied for (for example when operating at low speed) and the vectors must be extended and later compensated. Vector extension introduces undesirable current distortion, audible noise, torque ripple and vibration. In this thesis the high frequency oscillations and their sources are investigated and a method of using Artificial Neural Networks to estimate current derivatives using only a short window of the transient current response is proposed. The method is able to estimate the derivative directly from phase current measurements affected by high frequency oscillations and thus allows a reduction in the minimum pulse width to be achieved (since it is no longer necessary to wait for the oscillations to fully decay) without the need for dedicated current derivative sensors. The performance of the technique is validated with experimental results

A comparison of saliency based sensorless control techniques for a PM machine

This thesis analyzes saliency-based sensorless control methods for AC surface mounted permanent magnet machines (PMSM), because PMSMs have features that make them attractive for use in industrial drives: small size, high efficiency, low maintenance, high dynamics, and high power density. The thesis focuses on four different HF injection sensorless methods, which utilize resistance and inductance based saliencies for position estimation: the measurement axis method, the eddy current resistance based saliency tracking method, the eddy current inductance based saliency tracking method, and the PWM switching frequency injection method. The emphasis is in the comparison of the four HF saliency tracking methods under various conditions such as steady state, load impact, speed reversal, and zero and low speed operation. The amplitude and frequency of the injection signals are also compared to choose the best HF injection signal for the four saliency tracking methods. The best sensorless control method using eddy current resistance based saliency is introduced and the experimental results confirm the expected advantages for this sensorless application. This thesis also describes the development and enhancement of current derivative measurement for saliency tracking methods, which uses the stator current transient response to the voltage vectors contained in the fundamental PWM sequence. Due to the HF switching oscillations caused by the switching of the IGBT and parasitic capacitance, the accuracy of the current measurement is reduced and requires a minimum vector time of approximately 6µs. A signal processing algorithm is proposed which uses current samples during the high frequency current oscillations, and can potentially reduce this minimum pulse time

Neue Implementierungsmethoden für eingebettete geberlose Motor-Controller basierend auf dem Einsatz von Multi-Core-Mikrocontrollern

Diese Arbeit behandelt den Einsatz von Multi-Core-Mikrocontrollern in softwarebasierten Motor-Controllern zur geberlosen Stromregelung von PMSM. Hierbei werden die Steigerung der Motor-Controller-Performance durch Parallelisierung und die Auswirkungen von Cross-Core-Interferenzen auf das zeitliche Verhalten von Motor-Controllern fokussiert. Es wird eine Generalisierung von geberlosen Stromregelungen durchgeführt, um die allgemeine Parallelisierbarkeit dieser Anwendungen zu beschreiben. Hierauf aufbauend wird gezeigt, unter welchen Rahmenbedingungen eine effektive Steigerung der Regelfrequenz durch Parallelisierung realisierbar ist. Durch die Konsolidierung dedizierter Motor-Controller in ein Multi-Core-System kann Hardware eingespart und dadurch der Energiebedarf um bis zu 50 % gesenkt werden. Eine solche Konsolidierung verursacht regelmäßig Cross-Core-Interferenzen. Um diesem Problem entgegenzuwirken, wird ein Verfahren vorgestellt, das die negativen Einflüsse dieser Seiteneffekte auf die Laufzeiten der Motor-Controller analysiert und quantifiziert. Hierauf aufbauend werden Strategien zur Reduktion der Interferenzen beschrieben und evaluiert. Durch die erzielten Ergebnisse werden Multi-Core-Mikrocontroller als Basis neuer Implementierungsmethoden für Motor-Controller erschlossen. Sie erweitern deren Design- und Implementierungsprozesse, um hier Multi-Core-Mikrocontroller durch Parallelisierung und Konsolidierung effektiv und effizient einzusetzen.This thesis addresses the use of multi-core microcontrollers in software-based motor controllers for the position sensorless control of PMSM. The focus is on increasing the motor controller performance through parallelization and on the effects of cross-core interferences on the temporal behaviour of motor controllers. A generalization of position sensorless current controls is carried out in order to describe the general possibilities to parallelize these applications. Building on this, it is shown under which conditions an effective increase in the control frequency can be achieved through parallelization. By consolidating dedicated motor controllers into one multi-core system, hardware can be saved to reduce energy costs by up to 50 %. Such consolidation causes cross-core interference on a regular basis. To address this problem, a procedure is presented that analyses and quantifies the negative influences of these side effects on the runtimes of the motor controllers. Based on this, strategies for reducing interference are described and evaluated. The results of this work open up multi-core microcontrollers as a base for new implementation methods for motor controllers. They expand the design and implementation processes of motor controllers in order to use multi-core microcontrollers effectively and efficiently through parallelization and consolidation