Zero Speed Rotor Position Estimator based on Sliding Mode Control for Permanent Magnet Synchronous Motor

The permImplementation of an algorithm based on SMC that uses a unique technique for the rotor position estimation of a PMSM for low and zero speeds, by using inherit motor effect called "Saliency". The work proves that the rotor position estimation is possible with the information that is present in the system under SMC due to the saliency effect. Therefore, there is no need to inject any signal into the machine, which causes the increment in the losses of the machine, or to design dynamic observers. The algorithm is implemented in a DSP controller and the tests with the complete hardware platform validate the proposal in open loop and in sensorless operation

Advanced Modeling of Anisotropic Synchronous Machine Drives for Sensorless Control

Synchronous machines are extensively used for home appliances and industrial applications thanks to their fast dynamic response, good overload capability and high energy density. A precise knowledge of the rotor position is required to control efficiently this kind of motors. In most of the applications resolvers or absolute encoders are installed on the rotor shaft. The employment of position sensors leads to significant drawbacks such as the increased size and cost of the system and a lower reliability of the drive, caused by additional hardware and cabling. In sensorless drives motor position is estimated and employed in the machine control. Thus, no position sensor is required by the drive and all the drawbacks entailed by the sensor are eliminated. Moreover, the position estimation could be useful for redundancy in case of system failures. Therefore, position estimation techniques are object of great interest in the electric drives field. Position estimation techniques can be divided into two main categories: methods that are suitable for medium or high speed and techniques suitable for low speed or standstill operations. In the former group the motor position is estimated through a reconstruction of the permanent magnet flux or back electromotive force (back-EMF). In case of synchronous reluctance machines it is possible to reconstruct the extended active flux or back-EMF. Stator voltages and currents measurements are needed for these reconstruction methods. Since these signals amplitude is proportional to the rotor speed, position estimation can be successfully performed only for medium and high speed machine operations. In the low speed range, sensorless schemes exploit the rotor magnetic anisotropy. Thus, position can be estimated only for anisotropic motors, i.e. synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motors (PMA-SynRM) and interior permanent magnet synchronous motors (IPMSM). The rotor anisotropy is recognized thanks to an high frequency voltage injection in the stator windings. Several injection techniques have been proposed, differing from the signal typology. In particular, high frequency sinusoidal or square-wave carriers are often applied. The position information is usually extracted from the current response through a heterodyning demodulation that entails the use of low pass filters in the position estimator, limiting its dynamic. The aim of the research was proposing a new algorithm to estimate the rotor position from the HF current response, getting rid of the demodulation and its weaknesses. Thus, the ellipse fitting technique has been proposed. Robustness against signal processing delay effects and a reduced number of required filters are the main advantages of this novel approach. The inverse problem related to the ellipse fitting is solved implementing a recursive least squares algorithm. The proposed ellipse fitting technique is not affected by signal processing delay effects, and it requires the tuning of only one parameter, called forgetting factor, making the studied method suitable for industrial application thanks to its minimal setup effort. Besides the ellipse fitting technique for rotor position estimation, two other topics have been studied: - Computation of self-sensing capabilities of synchronous machines. - Online incremental inductances identification for SynRM.Synchronous machines are extensively used for home appliances and industrial applications thanks to their fast dynamic response, good overload capability and high energy density. A precise knowledge of the rotor position is required to control efficiently this kind of motors. In most of the applications resolvers or absolute encoders are installed on the rotor shaft. The employment of position sensors leads to significant drawbacks such as the increased size and cost of the system and a lower reliability of the drive, caused by additional hardware and cabling. In sensorless drives motor position is estimated and employed in the machine control. Thus, no position sensor is required by the drive and all the drawbacks entailed by the sensor are eliminated. Moreover, the position estimation could be useful for redundancy in case of system failures. Therefore, position estimation techniques are object of great interest in the electric drives field. Position estimation techniques can be divided into two main categories: methods that are suitable for medium or high speed and techniques suitable for low speed or standstill operations. In the former group the motor position is estimated through a reconstruction of the permanent magnet flux or back electromotive force (back-EMF). In case of synchronous reluctance machines it is possible to reconstruct the extended active flux or back-EMF. Stator voltages and currents measurements are needed for these reconstruction methods. Since these signals amplitude is proportional to the rotor speed, position estimation can be successfully performed only for medium and high speed machine operations. In the low speed range, sensorless schemes exploit the rotor magnetic anisotropy. Thus, position can be estimated only for anisotropic motors, i.e. synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motors (PMA-SynRM) and interior permanent magnet synchronous motors (IPMSM). The rotor anisotropy is recognized thanks to an high frequency voltage injection in the stator windings. Several injection techniques have been proposed, differing from the signal typology. In particular, high frequency sinusoidal or square-wave carriers are often applied. The position information is usually extracted from the current response through a heterodyning demodulation that entails the use of low pass filters in the position estimator, limiting its dynamic. The aim of the research was proposing a new algorithm to estimate the rotor position from the HF current response, getting rid of the demodulation and its weaknesses. Thus, the ellipse fitting technique has been proposed. Robustness against signal processing delay effects and a reduced number of required filters are the main advantages of this novel approach. The inverse problem related to the ellipse fitting is solved implementing a recursive least squares algorithm. The proposed ellipse fitting technique is not affected by signal processing delay effects, and it requires the tuning of only one parameter, called forgetting factor, making the studied method suitable for industrial application thanks to its minimal setup effort. Besides the ellipse fitting technique for rotor position estimation, two other topics have been studied: - Computation of self-sensing capabilities of synchronous machines. - Online incremental inductances identification for SynRM

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

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

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

A Nonlinear Extended State Observer for Rotor Position and Speed Estimation for Sensorless IPMSM Drives

© 1986-2012 IEEE. Sensorless machine drives in vehicle traction frequently experience rapidly-changing load disturbance and demand fast speed dynamics. Without gain-scheduling or compensation, conventional quadrature phase-locked-loop (Q-PLL) is unable to accurately estimate the rotor position and speed for these systems. In this paper, a third-order nonlinear extended state observer (TNESO) is proposed for position and speed estimation for sensorless interior permanent magnet synchronous motor drives. TNESO has the power of nonlinear feedback and takes the advantages of fast convergence and disturbance rejection. An optimized parameter configuration method is deployed to extend the disturbance observation bandwidth of the TNESO. Both steady state and transient performance of TNESO are verified through the experimental tests. In comparison with the performance of conventional Q-PLL scheme, the proposed observer is proved to be capable of delivering higher precision of position and speed estimation against rapidly varying disturbance in wide operating range

Control of a nine-phase symmetrical PMSM with reduced rare earth material

The rising demand for high-power fault-tolerant applications such as wind generators and electric vehicles, alongside the desire to achieve better performance, have directed the interests of many research centres around the world towards electric drive configurations comprising AC machines with more than three stator phases. These so-called multiphase machines have become well recognized as an attractive alternative to the conventional three-phase machines and are used when the three-phase counterpart cannot provide a drive system with the desired performance. The Thesis examines advanced control possibilities for multiphase surface-mounted permanent magnet synchronous machines (PMSMs). Although it is well-known that permanent magnet machines are today the first choice in many applications and that their market is anticipated to catch up with the induction machines market in the near future, the main drawbacks of this machine type are the relatively high capital costs, the security of magnet supply and the environmental costs associated with the rear-earth magnet materials used in the rotor construction. This has motivated researchers to investigate methods to reduce the amount of rare earth material used in the construction of these machines. If the amount of permanent magnet material is reduced, this will inevitably result in a machine which produces lower electromagnetic tor que. On the other hand, the additional degrees of freedom, present in multiphase systems, can be exploited to inject, into the stator windings, harmonic current(s) to enhance the developed torque. This work analyses a new nine-phase symmetrical PMSM with two surface mounted magnet poles on the rotor with a shortened span. This simple design produces a highly non-sinusoidal back-electromotive force (back-EMF) comprising high third and fifth harmonic components. It is shown that these harmonic components can be utilised to boost the torque to near the value obtainable with full span magnets, provided a suitable control system is developed. The developed control algorithm is based on the well-known vector space decomposition (VSD) and classic field-oriented control methods. To test the developed control algorithm, phase domain machine model is presented first, for both sinusoidal and non-sinusoidal back-EMF distributions. To transform variables from one reference frame to another, the VSD and rotational transformations are used. The optimal ratios between fundamental and other harmonic current components are derived using the maximal torque-per-Ampere (MTPA) theory. It is shown that, by using optimal current injection, the electromagnetic torque can be improved by 36% with third harmonic only, and, up to 45% with a combination of the fundamental, the third and the fifth harmonics. Simulation results are validated in finite element method software and afterwards verified experimentally using an experimental prototype. Control of the PMSM is next expanded with position sensor fault-tolerant capability. For this purpose, the same EMF spectrum is used. When harmonic current elimination is performed in x-y subspace, remaining hth harmonic order back-EMF can be efficiently used for position angle and speed estimation. For the estimation purpose, phase-locked-loop method is employed. With estimated position/speed, a new control algorithm is devised, which combines control in two auxiliary subspaces with the control of the first plane. The third harmonic is, in combination with the fifth, used for the torque boost prior to the fault, while afterwards, the fifth EMF harmonic enables position estimation for position-sensorless control. Hence, previously stated maximal torque improvement is preserved until position sensor fault is detected, while afterwards machine continues to operate in position-sensorless mode still with partial enhancement of the torque. Control is verified experimentally. Finally, operation in the flux-weakening region is investigated. Because finding sets of multiple harmonic current references which maximize torque by taking into account voltage and current limits leads to a difficult problem to formulate, which is often impossible to solve analytically, the work presented here builds on (offline) numerical optimisation procedure. To obtain best performance, harmonics up to the (and including) fifth are considered. Limitation of voltage is achieved by comparing measured phase-to-phase voltage with maximal dc-link voltage, while thermal (RMS) constraint and inverter switch (peak) current constraint are taken into account by limiting the current. In such scenario, maximal reachable speed is much higher than the base speed, while respecting at the same time both machine and inverter constraints

Sensorless control of surface mounted permanent magnet machine using fundamental PWM excitation

This thesis describes the development of a sensorless control method for a surface mounted permanent magnet synchronous machine drive system. The saturation saliency in the machine is tracked from the stator current transient response to the fundamental space vector PWM (pulse width modulation) excitation. The rotor position and speed signals are obtained from measurements of the stator current derivative during the voltage vectors contained in the normal fundamental PWM sequence. In principle, this scheme can work over a wide speed range. However, the accuracy of the current derivative-measurements made during narrow voltage vectors reduces. This is because high frequency current oscillations exist after each vector switching instant, and these take a finite time to die down. Therefore, in this thesis, vector extension and compensation schemes are proposed which ensure correct current derivative measurements are made, even during narrow voltage vectors, so that any induced additional current distortion is kept to a minimum. The causes of the high frequency switching oscillations in the AC drive system are investigated and several approaches are developed to reduce the impact of these oscillations. These include the development of a novel modification to the IGBT gate drive circuit to reduce the requirement for PWM vector extension. Further improvements are made by modifications to the current derivative sensor design together with their associated signal processing circuits. In order to eliminate other harmonic disturbances and the high frequency noise appearing in the estimated position signals, an adaptive disturbance identifier and a tracking observer are incorporated to improve the position and speed signals. Experimental results show that the final sensorless control system can achieve excellent speed and position control performance

Comparison of shaft position estimation and correction techniques for sensorless control of surface mounted PM synchrononous motors

This thesis is a detailed study of how two error correction schemes affect the precision of shaft position estimation in state-observer techniques for sensorless control surface-mounted Permanent Magnet Synchronous Motors (PMSM), variance correction and variable PI regulation. A novel sensorless estimation technique based on Linear Kalman Filter (LKF) through constant variance correction is proposed and compared with the conventional Flux Linkage Observer (FLO) method and other state-estimation sensorless control techniques namely, Extended Kalman Filter (EKF), variable variance correction, Single Dimension Luenberger (SDL) observer and Full-Order Luenberger (FOLU) observer both through variable PI regulation. These five sensorless control techniques for PMSM are successfully implemented in the same lab-based hardware platform, i.e. full digital float-point-type DSP control inverter-fed PMSM system. Experiments are reported on each sensorless method covering position estimation, speed response, self-startup and load behaviour. Intensive analysis has also been carried out on the impact of error correction of estimated position on the steady/dynamic PMSM characteristics with different sensorless approaches. The experiment demonstrates that the novel Linear Kalman Filter can achieve the minimum average position estimation error throughout the electrical cycle of the five sensorless estimation techniques during no load operation at rated speed and also makes PMSM capable of self-startup for any initial rotor position except the dead area. A speed response experiment for LKF shows that individual speed estimation can be extracted directly from LKF state estimation for sensorless control PMSM. Experiments on the five sensorless methods proves that position error correction scheme is the dominating factor for state estimation sensorless control PMSM and better dynamic/steady control performance can be achieved using a variance correction scheme applied in EKF/LKF than with variable PI regulation applied in SDL/FOLU. The thesis also concludes that the novel Linear Kalman Filter is an optimised cost-effective sensorless estimation method for the PMSM drive industry compared with classic and Flux Linkage observers/Extended Kalman Filters