Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications

Accurate angle representation from misplaced hall-effect switch sensors for low-cost electric vehicle applications

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis article presents an accurate method to determine the mandatory rotor position to control a permanent magnet synchronous machine from misplaced Hall-effect switch sensors. The main feature of this technique is the estimated speed from two consecutive edge transitions in the same phase to dodge the inaccurate information. Besides, when a new electrical cycle starts, a gradual compensation algorithm corrects the initial speed estimation to cancel the electrical angle error in order to prevent current distortions. Furthermore, a first-order Taylor series approximation estimates the rotor position from the compensated speed calculation, reducing the possible torque ripple and noise due to an inaccurate control strategy. The proposed method has been compared with other state-of-the-art approaches through simulation and experimental results obtained from a low-voltage powertrain, showing more straightforward implementation and delivering the best balance performance during steady-state and transient operation.Peer ReviewedPostprint (author's final draft

Harjattoman tasavirtamoottorin arviointi opto-mekaanisessa paikkasäätösovelluksessa

This thesis evaluates the applicability of a micro-sized brushless direct current (DC) mo- tor in an opto-mechanical positioning application. Brushless DC motors are electronically commutated motors that use permanent magnets to produce the airgap magnetic field. The motor is powered through an inverter or switching power supply which produces an AC electric current to drive each phase of the motor. Optimal current waveforms are determined by the motor controller based on the desired torque, speed or position requirements. The benefits of a brushless motor over conventional brushed DC motors are a high power to weight ratio, low noise and a long operating life. The purpose of this thesis is to find out the performance potential of such motors and determine methods to achieve it. Firstly, a motor model and an exact motor classification is presented. A literature review is made to discuss state of the art control methods and hardware configurations for dynamic position control. Based on the literature review, a control scheme with field-oriented control based torque control and cascaded PI controlled speed and position loops was selected for further evaluation. Experimental positioning tests were executed for two motors with different power transmission setups. Tests were performed with both, a hardware and software implemented, motor controllers. Results show promising performance. It was shown that the required acceleration is feasible with both, geared and direct drive, transmissions. Field-oriented control was shown as a well performing method to control torque but special caution was needed to implement a reliable position sensing solution in a small size as the control algorithm is intolerant for inaccurate and noisy position data. The conventional PI based position controller was effective in cases with no feedback related harmonics or motor related torque ripple but was not capable in handling ripple caused by a non-ideal system. Quality variances were seen between motors which were originated from mechanical defects and non-idealities in the stator structure. Further research is needed to achieve a better settling performance through filtering undesired feedback harmonics, better tuning and thus minimizing undesired vibrations.Tämän diplomityön tarkoituksena on arvioida pienikokoisen harjattoman tasavirtamoottorin soveltuvuutta opto-mekaaniseen paikkasäätösovellukseen. Harjattomat tasavirtamoottorit ovat elektronisesti ohjattuja moottoreita, joissa ilmavälin magneettivuo luodaan kestomagneeteilla. Moottorille syötetään virtaa taajuusmuuttajalta, joka muodostaa halutunlaisen vaihtovirran jokaiselle moottorin vaiheelle. Syötettävää virtaa ohjataan moottorinohjaimelta määritettyjen vääntö-, nopeus- ja paikkavaatimusten perusteella. Harjattoman DC-moottorin edut verrattuna perinteiseen harjalliseen DC-moottoriin ovat hyvä teho-painosuhde, hiljainen käyntiääni ja pitkä käyttöikä. Diplomityön tavoitteena on kartoittaa kyseisen moottorityypin suorituskyky paikkasäädössä ja tutkia keinoja saavuttaa haluttu taso. Alan tutkimuksessa ja kirjallisuudessa tunnettuja suorituskykyisiä säätömenetelmiä ja laite- sekä komponenttikokoonpanoja on koostettu kirjallisuuskatsauksessa. Tämän perusteella kokeellisiin testeihin valittiin säätöarkkitehtuuri vektorisäätöön perustuvalla virransäädöllä sekä PI-pohjaisilla nopeus- ja paikkasäätimillä. Kokeellisilla paikoitustesteillä arvioitiin kahden moottorin suorituskykyä erilaisilla voimansiirtovaihtoehdoilla. Testit suoritettiin sekä ohjelmistopohjaisella että sovelluskohtaiseen mikropiiriin toteutetulla laitepohjaisella säätimellä. Tulokset osoittavat että vaaditun kiihtyvyyden saavuttaminen on mahdollista sekä vaihteellisella että suoravetoisella voimansiirrolla. Vektorisäätö osoittautui suorituskykyiseksi virransäätömenetelmäksi, mutta moottorin asentomittauksen luotettava toteutus vaati erityishuomiota, sillä vektorisäätöalgoritmi on herkkä paikkadatan tarkkuudelle. PI-säätimillä toteutettu paikkasäätö osoittautui toimivaksi, mutta herkäksi moottorin epäideaalisuuksille sekä häiriöille takaisinkytkennässä. Moottoreiden välillä havaittiin laatueroja mekaanisissa toleransseissa ja staattorin rakenteessa. Lopullisen asettumisajan saavuttaminen vaatii lisätutkimusta. Erityishuomiota on kiinnitettävä harmonisten komponenttien suodattamiseen sekä systeemin säätöön, jotta ei-toivotut värinät saadaan minimoitua

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

Linear actuators for locomotion of microrobots

University of Technology, Sydney. Faculty of Engineering.The successful development of the miniaturisation techniques for electronic components and devices has paved the way for the miniaturisation in other technological fields. In the past two decades, the research achievements in micromechatronics have spurred fast development of micro machines and micro robotic systems. Miniature or micro actuators are the critical components to make these machines more dexterous, compact and cost effective. The main purpose of this dissertation is to develop micro actuators suitable for the locomotion of an in-pipe or endoscopic microrobot. The content of the thesis covers the selection of the actuation principle, robotic system design, actuator design and prototype construction, performance analysis, and design, analysis, and implementation of the appropriate drive control system. Among different types of actuation principles, piezoelectric and electromagnetic actuators are the two major candidates for the micro robotic systems. In order to find a suitable actuation principle for the desired robotic application, a comparative study was conducted on the scaling effects, attainable energy density, and dynamic performances of both types of actuators. Through the study, it was concluded that the electromagnetic actuator is more suitable for the endoscopic microrobot. Linear actuators are the common design used for the locomotion of microrobots due to many advantages compared to their rotational counterparts. Through a thorough review and comparison of the electromagnetic linear actuator topologies, a moving-coil tubular linear actuator was chosen as the first design due to its simplest structure. Via the magnetic circuit analysis and numerical magnetic field solutions, the actuator was designed for optimum force capability, and the electromagnetic force and the machine parameters of the actuator were predicted. According to the results obtained from the magnetic field analysis, the dynamic model of the actuation system with a driving control scheme was established and used in the actuation performance analysis of the robotic system. Based on the experience achieved through the first design, a new moving-magnet tubular linear actuator was designed. The methodology developed in the design and analysis of the moving-coil linear actuator was adopted for the moving-magnet actuator design. However, the optimal design is more complicated due to the multi-pole and multi-phase structure of the moving-magnet actuator. The electromagnetic force of the actuator was analysed under the condition of different excitation methods. An enhanced parameter computation method is proposed for predicting the actuator parameters. Based on the results of magnetic field analysis, a comprehensive dynamic model of the actuator was developed. Through the coupled field-circuit analysis, this model can predict accurately the dynamic performance of the actuator. The characteristics analysis shows that the performance of the moving-magnet actuator is much better than that of the moving-coil actuator. Two prototypes of the moving-magnet tubular linear actuator with different dimensions were constructed to verify the performance and the scaling theory. Various precision machining techniques were employed during the fabrication. The performances and parameters of the two different prototypes were measured and the results agree substantially with the theory. The brushless DC drive method was chosen for the driving control of the proposed linear actuator because of the compact circuit topology and simple implementation, which are two essential factors for micro applications. A sensorless control scheme based on the back EMF was developed as physical position sensors are not permitted in such a micro system. The control scheme was then applied to the locomotion control of the proposed microrobot. The system simulation shows that the control performances of both the actuator and microrobot are satisfactory. A dSPACE prototyping system based driving control hardware was designed and implemented to experimentally verify the control design. The experimental results agree substantially with the theoretical work

Design and Characterization for Regenerative Shock Absorbers

L'abstract è presente nell'allegato / the abstract is in the attachmen

Development of a knee prosthesis powered by electro-hydrostatic actuation

L'abstract è presente nell'allegato / the abstract is in the attachmen

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

Current commutation and control of brushless direct current drives using back electromotive force samples

Brushless DC machines (BLDC) are widely used in home, automotive, aerospace and military applications. The reason of this interest in different industries in this type of machine is due to their significant advantages. Brushless DC machines have a high power density, simple construction and higher efficiency compared to conventional AC and DC machines and lower cost comparing to permanent magnet AC synchronous machines. The phase currents of a BLDC machine have to commutate properly which is realised by using power semiconductors. For a proper commutation the rotor position is often obtained by an auxiliary instrument, mostly an arrangement of three Hall-effect sensors with 120 spatial displacement. In modern and cost-effective BLDC drives the focus is on replacing the noise sensitive and less reliable mechanical sensors by numerical algorithms, often referred to as sensorless or self-sensing methods. The advantage of these methods is the use of current or voltage measurements which are usually available as these are required for the control of the drive or the protection of the semiconductor switches. Avoiding the mechanical position sensor yields remarkable savings in production, installation and maintenance costs. It also implies a higher power to volume ratio and improves the reliability of the drive system. Different self-sensing techniques have been developed for BLDC machines. Two algorithms are proposed in this thesis for self-sensing commutation of BLDC machines using the back-EMF samples of the BLDC machine. Simulations and experimental tests as well as mathematical analysis verify the improved performance of the proposed techniques compared to the conventional back-EMF based self-sensing commutation techniques. For a robust BLDC drive control algorithm with a wide variety of applications, load torque is as a disturbance within the control-loop. Coupling the load to the motor shaft may cause variations of the inertia and viscous friction coefficient besides the load variation. Even for a drive with known load torque characteristics there are always some unmodelled components that can affect the performance of the drive system. In self-sensing controlled drives, these disturbances are more critical due to the limitations of the self-sensing algorithms compared to drives equipped with position sensors. To compensate or reject torque disturbances, control algorithms need the information of those disturbances. Direct measurement of the load torque on the machine shaft would require another expensive and sensitive mechanical sensor to the drive system as well as introducing all of the sensor related problems to the drive. An estimation algorithm can be a good alternative. The estimated load torque information is introduced to the self-sensing BLDC drive control loop to increase the disturbance rejection properties of the speed controller. This technique is verified by running different experimental tests within different operation conditions. The electromagnetic torque in an electrical machine is determined by the stator current. When considering the dynamical behaviour, the response time of this torque on a stator voltage variation depends on the electric time constant, while the time response of the mechanical system depends on the mechanical time constant. In most cases, the time delays in the electric subsystem are negligible compared to the response time of the mechanical subsystem. For such a system a cascaded PI speed and current control loop is sufficient to have a high performance control. However, for a low inertia machine when the electrical and mechanical time constants are close to each other the cascaded control strategies fail to provide a high performance in the dynamic behavior. When two cascade controllers are used changes in the speed set-point should be applied slowly in order to avoid stability problems. To solve this, a model based predictive control algorithm is proposed in this thesis which is able to control the speed of a low inertia brushless DC machine with a high bandwidth and good disturbance rejection properties. The performance of the proposed algorithm is evaluated by simulation and verified by experimental results as well. Additionally, the improvement on the disturbance rejection properties of the proposed algorithm during the load torque variations is studied. In chapters 1 and 2 the basic operation principles of the BLDC machine drives will be introduced. A short introduction is also given about the state of the art in control of BLDC drives and self-sensing control techniques. In chapter 3, a model for BLDC machines is derived, which allows to test control algorithms and estimators using simulations. A further use of the model is in Model Based Predictive Control (MBPC) of BLDC machines where a discretised model of the BLDC machine is implemented on a computation platform such as Field Programmable Gate Arrays (FPGA) in order to predict the future states of the machine. Chapter 4 covers the theory behind the proposed self-sensing commutation methods where new methodologies to estimate the rotor speed and position from back-EMF measurements are explained. The results of the simulation and experimental tests verifies the performance of the proposed position and speed estimators. It will also be proved that using the proposed techniques improve the detection accuracy of the commutation instants. In chapter 5, the focus is on the estimation of load torque, in order to use it to improve the dynamic performance of the self-sensing BLDC machine drives. The load torque information is used within the control loop to improve the disturbance rejection properties of the speed control for the disturbances resulting from the applied load torque of the machine. Some of the machine parameters are used within speed and load torque estimators such as back-EMF constant Ke and rotor inertia J. The accuracy with which machine parameters are known is limited. Some of the machine parameters can change during operation. Therefore, the influence of parameter errors on the position, speed and load torque is examined in chapter 5. In Chapter 6 the fundamentals of Model based Predictive Control for a BLDC drive is explained, which are then applied to a BLDC drive to control the rotor speed. As the MPC algorithm is computationally demanding, some enhancements on the FPGA program is also introduced in order to reduce the required resources within the FPGA implementation. To keep the current bounded and a high speed response a specific cost function is designed to meet the requirements. later on, the proposed MPC method is combined with the proposed self-sensing algorithm and the advantages of the combined algorithms is also investigated. The effects of the MPC parameters on the speed and current control performance is also examined by simulations and experiments. Finally, in chapter 7 the main results of the research is summarized . In addition, the original contributions that is give by this work in the area of self-sensing control is highlighted. It is also shown how the presented work could be continued and expanded