Ce travail de recherche s'intéresse à la commande sans capteur mécanique du moteur synchrone à aimants permanents (MSAP) à pôles saillants, particulièrement en basse vitesse, avec détection de la position initiale du rotor. Après une présentation des techniques et approches qui ont initié nos travaux, en terme d'estimation de la vitesse et/ou de la position, nous avons choisi celles qui présentent plus d'intérêt de point de vue stabilité, robustesse, précision et simplicité d'implémentation. La première approche est basée sur le Système Adaptatif avec Modèle de Référence (MRAS). Quant à la deuxième, elle est réalisée autour d'un observateur non-linéaire pour l'estimation de la position et de la vitesse du MSAP à pôles saillants. Les deux techniques d'observation de la vitesse sont associées à une commande par orientation du flux rotorique avec la technique MLI vectorielle. Pour détecter la position initiale du rotor, nous avons utilisé une nouvelle approche qui permet d'estimer cette position avec une incertitude de ±5° mécanique. Cette nouvelle approche est basée sur l'application de signaux tests aux bornes des phases statoriques du MSAP. Des résultats de simulation et expérimentaux sont présentés tout au long de ces travaux pour valider les études théoriques de la commande vectorielle sans capteur mécanique du MSAP. Enfin, nous avons étudié et analysé les performances de la commande tolérante aux défauts sans capteur mécanique du MSAP en présence de défaillances de types transistors à l'état-off. / This research focuses on the sensorless vector control of a salient pole permanent magnet synchronous motor (PMSM), particularly at low speed, with detection of the initial rotor position. In first step, an overview of the state of the art concerning the estimation of the rotor speed as well as the initial rotor position of PMSM is addressed. From such a study, we have adopted an interesting strategy based on the model reference adaptive system (MRAS). The second step in this research consists in studying the performances and the feasibility of a non-linear observer for closed-loop vector control of salient pole PMSM. The MRAS technique as well as the non-linear observer is associated to a vector control scheme based on the field oriented strategy with space vector pulse width modulation (SVPWM). To detect the initial rotor position, we have proposed a new approach which estimates the position with a resolution of ±5° mechanical degrees. This new approach is based on applying short voltage pulses to the stator winding of salient pole PMSM. Several simulation and experimental results are presented to confirm the theoretical studies of the sensorless vector control of the salient pole PMSM drive. Finally, we have analyzed the performances of the sensorless speed fault tolerant control (FTC) of salient pole PMSM under failures related to the voltage source inverter (open circuit fault). The experimental results obtained based on the proposed techniques using nonlinear and MRAS observers have been improved in term of the reliability and allow a continuous operation of the salient pole PMSM drive even when it is supplied with two inverter legs.

Permanent magnet synchronous machine drives are used more often. Although, synchronous machines drive also suffer from possible faults. This thesis is focused on the detection of the three-phase synchronous motor winding faults and the detection of the drive control loop sensors' faults. Firstly, a model of the faulty winding of the motor is presented. Effects of the inter-turn short fault were analyzed. The model was experimentally verified by fault emulation on the test bench with an industrial synchronous motor. Inter-turn short fault detection algorithms are summarized. Three existing conventional winding fault methods based on signal processing of the stator voltage and stator current residuals were verified. Three new winding fault detection methods were developed by the author. These methods use a modified motor model and the extended Kalman filter state estimator. Practical implementation of the algorithms on a microcontroller is described and experimental results show the performance of the presented algorithms in different scenarios on test bench measurements. Highly related motor control loop sensors fault detection algorithms are also described. These algorithms are complementary to winding fault algorithms. The decision mechanism integrates outputs of sensor and winding fault detection algorithms and provides an overall drive fault diagnosis concept.

The diploma thesis focuses on manufacturing carbon fiber and epoxy composite material using filament winding method. Material properties of manufactured composite are ap-proximated using analytical and numerical homogenization models. Calculated material properties are applied to design and evaluate reserve factor of retaining sleeve for high speed brushless permanent magnet synchronous motor. Margin of safety of designed rotor is evaluated using composite failure criteria. Test stand for both static and dynamic testing is designed, static test stand is manufactured and assembled. Static strength test is carried out.

This thesis deals with the elaboration of The Permanent Magnet Synchronous Motor and the calculation of its parameters. In the first part, the construction and used permanent magnets of this motor are listed here. The next part of the thesis contains a short overview of the stator windings, the calculation of the winding factors and calculation of the basic parameters of the stator winding. The calculation of the magnetic induction in the air gap is also illustrated here. The result is recalculated by using the Carter factor and then the value of the first harmonics of air-gap flux density is determined. The result is compared with the analysis in the program FEMM. The next part of the thesis is creating a comprehensive overview of the machine using a replacement circuit diagram and phasor diagrams. Finally, the thesis contains model created in RMxprt and ANSYS Maxwell. The results of the model analysis are compared with the analytical calculation

The Permanent Magnet Synchronous Motor (PMSM, also known as the servo motor) is a crucial component within robotic servo systems. To optimally respond to the torque demands sent from the high-level motion controller, the PMSM current controller must track the reference with speed and precision. Nevertheless, the operation of servo motors could be compromised due to the nonlinearity of flux linkage and inaccuracies in parameters induced by unpredictable fluctuations in temperature. This Master’s thesis proposes a novel Robust Nonlinear Deadbeat Predictive Current Control (RN-DPCC) scheme to counter these challenges effectively. The nonlinear mappings between flux linkage and current on the dq-axis are established using polynomial fitting based on experimental data. Furthermore, the Nonlinear Deadbeat Predictive Current Control (N-DPCC) is derived using nonlinear feedforward. Meanwhile, Delayed Integral Action (DIA) is introduced as a robustness-enhancing measure for N-DPCC, thus evolving it into the Robust N-DPCC (RN-DPCC). Compared to conventional Integral Action (IA), DIA effectively curtails overshoot triggered by integral error and accelerates the current transient without incorporating additional tunable parameters. Numerical simulations that leverage the mathematical modeling of the converter and nonlinear PMSM are implemented using fundamental blocks in Simulink, which replicates the actual experimental setup employed within the Motor Control Lab at ABB Corporate Research. The effectiveness of employing nonlinear feedforward compensation is confirmed through a comparative analysis of the simulation results from N-DPCC and conventional Deadbeat Predictive Current Control (DPCC). The enhancements in transient response brought about by DIA are demonstrated through a comparison of RNDPCC and N-DPCC with IA. The robustness of RN-DPCC is demonstrated by comparing it with N-DPCC under conditions where parameter inaccuracies are present. / Den permanenta magnet-synkronmotorn (PMSM, även känd som servomotorn) är en avgörande komponent inom robotiserade servosystem. För att optimalt kunna reagera på momentkraven som skickas från högnivårörelsekontrollern måste PMSM-strömregulatorn följa referensen med hastighet och precision. Trots detta kan driften av servomotorer påverkas av ickelinjäriteter i flödeslänkningen och felaktigheter i parametrar som orsakas av oförutsägbara temperaturfluktuationer. Denna magisteravhandling föreslår en ny robust icke-linjär deadbeat-prediktiv strömreglering (RN-DPCC) för att effektivt hantera dessa utmaningar. De icke-linjära avbildningarna mellan flödeslänkning och ström på dq-axeln etableras med hjälp av polynomisk anpassning baserat på experimentella data. Dessutom härleds den ickelinjära deadbeat-prediktiva strömregleringen (N-DPCC) med hjälp av Ickelinjär feedforward. Samtidigt introduceras fördröjd integralåtgärd (DIA) som en robusthetsförbättrande åtgärd för N-DPCC, vilket förvandlar den till Robust N-DPCC (RN-DPCC). Jämfört med konventionell integralåtgärd (IA) minskar DIA effektivt överhäng som utlöses av integralfel och accelererar strömövergången utan att införa ytterligare justerbara parametrar. Numeriska simuleringar som utnyttjar den matematiska modelleringen av omvandlaren och den icke-linjära PMSM implementeras med hjälp av grundläggande block i Simulink, vilket återskapar den faktiska experimentella uppställningen som används i Motor Control Lab vid ABB Corporate Research. Effektiviteten i att använda icke-linjär framåtmatningskompensation bekräftas genom en jämförande analys av simulationsresultaten från N-DPCC och konventionell deadbeat-prediktiv strömreglering (DPCC). Förbättringarna i transientrespons som DIA medför demonstreras genom en jämförelse av RN-DPCC och NDPCC med IA. Robustheten hos RN-DPCC demonstreras genom att jämföra den med N-DPCC under förhållanden där parameterfel förekommer.

Model predictive control is a popular research focus in electric motor control as it allows designers to specify optimization goals and exhibits fast transient response. Availability of faster and more affordable computers makes it possible to implement these algorithms in real-time. Real-time implementation is not without challenges however as these algorithms exhibit high computational complexity. Field-programmable gate arrays are a potential solution to the high computational requirements. However, they can be time-consuming to develop for. In this thesis, we present a methodology that reduces the size and development time of field-programmable gate array based fixed-point model predictive motor controllers using automated numerical analysis, optimization and code generation. The methods can be applied to other domains where model predictive control is used. Here, we demonstrate the benefits of our methodology by using it to build a motor controller at various sampling rates for an interior permanent magnet synchronous motor, tested in simulation at up to 125 kHz. Performance is then evaluated on a physical test bench with sampling rates up to 35 kHz, limited by the inverter. Our results show that the low latency achievable in our design allows for the exclusion of delay compensation common in other implementations and that automated reduction of numerical precision can allow the controller design to be compacted. / Thesis / Master of Applied Science (MASc)