Prädiktive Regelung und Finite-Set-Beobachter für Windgeneratoren mit variabler Drehgeschwindigkeit

This dissertation presents several model predictive control (MPC) techniques and finite-position-set observers (FPSOs) for permanent-magnet synchronous generators and doubly-fed induction generators in variable-speed wind turbines. The proposed FPSOs are novel ones and based on the concept of finite-control-set MPC. Then, the problems of the MPC techniques like sensitivity to variations of the model parameters and others are investigated and solved in this work.Die vorliegende Dissertation stellt mehrere unterschiedliche Verfahren der modellprädiktiven Regelung (MPC) und so genannte Finite-Position-Set-Beobachter (FPSO) sowohl für Synchrongeneratoren mit Permanentmagneterregung als auch für doppelt gespeiste Asynchrongeneratoren in Windkraftanlagen mit variabler Drehzahl vor und untersucht diese. Für die Beobachter (FPSO) wird ein neuartiger Ansatz vorgestellt, der auf dem Konzept der Finite-Control-Set-MPC basiert. Außerdem werden typische Eigenschaften der MPC wie beispielsweise die Anfälligkeit gegenüber Parameterschwankungen untersucht und kompensiert

Dynamic Performance Analysis of a Five-Phase PMSM Drive Using Model Reference Adaptive System and Enhanced Sliding Mode Observer

This paper aims to evaluate the dynamic performance of a five-phase PMSM drive using two different observers: sliding mode (SMO) and model reference adaptive system (MRAS). The design of the vector control for the drive is firstly introduced in details to visualize the proper selection of speed and current controllers’ gains, then the construction of the two observers are presented. The stability check for the two observers are also presented and analyzed, and finally the evaluation results are presented to visualize the features of each sensorless technique and identify the advantages and shortages as well. The obtained results reveal that the de-signed SMO exhibits better performance and enhanced robustness compared with the MRAS under different operating conditions. This fact is approved through the obtained results considering a mismatch in the values of stator resistance and stator inductance as well. Large deviation in the values of estimated speed and rotor position are observed under MRAS, and this is also accompanied with high speed and torque oscillations

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

Investigation of traction motor control systems for electric vehicle applications.

Masters Degree. University of KwaZulu-Natal, Durban.Electric vehicles are a promising solution to the current pollution and greenhouse gas issues faced by the transport sector. As such, the traction motor control system of an electric vehicle is worthy of investigation. Direct torque and indirect field-oriented control are commonly applied control techniques, enabling advanced control of the induction and permanent magnet synchronous motors currently used in most electric vehicles being produced. Various improvements have been made to current traction motor control schemes to reduce ripple, improve parameter insensitivity, and increase powertrain efficiency. Consequently, the objective of the research conducted is to contribute to the field of electric vehicle powertrains through comprehensive investigations into the suitability and performance of direct torque and indirect field-oriented control in the traction motor control system of an electric vehicle. A four-stage simulation-based investigation was undertaken, with five motor control techniques initially assessed, which were conventional direct torque and field-oriented control, two space vector modulation-based direct torque control systems and fuzzy logic-based direct torque control. Results from the first stage of the simulation-based study highlighted expected issues with conventional direct torque control and showed that fuzzy logic-based direct torque control and space vector modulational-based direct torque control with closed-loop torque and flux control present promising solutions for use in the traction motor control system of an electric vehicle. Extensions of the simulation-based investigation in stages two and three included the integration and assessment of field-weakening control and sensorless speed estimation. Furthermore, stage four concluded the investigation with an essential analysis of a complete control mechanism in realistic urban and highway driving conditions. The fourth stage utilised sections of the New York City Cycle and Highway Fuel Economy Test cycle, with a simulated vehicle load. The complete study indicated that space vector modulation-based direct torque control with closed-loop torque and flux control performs suitably for electric vehicle applications, providing favourable speed, torque, current and stator flux results with a faster computation time than some comparable control options. The comprehensive investigation extends current literature and forms a basis for further investigation in the field of traction motor control systems for electric vehicle applications

Model predictive MRAS estimator for sensorless induction motor drives

Ph. D. ThesisThe project presents a novel model predictive reference adaptive system (MRAS) speed observer for sensorless induction motor drives applications. The proposed observer is based on the finite control set-model predictive control principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS observers. Extensive simulation and experimental tests have been carried out to evaluate the performance of the proposed observer. Both the simulation and the experimental results show improved performance of the MRAS scheme in both open and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller. However, some of the experimental results show oscillations in the estimated rotor speed, especially at light loading conditions. Furthermore, due to the use of the voltage equation in the reference model, the scheme remains sensitive, to a certain extent, to the variations in the machine parameters. Therefore, to reduce rotor speed oscillations at light loading conditions, an adaptive filter is employed in the speed extraction mechanism, where an adaptation mechanism is proposed to adapt the filter time constant depending on the dynamic state of the system. Furthermore, a voltage compensating method is employed in the reference model of the MP-MRAS observer to address the problems associated with sensitivity to motor parameter variation. The performance of the proposed scheme is evaluated both experimentally and by simulation. Results confirm the effectiveness of the proposed scheme for sensorless speed control of IM drives

Dahlin-based fast and robust current control of a PMSM in case of low carrier ratio

The low ratio of sampling frequency to electrical frequency (carrier ratio) is a challenging issue for applications, such as high-speed or high-power drives. In fact, high-speed drives have high fundamental frequency and high-power drives have low switching (sampling) frequency, leading to the same control challenges of having high dynamic and stability with a limited number of control actions in one period. Parameters mismatch occurs due to the converter non-linearities, deadtimes, temperature change, and saturation; hence, providing robust control is a key challenge. This paper starts reviewing the problems of controlling machines with a few switching instances per fundamental period and an analysis of the state-of-the-art current control strategies for permanent magnet synchronous motors (PMSMs). Three different control schemes are analyzed. The discrete-time PI current controller is providing good robustness, while the dynamic performance may not be sufficient for some applications. Second, the deadbeat control offers very fast dynamic performance but is weak under parameter mismatch. The novel application of the Dahlin controller offers a tradeoff between performance and stability. The control algorithms are evaluated based on the stability, robustness, and dynamic and steady-state performances. Their performance and sensitivity to parameter variation are analyzed through simulations, and the experimental measurements are proving the results

Maximising Utilisation of the DC-Link Voltage in the Field Weakening Region for AC Motor Drives

PhD ThesisMost standard electric drives have two operational regions: the constant torque region and field weakening region. In order to increase the power level at the field-weakening region, the phase voltage must be increased. The phase voltage, however, is a function of the inverter input voltage and the control scheme that is applied to the inverter. Several methods have been applied to optimise the stator voltage modulation to maximise the power level at the field-weakening region. These methods suffer from fake voltage extension, which produce high current ripples, and a step reduction of motor currents in the transient area from the constant torque region to the field-weakening region. Adding extra regulators for these methods was proposed, but this still would not show any significant improvement in electric drive performance and increase the additional complexity of the closed-loop control system. During the course of this research, several control schemes based on mathematical modelling and voltage feedback mechanism are proposed to tackle the aforementioned issues. In the proposed novel methods, flux-producing current is designed based on the position of the stator voltage vector to push the stator voltage to the hexagonal voltage boundary. This consequently causes a smooth transition from the constant torque region to the field-weakening region, and it also increases the output torque and power of the electric machine without applying extra controllers or producing a step reduction on the d-axis current. The capabilities of the proposed schemes have been evaluated and compared to conventional model-based and closed-loop voltage algorithms by using MATLAB simulation and an experimental test set-up. This research also developed and proposed two parameter estimation techniques based on EKF and combined MRAS-KF to improve the accuracy of online estimation techniques. The performance of developed estimation schemes was investigated by using MATLAB simulation and a plant emulator-based setup

Model predictive control: an effective control approach for high performance induction machine drives

Induction machine drives with various configurations are getting a lot of attention in several industrial applications. Due to this increasing demand in industrial applications, the significance of developing effective control approaches for obtaining a high dynamic performance from the induction machine drives became essential. Up to the present time, the control of induction machine drives using power converters has been based on the principle of mean value, using pulse width modulation with linear controllers in a cascaded structure. Recent research works have demonstrated that it is possible to use Predictive Control to control induction machine drives with the use of power converters, without using modulators and linear controllers. This new approach will have a strong impact on control in power electronics in coming decades. The advantages of Predictive Control are noticed through the ability to consider a multi-objective case within the model, easy inclusion of non-linearities within the model, simple treatment of system constraints, easy of digital implementation, and flexibility of including modifications and extension of control horizons according to the required applications. Upon this, the research presented in this thesis concerns with developing different control topologies for various configurations of induction machine drives based on finite control set model predictive control (FCS-MPC) principle, which actuates directly the switch states of the voltage source inverter (VSI). In addition, for enhancing the robustness of the induction machine drives, different sensorless approaches are utilized and tested for validations. The first topology of induction machine drives that has been studied is the induction motor (IM) drive. An effective model predictive direct torque control (MP DTC) approach is used to control the torque and stator flux of the motor through the utilization of an effective cost function, through which the understanding and comparing implementation variants and studying convergence and stability issues can be easily investigated. The speed sample effect on the control variants and overall performance of the proposed MP DTC is analyzed, which enables the understanding of the real base principle of DTC, as well as why and when it works well. Two different sensorless procedures for estimating the speed and rotor position are used by the proposed MP DTC approach; the first utilizes a model reference adaptive system (MRAS) observer, while the other exploits the prediction step during the implementation of proposed MP DTC to get the speed information through performing a linear extrapolation of the speed values starting from the last two estimated samples. Extensive simulation and experimental tests have been carried out to validate the effectiveness of both sensorless approaches in achieving precise tracking of speed commands for a wide range of variations. For enhancing the robustness of proposed MP DTC, the stator flux as a control variable is replaced with controlling the flow of the reactive power through the induction motor drive. As the reactive power is a measured quantity compared with the estimated value of stator flux, thus, the sensitivity of the control against parameters variation is limited, and this confirmed through the obtained results from both simulation and experimental tests. In addition, an effective alternative approach to the MP DTC is presented, which based on controlling the instantaneous values of the active and reactive powers of the IM drive based on model predictive principle, instead of controlling the torque and flux as in MP DTC. This technique has the advantage that all controlled variables are became measured quantities (active and reactive powers), thus the estimation problems that commonly present in classic DTC schemes are effectively limited. For the last two control approaches (MP DTC reactive power control, and MP IPCactive and reactive power control), the sensorless that utilizes the predictive feature is also adopted. Obtained results via simulation and experiments confirm the feasibility of the two alternatives control procedures in obtaining a robust dynamic response of IM drive. To limit the accompanied ripple contents in the controlled values of electromagnetic torque and stator flux of induction motor, an effective ripple reduction technique has been presented. The technique is based on the derivation of the optimal value for the weighting factor (w_f) used in the cost function. A detailed mathematical derivation of the optimal value of w_f is introduced based on the analysis of torque and flux ripples behaviors. The proposed ripple reduction technique has been validated via simulation utilizing Matlab/Simulink software, and experimentally tested using a fast control prototyping dSpace 1104 board. In addition, the prediction step based sensorless approach is adopted during implementation. The performance of the IM drive using the proposed approach is compared with the results obtained from MP DTC approach that uses an arbitrary value of w_f. The comparison confirms the validity of the proposed ripple reduction procedure in reducing the ripple contents in the controlled variables while preserving the permissible computation burdens during the implementation. The FCS-MPC principle is also utilized to control the current of induction motor as an alternative to classic field oriented control (FOC), the proposed model predictive current control (MPCC) approach belongs to the class of the hysteresis predictive control (for limiting the switching frequency) as the MPCC is triggered by the exceeding of the error of a given threshold. In addition, a sensorless drive is achieved by including an effective Luenberger observer (LO) for precise estimation of rotor flux vector together with stator current, speed and load torque. The stator currents are estimated to eliminate the accompanied noise in their values when they are directly measured, thus the currents noise during prediction is limited. An effective pole placement procedure for the selection of observer gains has been adopted. The procedure is based on shifting the poles of the observer to the left of the motor poles in the complex (s-plane) with low imaginary part, so that the stability of the observer is enhanced for wide speed range. The feasibility of the sensorless MPCC for IM drive is confirmed through the obtained simulation and experimental results. The second topology of induction machine drives that has been studied is the doubly fed induction motor (DFIM) drive. An effective model predictive direct torque control (MP DTC) algorithm is developed for controlling the torque and rotor flux of DFIM drive. In addition, an effective sensorless approach is presented, which estimates the speed and rotor position in an explicit way without the need for involving the flux in the estimation process, thus the effect of parameters variation on the overall performance of the sensorless observer is effectively limited, this has been approved through the obtained results that are performed for a wide speed range from sub-synchronous to super-synchronous speed operation. During the operation, the stator resistance and magnetizing inductance values are changed from their original values to study the variation effect on the observer performance. Matlab/Simulink software and a prototyping dSpace 1104 control board are used to validate the effectiveness of proposed sensorless MP DTC approach through simulation and experiments, respectively. The results proof the robustness of the proposed sensorless approach and its ability to achieve precise estimation of the speed and rotor position. The third topology of induction machine drives that has been studied is the doubly fed induction generator (DFIG). A detailed analytical derivation for the proposed model predictive direct power control (MP DPC) approach for DFIG is presented, which as a sequence considered as a transposed control approach from the MP DTC used before for doubly fed induction motor (DFIM). A sensorless approach based on model reference adaptive system (MRAS) observer is adopted for estimating the speed and rotor position. Both simulation using Matlab/Simulink software and experimental test using a prototyping dSpace 1104 control board have tested the dynamic performance of the drive. Obtained results affirm the feasibility of the proposed MP DPC approach in achieving a decoupled control of active and reactive powers for DFIG. In summary, it can be said that the proposed model predictive control approaches have proved their ability in achieving high dynamic performance for different topologies of induction machine drives. In addition, the proposed sensorless techniques have confirmed their effectiveness for a wide range of speed variations. All of this are approved and validated through extensive simulation and experimental tests