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EN
This paper present the scalar control method applied in an electric vehicle, witch use an induction motor for its drive, where the dSPACE MicroLabBox is used as a real time interface (RTI) for SIMULINK. At first we present the induction motor model in the dqo axis, and the control method, then we present the dynamic model of the vehicle. Finally, the figures show materials used, and the experimental results obtained by experiment software Control Desk.
PL
W artykule przedstawiono metodę sterowania skalarnego zastosowaną w pojeździe elektrycznym wykorzystującym do napędu silnik indukcyjny, gdzie dSPACE MicroLabBox jest używany jako interfejs czasu rzeczywistego (RTI) dla SIMULINK. Najpierw przedstawiamy model silnika indukcyjnego w osi dqo oraz sposób sterowania, następnie przedstawiamy model dynamiczny pojazdu. Wreszcie, rysunki przedstawiają użyte materiały i wyniki eksperymentalne uzyskane za pomocą oprogramowania doświadczalnego Control Desk.
EN
The article discusses the universal current sensor fault detection and compensation mechanism, which can be applied in three-phase power electronics (PE) symmetrical system. The mechanism is based on the assumption that a symmetrical system can be described using different components in the stationary reference frame. The solution given in article as a Cri-base detector was tested in electrical drives with induction motors (IMs) and permanent magnet synchronous motors (PMSMs). This study also proves that the same algorithm can work stable in active rectifier systems. Such an application of this detector has not been previously reported in the literature. The article describes the detection of various types of faults in different phases. The fault-tolerant voltage-oriented control (FTVOC) of an active rectifier is compared with previously described solutions for IMs and PMSMs. By analysing in various types of systems, the work proves the universality of the detector based on Cri markers.
EN
This article presents a new development of an indirect stator flux-oriented controller for sensorless speed induction motor drive utilising instantaneous and steady-state values, respectively, of a fictitious resistance symbolised as R_f. The dimension of the fictitious quantity, in this context, is the ohm, which is the difference between the stator d- and q-axis fictitious resistances. However, from the measurement of the stator voltage and currents of the machine, two independent resistance estimators are built. Therefore, the first is considered as a reference model of the induction machine (IM), and the second is considered as an adjustable model. Subsequently, the error between the states of the two models is used to drive a suitable adaptation mechanism that generates the estimation of the speed, for the adjustable model. Furthermore, the structure of the proposed estimator is free from stator resistance and eliminates the requirement of any flux computation. All the detailed simulation study is carried out in MATLAB/Simulink to validate the proposed method and to highlight the robustness and the stability of the proposed model reference adaptive system estimator.
EN
The paper presents a novel model predictive flux control (MPFC) scheme for three-level inverter-fed sensorless induction motor drive operated in a wide speed region, including field weakening. The novelty of the proposed drive lies in combining in one system a number of new solutions providing important features, among which are: very high dynamics, constant switching frequency, no need to adjust weighting factors in the predictive cost function, adaptive speed and parameter (stator resistance, main inductance) estimation. The theoretical principles of the optimal switching sequence predictive stator flux control (OSS-MPFC) method used are also discussed. The method guarantees constant switching frequency operation of a three-level inverter. For speed estimation, a compensated model reference adaptive system (C-MRAS) was adopted while for IM parameters estimation a Q-MRAS was developed. Simulation and experimental results measured on a 50 kW drive that illustrates operation and performances of the system are presented. The proposed novel solution of a predictive controlled IM drive presents an attractive and complete algorithm/system which only requires the knowledge of nominal IM parameters for proper operation.
EN
The paper presents research on the development of a line-start synchronous reluctance motor (LSSynRM) and line-start permanent magnet synchronous motor (LSPMSM) based on components of a mass-produced three-phase low-power squirrel cage induction motor (IM). The aim of the research was to modify the squirrel cage rotor structure for which the best functional parameters characterizing the steady state of the LSSynRM and LSPMSM were obtained, while meeting the additional requirements for asynchronous start-up. Field-circuit models of the LSSynRM and LSPMSM have been developed in the professional finite element method (FEM) package, MagNet, and applied in the design and optimization calculations of the considered machines. Experimental testing on the designed LSSynRM and LSPMSM prototypes were carried out. The obtained results were compared with the performance of the reference IM. The conclusions resulting from the comparative analysis of these three motors are given and proposals for further work are discussed.
EN
This paper deals with the effective design and implementation of the morphological analyser of Oriya, which is a morphologically rich language derived from Sanskrit. The most of the morphemes in Oriya coordinate with the root words in the form of suffixes. Information such as Part of Speech (PoS), Case-relation, number, person, tense, aspect and mood are all conveyed through morphological attachments to the root of nominal or verbal words. This makes morphological analyser and generator of Oriya words a challenging task which is very essential tool in the area of Machine Translation, Parser, Spell Checker, OriNet (WordNet for Oriya), PoS tagging etc. This paper elucidates the simple and efficient computational model for Oriya morphology based on finite state transducers.
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