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In this paper, a new synchronous machine model is developed for electromagnetic transients program type simulations. The stator circuit is expressed in the abc phase domain. The machine model is represented as a Norton equivalent with a current source in parallel with a constant Norton admittance. The machine equations are reformulated so that the computational effort required for the modeling of the machine is reduced. Test studies demonstrate the accuracy of the proposed synchronous machine model and show that the proposed model is computationally more efficient than the existing constant conductance phase domain model and voltage-behind-reactance model. [ABSTRACT FROM AUTHOR]

Switched reluctance machines (SRMs) are witnessing increased interests and applications in the industry and scientific communities thanks to the advantages of rigid structures, high reliability and robustness, the absence of permanent magnets, fast dynamic response, and low manufacturing cost. SRMs have become a feasible and popular alternative to conventional electric machines, such as induction machines and permanent magnet machines, with variable speed drives in many applications. Since improving the electromagnetic and thermal performances of an SRM at the design stage is of significant value, this paper presents an in-depth literature review on the status and potential trends of the technology pertinent to the design and optimization of SRMs in the following aspects: the mathematical modeling of the electromagnetic and thermal fields in SRMs, the enhancement of the performances in terms of the torque ripple, acoustic noise, efficiency, and torque density, and the multiobjective design optimization incorporating all the above factors. Finally, the presence of SRMs and their design considerations for specific applications in electric vehicles, aircraft and aerospace systems, wind generators, high speed, and energy storage systems are extensively discussed in this paper. The existing approaches advancing the SRM technologies are systematically and comprehensively summarized and compared for each category. [ABSTRACT FROM AUTHOR]

In this paper, the model predictive current control is introduced in the semicontrolled open-winding permanent magnet synchronous motor (OW-PMSM) generation system with a common dc bus to suppress the zero-sequence current for the first time. Particularly, the basic voltage vectors of the semicontrolled OW-PMSM, which are synthesized by the three-phase full-controlled converter and the three-phase uncontrollable diode bridge, is analyzed and their influences on the zero-sequence current are investigated for the first time in this paper. Then the current-error-based cost function that includes dq-axis current error and zero-sequence current error is designed to evaluate all the voltage vectors. Moreover, to further improve the steady-state control performance of the whole generation system, a zero-sequence current suppression method based on the uncontrollable side voltage vector adjustment, which has the advantage of low computation burden, is developed. In this method, two voltage vectors of the controllable converter are applied during one control period. Based on the distribution character of the basic voltage vector in the semicontrollable OW-PMSM generation system, the first voltage vector is selected according to the three-phase current direction to adjust equivalent vector of the uncontrollable diode bridge, whereas for the second voltage vector, the selection method based deadbeat voltage vector sector is designed to reduce the range of the candidate voltage vector. In addition, the vector durations are also computed. Finally, simulation and experiment are carried out to validate the proposed control approaches. [ABSTRACT FROM PUBLISHER]

In spite of the wide improvement in computer simulation packages, analyzing, and optimizing the simulation model, particularly under uncertainty can still be computationally expensive and time-consuming. This paper aims to tackle these features by proposing a comprehensive methodology applied to black-box stochastic simulation models under uncertainty. For this purpose, the common surrogate model as Kriging metamodel is served to fit the simulation input–output data produced by Latin hypercube sampling experimental design. Taguchi terminology of robust design enables the optimization methods to control uncertainty and uncontrollable environmental factors. So as to formulate robust counterpart optimization, three different models in the class of dual-response surface are integrated with metamodel and robust design. Leave-one-out cross-validation is applied to validate the Kriging metamodel. Finally, a numerical case study as a direct speed control of dc motor under uncertainty is served to demonstrate the applicability of the proposed method in real engineering problems. This simplified and practical mechatronics case illustrates how the proposed procedure can be expanded for analyzing and optimizing the real complex systems. [ABSTRACT FROM AUTHOR]

Six-phase electrical machines have received significant attention in the literature due to their use in special purpose applications (e.g., aircraft, naval, and vehicular systems). Recently, such machines have also been considered for renewable energy systems including wind generators. Modeling of such machines in commonly available transient simulation programs is not straightforward, especially when the machine model is interfaced with external inductive network and/or power electronic converters. The available modeling approaches include the classical qd 0 model, the coupled-circuit-phase-domain and the voltage-behind-reactance (VBR) models (each having its interfacing challenges). This paper extends the prior research in this area and proposes a constant-parameter VBR model that has a very convenient constant RL−branch interfacing circuit (even for salient pole machines), which makes it simple to implement in most state-variable-based simulations programs. The presented computer studies demonstrate significant numerical advantages of the new model over the existing alternative models. [ABSTRACT FROM PUBLISHER]