Showing 4 results for Lucas
A. Fereidunian, H. Lesani, C. Lucas, M. Lehtonen, M. M. Nordman,
Volume 2, Issue 3 (October 2006)
Abstract
Almost all of electric utility companies are planning to improve their
management automation system, in order to meet the changing requirements of new
liberalized energy market and to benefit from the innovations in information and
communication technology (ICT or IT). Architectural design of the utility management
automation (UMA) systems for their IT-enabling requires proper selection of IT choices for
UMA system, which leads to multi-criteria decision-makings (MCDM). In response to this
need, this paper presents a model-based architectural design-decision methodology. The
system design problem is formulated first then, the proposed design method is introduced,
and implemented to one of the UMA functions–feeder reconfiguration function (FRF)– for
a test distribution system. The results of the implementation are depicted, and
comparatively discussed. The paper is concluded by going beyond the results and fair
generalization of the discussed results finally, the future under-study or under-review
works are declared.
Saba Sedghizadeh , Caro Lucas , Hassan Ghafoori Fard ,
Volume 5, Issue 2 (June 2009)
Abstract
An adaptive online flux-linkage estimation method for the sensorless control of switched reluctance motor (SRM) drive is presented in this paper. Sensorless operation is achieved through a binary observer based algorithm. In order to avoid using the look up tables of motor characteristics, which makes the system, depends on motor parameters, an adaptive identification algorithm is used to estimate of the nonlinear flux-linkage parameters. This method makes position and speed estimation more accurate and robust towards any model uncertainty, also it is suitable replacement for a priori knowledge of motor characteristics.
C. Lucas, F. Tootoonchian, Z. Nasiri-Gheidari,
Volume 6, Issue 3 (September 2010)
Abstract
In this paper a brushless permanent magnet motor is designed considering
minimum thrust ripple and maximum thrust density (the ratio of the thrust to permanent
magnet volumes). Particle Swarm Optimization (PSO) is used as optimization method. Finite
element analysis (FEA) is carried out base on the optimized and conventional geometric
dimensions of the motor. The results of the FEA deal to the significant improvement of the all
objective functions.
C. Lucas , Z. Nasiri-Gheidari , F. Tootoonchian,
Volume 6, Issue 4 (December 2010)
Abstract
In this paper particle swarm optimization (PSO) is used for a design optimization of a linear permanent magnet synchronous motor (LPMSM) considering ultra low thrust force ripples, low magnet consumption, improved efficiency and thrust. The influence of PM material is discussed, too and the modular poles are proposed to achieve the best characteristic. PM dimensions and material, air gap and motor width are chosen as design variables. Finally 2-D finite element analyses validate the optimization results.
