Node Mapping Criterion for Highly Saturated Interior PMSMs Using Magnetic Reluctance Network

Interior Permanent Magnet Synchronous Machine (IPMSM) are high torque density machines that usually work under heavy load conditions, becoming magnetically saturated. To obtain properly their performance, this paper presents a node mapping criterion that ensure accurate results when calculating the performance of a highly saturated IPMSM via a novel magnetic reluctance network approach. For this purpose, a Magnetic Circuit Model (MCM) with variable discretization levels for the different geometrical domains is developed. The proposed MCM caters to V-shaped IPMSMs with variable magnet depth and angle between magnets. Its structure allows static and dynamic time stepping simulations to be performed by taking into account complex phenomena such as magnetic saturation, cross-coupling saturation effect and stator slotting effect. The results of the proposed model are compared to those obtained by Finite Element Method (FEM) for a number of IPMSMs obtaining excellent results. Finally, its accuracy is validated comparing the calculated performance with experimental results on a real prototype.

EFFICIENCY ESTIMATION OF PARALLEL ALGORITHM OF ENHANCED HISTORICAL DATA INTEGRATION ON COMPUTATIONAL GRID

The main feature of neural network using for accuracy improvement of physical quantities (for example, temperature, humidity, pressure etc.) measurement by data acquisition systems is insufficient volume of input data for predicting neural network training at an initial exploitation period of sensors. The authors have proposed the technique of data volume increasing for predicting neural network training using integration of historical data method. In this paper we have proposed enhanced integration historical data method with its simulation results on mathematical models of sensor drift using single-layer and multi-layer perceptrons. We also considered a parallelization technique of enhanced integration historical data method in order to decrease its working time. A modified coarse-grain parallel algorithm with dynamic mapping on processors of parallel computing system using neural network training time as mapping criterion is considered. Fulfilled experiments have showed that modified parallel algorithm is more efficient than basic parallel algorithm with dynamic mapping, which does not use any mapping criterion.

Foreign Law in Courts: A Typology

The chapter maps the landscape of various types of foreign law in domestic courts. The mapping criterion used is the domestic normative authority a national judge has for considering foreign law in various types of cases. On this basis, three types of the use of the foreign law before national courts are distinguished: mandatory uses, advisable uses, and voluntary uses. Advisable and voluntary uses are for ease of reference conflated into one category of non-mandatory references. Eventually, it is suggested that in most cases, the non-mandatory use of foreign law functionally overlaps with situations in which comparison between the foreign and domestic law is carried out.

Study of the improved algorithm for correlation integral method and its application to surge precursor identification

Correlation integral method (CIM) is a perfect method for the detection of stall and surge. However, CIM is very time-consuming due to its computational complexity. This paper aims to resolve the disadvantage. First, the segmented computation of correlation integral (CI) is deduced; second, the mapping criterion is given; finally the improved correlation integral method (ICIM) is proposed. The criterion can search the repeated subset of points and pair of subsets efficiently, which aids the ICIM in eliminating all redundancy caused by the overlapping of consecutive time windows. By applying ICIM to the detection of surge precursor in centrifugal compressors, it is illustrated that CI has a sharp decline more than 1.5 s prior to the fully developed surge. Also the processing time of ICIM is much shorter than that of CIM. The explicit detection of surge precursor, its rapid recognition, and the resulting longer time available for the feedback preventing the surge are the principal advantages of this approach. These studies are significant for CIM and will boost its application in numerous fields, especially in the detection of stall and surge.