Calculation of Flux density in Air-Gap for Reluctance Motor with Two Ports (Double-Stator, Double- Rotor) by Fourier Series

Abstract

In this paper, a model based on Fourier series is presented to predict value of flux density in airgap with respect to mechanical angle for double-stator, double-rotor reluctance motor (DSDRRM). The DSDRRM is an excellent choice to be used as the electric motor in hybrid electric vehicles (HEVs) due to integrating two rotors and two stators into a compact structure and robust structure but torque ripple in this type of machines is high then special and fast model is necessary to design that proposed model can help us to have fast design. Point to point components of radial and tangential for DSDRRM are shown in figures compared between proposed model and finite element analysis (FEA) that the approach can be used for the magnetic field calculation in DSDRRM with any combination of rotor- and stator-pole number eventually, after putting analytical outputs on numerical outputs, efficacy of proposed model is validated.

Accurate and Fast model for single Rotor Double Stator Interior Permanent Magnet Brushless Synchronous Machine with Spoke-Type structure at no-Load

“…If the interface is source-free, as result the parallel component of the magnetic eld intensity vector on one side of the boundary is equal to that of the other side in according to Table1. Also, the parallel component of the magnetic eld intensity vector is zero at the interface of those media adjacent to in nitely permeable domains that solving the nonlinear equations are done by Shwarz-Christoffel formula [35][36][37][38][39][40][41][42][43][44].…”

Recommender System for Predicting the Academic Status of Students of Bangladesh Using Artificial Neural network

“…The block-mathematical model of a neural network is shown in Fig. 1 [33][34][35][36][37][38][39][40][41][42][43].…”

“…Learnability means the ability to adjust time-varying parameters, with the aim that the network can be e cient for new conditions with brief training. In most neural networks, learning rules are used to train the network, and neural network learning is done in two types, supervised and unsupervised, which is shown in Table 2 comparing these two learning methods [34], [35], [36], [37].…”

Analytical Analysis of the Slotted Double-Sided Linear Flux Switching Permanent Magnet Motors by Considering Different Layers of Winding

“…However, these linear format structures still adopted even number of primary poles. Due to linear structure without the problem of unbalanced magnetic force in rotatory machines, odd number of primary poles has been applied in the linear machine with partitioned primary [11]- [12]- [13]- [14]- [15]- [16]- [17]- [18]- [19]- [20].…”