Air flow and Heat Transfer Modeling of an Axial Flux Permanent Magnet Generator

Axial Flux Permanent Magnet (AFPM) Machines require effective cooling due to their high power density. The detrimental effects of overheating such as degradation of the insulation materials, magnets demagnetization, and increase of Joule losses are well known. This paper describes the CFD simulations performed on a test rig model of an air cooled Axial Flux Permanent Magnet (AFPM) generator built at Durham University to identify the temperatures and heat transfer coefficient on the stator. The Reynolds Averaged Navier-Stokes and the Energy equations are solved and the flow pattern and heat transfer developing inside the machine are described. The Nusselt number on the stator surfaces has been found. The dependency of the heat transfer on the flow field is described temperature field obtained. Tests on an experimental are undergoing in order to validate the CFD results.

Transient Thermal Modeling of an Axial Flux Permanent Magnet (AFPM) Machine Using a Hybrid Thermal Model

This paper presents the development of a hybrid thermal model for the EVO Electric AFM 140 Axial Flux Permanent Magnet (AFPM) machine as used in hybrid and electric vehicles. The adopted approach is based on a hybrid lumped parameter and finite difference method. The proposed method divides each motor component into regular elements which are connected together in a thermal resistance network representing all the physical connections in all three dimensions. The element shape and size are chosen according to the component geometry to ensure consistency. The fluid domain is lumped into one region with averaged heat transfer parameters connecting it to the solid domain. Some model parameters are obtained from Computation Fluid Dynamic (CFD) simulation and empirical data. The hybrid thermal model is described by a set of coupled linear first order differential equations which is discretised and solved iteratively to obtain the temperature profile. The computation involved is low and thus the model is suitable for transient temperature predictions. The maximum error in temperature prediction is 3.4% and the mean error is consistently lower than the mean error due to uncertainty in measurements. The details of the model development, temperature predictions and suggestions for design improvements are presented in this paper.

Design and Simulation of Low Speed Axial Flux Permanent Magnet (AFPM) Machine

In this paper presented initial design of Low Speed Axial Flux Permanent Magnet (AFPM) Machine with Non-Slotted TORUS topology type by use of certain algorithm (Appendix). Validation of design algorithm studied by means of selected data of an initial prototype machine. Analytically design calculation carried out by means of design algorithm and obtained results compared with results of Finite Element Method (FEM).