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2008 Int ANSYS Conf Electronic CFD Validation Motors

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2008 International ANSYS Conference
TEFC Electric Motors: CFD-Based Design Validation
 
WEG Electric Equipment –Motors
 
This is WEG -Foundation
September 16th, 1961 –Jaraguá do Sul -SC -Brazil
Capital US$ 12,000.00 = 3 VW Beetle
*WEG in german means way.
 
This is WEG -Products
“The largest transformer made by WEG”
“The largest die cast iron frame of the world”
 
 
This is WEG –After 47 years
-Exports since 1970
-Sales to 5 Continents (100 Countries)
-Branches abroad: USA, Mexico, Argentina, Venezuela, Belgium, Germany, France, Spain, England, Sweden, Italy, Portugal, Japan, Australia, Chile, Colombia, India, China, Singapore and Emirates.-Seven plants in the exterior:Argentina, Mexico, Portugal, India and China.
-Exportation: 39 % of the income
-Employees 2008: 22000 (estimated)
Income 2008:US$ 3,34 Billion (goal)
 
Function of Electrical Motors
Function: Convert Electrical Energy in Mechanical Energy
 
 
Heat Sources and Fan Systems
External Fan System
Internal Fan System
Heat Sources
 
Evaluation of Fan System -External
Quantitative
Qualitative
Smoke generator
Automatic hot wire anemometer system
 
Evaluation of Fan System -Internal
How to evaluate the internal fan system in a electric motor?
Problems:
-Difficult to access;
-Risk of electrical shock;
-Difficult to do qualitative analysis.
 
Alternatives? Use of Numerical Softwares –CFD.
Evaluation of Fan System -Internal
How accuracte can CFD be?
 
First Discretization of the Problem
Physical Domain
Numerical Domain
Transposition aid of a 3D coordinate-measuring machine
 
Data Acquisition (Air Flow)
TSI Hot Wire Anemometer, model 8465.
Data Acquisition Software (in house)
0.5 mm Mechanical Pencil
Max. Air Velocity
Min. Air Velocity
Measurement Interval
Mean Air Velocity
 
Measurement Points (Air Flow)
Example of Radial Points (RD-005-X and RD-095-1)
Example of Axial Points
(AR-100-X and AR-140-X)
140 mm
100 mm
AR-100-X
AR-140-X
Measurement Points (Air Flow)
RD-005-X
RD-095-1
 
Data Acquisition (Fan Consumption)
Power Analizer
Special Device
Auxiliar Electric Motor
Measurement Results (Air Flow)
 
Numerical Simplifications
Physical Domain
Numerical Domain
 
Simulation Domain
Periodic Symmetry (1/4)
 
Stationary Domain
Simulation Domain
Rotating Domain
Additional data: steady state regime, stage interfaces, convergence criteria 5.10-5(rms)
 
Steady State Results (non converging)
Iteration 299Iteration 399
Velocity Streamlines
Residual Values
Iteration 299Iteration 399
Steady State Results (non converging)
 
Steady State Results (non converging)
 
 
 
Mesh Transition
Mesh Size 554.861 nodes
 
Results for y+
y+mean=5.55
y+max=16.33
y+min=0.03
 
 
Differences Between Domains
Temporal Average
Residual Values
Velocity Monitoring
Steady State
Transient
Temporal Mean
Additional data: transient regime, frozen rotor interfaces, convergence criteria 5.10-5(rms)
(Stage)
(Frozen Rotor)
 
Air Flow –Time of Simulation
Time over streamlines
 
Air Flow –Geometric Mean
Physical Domain
Numerical Domain
RD-005-6
 
Air Flow -Results
 
 
Air Flow –Error @ 3600 rpm
 
Analyses for Results @ AR-100-6
Hot wire anemometer sensor
 
Analyses for Results @ AR-100-6
Hot wire anemometer sensor
 
Air Flow –Results @ 1800 rpm
 
Fan Energy Consumption
Additional data:
-steady state regime;
-stage interfaces;
-convergence criteria: torque stabilization.
 
Fan Energy Consumption (Simulation)
Additional data:
-
Shell script and 400 interations by rotation speed.
 
Fan Energy Consumption -Results
 
Conclusions and Next Steps
 
The methodology used allowed to address efforts to the aspects related to numerical problems, eliminating uncertainties due to the geometric aspects. As a result, the numeric parameters that are essential for the study of the internal air flow of electric motors were obtained.
 
This work discussed the problem of numerical convergence and proposed a methodology to deal with this situation. Once defined the numerical methodology, it was possible to continue with the optimization problem.
 
The SST turbulence model, allied with the automatic wall function model, resulted in good agreement between numerical and experimental analyses, not only regarding to the punctual comparisons of the air speed, but also the power consumption of the external fan system.
Next Step: Include heat transfer and optimization processes.
 
Acknowledgment
The authors want to thank:
 WEG, for the support and testing facilities;
 ESSS (Engineering Simulation and Scientific Software), for the support to ANSYS-CFX;
 Mr. Regis Ataides for having made feasible this presentation;
 ANSYS for the invite.THANK YOU!
 
 
 
 
 

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