2008 int ansys conf electronic cfd validation motors

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2008 International

ANSYS Conference

TEFC Electric Motors:CFD-Based Design Validation

Cassiano A. Cezário, M.Sc.

ResearcherWEG Electric Equipment – Motors

Amir A. M. de Oliveira Jr., Ph. D.Professor

Federal University of Santa Catarina - Brazil

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This is WEG - Foundation

Werner

Eggon

Geraldo

September 16th, 1961 – Jaraguá do Sul - SC - Brazil

Capital US$ 12,000.00 = 3 VW Beetle

*WEG in german means way .

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This is WEG - Products

“The largest transformer made by WEG” “The largest die cast iron frame of the world”

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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, Indiaand China.

-Exportation: 39 % of the income

-Employees 2008: 22000 (estimated)

Income 2008:US$ 3,34 Billion (goal)

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Heat Sources and Fan Systems

External Fan System

Internal Fan System

Heat Sources

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Evaluation of Fan System - External

QuantitativeQualitative

Smoke generator Automatic hot wire anemometer system

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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.

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Alternatives? Use of Numerical Softwares – CFD.

Evaluation of Fan System - Internal

How accuracte can CFD be?

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First Discretization of the Problem

Physical Domain Numerical Domain

Transposition aid of a 3D coordinate-measuring machine

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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

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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 mm100 mm

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AR-100-X

AR-140-X

Measurement Points (Air Flow)

RD-005-X

RD-095-1

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Data Acquisition (Fan Consumption)

Power Analizer

Special Device Auxiliar Electric Motor

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Measurement Results (Air Flow)

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Numerical Simplifications

Physical Domain Numerical Domain

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Simulation Domain

Periodic Symmetry (1/4)

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Stationary Domain

Simulation Domain

Rotating Domain

Additional data: steady state regime, stage interfaces, convergence criteria 5.10-5 (rms)

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Steady State Results (non converging)

Iteration 299 Iteration 399

Velocity Streamlines

Residual Values

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Iteration 299 Iteration 399

Steady State Results (non converging)

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Steady State Results (non converging)

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Mesh

Mesh Transition

Mesh Size 554.861 nodes

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Results for y+

 y+mean

= 5.55 y+max

= 16.33 y+min

= 0.03

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Differences Between Domains

TemporalAverage

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)

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Air Flow – Time of Simulation

Time over streamlines

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Air Flow – Geometric Mean

Physical Domain Numerical Domain

RD-005-6

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Air Flow - Results

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Air Flow – Error @ 3600 rpm

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Analyses for Results @ AR-100-6

Hot wire anemometer sensor

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Air Flow – Results @ 1800 rpm

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Fan Energy Consumption

Additional data:- steady state regime;- stage interfaces;- convergence criteria: torque stabilization.

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Fan Energy Consumption (Simulation)

Additional data:- Shell script and 400 interations by rotation speed.

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Fan Energy Consumption - Results

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Conclusions and Next Steps

• The methodology used allowed to address efforts to the aspects related to

numerical problems, eliminating uncertainties due to the geometricaspects. As a result, the numeric parameters that are essential for thestudy 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 numericalmethodology, 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.

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Acknowledgment

The authors want to thank:

• WEG, for the support and testing facilities;

• ESSS (Engineering Simulation and Scientific Software), for the support toANSYS-CFX;

• Mr. Regis Ataides for having made feasible this presentation;

• ANSYS for the invite.

THANK YOU!