Electric Machine Simulation T Electric Machine Simulation Technology - - PowerPoint PPT Presentation

Electric Machine Simulation T Electric Machine Simulation Technology chnology

St Steve Har e Hartridge ridge Direct Director

• r, Electric &

, Electric & Hybrid V Hybrid Vehicles hicles

Intr Intro/Session description

• /Session description

Toda days demands/Mo ys demands/Motiv ivations ations EMA EMAG and and Thermal Thermal modeling modeling Combined w Combined workflo rkflow Exam Examples ples

Ag Agenda

Ov Over the last decade it er the last decade it is is no noticeable that there is ticeable that there is a a gr growing need f ing need for electric r electric machines with machines with

• High t

High torque ue or

• r
• High po

High power density along with a r density along with a

• High ef

High efficiency ciency demand demand or/and

• r/and
• Reduction in

duction in size, w size, weight, cost ight, cost

Leading t Leading to

• high

gher er t temperat mperature gr ure grad adients with a ients with a higher higher demand demand on the mat

• n the materials

rials in in general, general, but esp. but esp.

• n the insulation mat
• n the insulation materia

rials

• shor

shorter r lif lifetime time expectation pectation due t due to a higher a higher risk of thermal damag risk of thermal damages (esp. in s (esp. in the the insulation mat insulation materials). rials).

• A higher risk

igher risk of dema

• f demagne

gnetizatio ion n of the

• f the

magne magnets

Source ce g graphics: aphics: N NREL

Motiv Motivation f tion for Analysis r Analysis

Motiv Motivation f tion for Analysis r Analysis

Component lifetime estimates [1]:

– 22% of failures due to thermal damages in insulation – 17% further thermal damage in other components

Lif Lifetime d time depends on pends on t temperature hist erature histor

• ry;

y; Temperature d erature depend pends on s on losses an losses and cooling d cooling Insulation lifetime L can be modeled by the Arrhenius chemical equation [2]: Montsinger’s rule taken from transformer oil and solid insulation materials shows that the lifetime L decreases by 50% with increase of temperature T by 10 K [3]: So insulation breakdown is likely to be the problem associated with high

• temperatures. This problem may be tackled by

– either improving the insulation material and allowing the temperatures to rise or – improving the cooling performance of the windings and limiting the maximum temperature.

L A ·

• ⋅

L T 10K 0.5 · LT

Source: [1] Bruetsch, R., Tari, M. Froehlich, K. Weiers, T. and Vogesang, R., 2008. Insulation Failure Mechanisms of Power Generators IEEE, Electrical Insulation Magazine, 24(4) [2] Dakin, T.W., 1948, Electrical Insulation Deterioration Treated as a Chemical Rate Phenomena, AIEE Trans., Part 1, 67 [3] Binder, A., TU Darmstadt, EW, 2008, Script Large Generators & High Power Drives

To accomplish today’s demand the new machine designs have – to eliminate the safety factors of the over-sizing designs of the past – to finally ensure the requested high power densities. The need to have an optimized thermal design besides an optimized electro- magnetic design.

Motiv Motivation f tion for Analysis r Analysis

Electric Machine Simulation T Electric Machine Simulation Technology chnology

Electr Electromagne

• magnetic Simulation

tic Simulation

• Elect

ectrical/mech ical/mechanical per nical performance o

• rmance of

design design

• Design studies of dif

Design studies of differe erent types of t types of machine machine IMD IMD vs. BDC

• vs. BDC
• Torque and ef

ue and efficiency ency r requirement quirements ar are e me met

• Build ef

Build efficiency map f ciency map for machine r machine

• Detailed geome

Detailed geometric design of ric design of component

• nents –

– 2D/3D

• Optimize

Optimize magne magnet position/shape/mat position/shape/material erial

• Includ

Include a a sim simple le/conductio ction only n only therma thermal mod l model

Thermal Simulat Thermal Simulation

• n
• Under

Understand tand the ef the efficiency of the cooling ciency of the cooling syst system em

• Optimize

Optimize a flo a flow paths f paths for a giv r a given cooling en cooling syst system em

• Predict maximum com

Predict maximum component

• nent

temperatures at giv eratures at given dif en different operating erent operating points points

• Conside

Consider Conduction/c Conduction/con

• nvection/rad

ion/radiation syst ation system em

• Inc

Include t ude temperat mperature dependent ure dependent pr proper erties es

Coupled Problem Machine Designer/Electrical Engineer Thermal analyst/Mechanical engineer

The heat generated inside the motor originates from two main sources: – Electrical losses include

• the copper l

the copper losses - sses - also

• I2

2 ·R losses -

losses - in n the windings the windings

(heating ef (heating effect due t ct due to copper resi copper resistance), ance),

• core losses and

core losses and

(magnetic h (magnetic hyst steresis ( eresis (~ Bk · f) and eddy cu ) and eddy currents ( rrents (~ B2 · f2) in ir ) in iron

• n cores)

cores)

• eddy current losses in

eddy current losses in other par her parts of the machine being electric s of the machine being electric conductiv conductive, e.g e, e.g permanent magne ermanent magnets, end s, end shields, housing par shields, housing parts, … s, … – Mechanical losses, such as

• frictional losses generat

frictional losses generated b ed by the bearings as w the bearings as well as ll as

• windage

windage losses

• sses

Losses in Electrical Machines Losses in Electrical Machines

Conjugate Heat Transfer Analysis of Integrated Brushless Generators for More Electric Engines Marco Tosetti, Paolo Maggiore, Andrea Cavagnino, Senior Member IEEE, and Silvio Vaschetto, Member IEEE Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino – Italy

Br Brushless g ushless gener nerator

Thermal Modeling Thermal Modeling in Electrical Machines in Electrical Machines

Conjugate Heat Transfer Analysis of Integrated Brushless Generators for More Electric Engines Marco Tosetti, Paolo Maggiore, Andrea Cavagnino, Senior Member IEEE, and Silvio Vaschetto, Member IEEE Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino – Italy

Br Brushless g ushless gener nerator

Thermal Modeling Thermal Modeling in Electrical Machines in Electrical Machines

Winding Temperature Stator Core Temperature

Achie hieving ing Coupled Models Coupled Models

Electr Electromagne

• magnetic Simulation

tic Simulation Thermal Simulat Thermal Simulation

• n

Coupled Problem

• Manual T

Manual Transf ansfer of er of losses losses

• Rotor, Stator, Windings
• Homogeneous application
• Mapping of distributed losses
• Segmented by parts
• Maintain distribution of losses
• Typically from Finite element codes
• Codes often use a temperature
• Templat

mplate b based de d design ign c codes des

• Simple circuit models
• Finite Volume flow/thermal codes
• Homogeneous losses on bodies
• Rotor
• Stator
• Windings
• Heterogeneous losses
• Map between grids

Losses in Electric Machines Losses in Electric Machines

Homogeneous application of losses per component

– Copper losses = 43 W – Iron losses stator = 345 W – Magnet losses = 0.74 W

Heterogeneous application of losses

– See image

Comparison of Solution

Heterogeneous Homogeneous

Brushless DC Brushless DC mo motor, 1 10KW 0KW max po max power

Losses in Electric Machines Losses in Electric Machines

Comparison of maximum temperature

Heterogeneous Homogeneous

Heterogeneous “mapped” losses lead to higher maximum temperatures

The B-f The B-field v eld variation allo riation allows ir ws iron

• n loss

loss estimation estimation

– GoFER of 72 rotor positions /elec. revolution – Modified Steinmetz method in SPEED applies also to non sinusoidal currents

Front par

• nt part of the t
• f the tooth sees str
• th sees strong

nger f er fiel eld d variations which is riations which is reflect reflected in ed in the higher the higher ir iron loss density

• n loss density

The ir The iron

• n loss density can

loss density can be visualized be visualized SPEED SPEED

– Select the “Plot” Tab

Data T Data Transf ansfer t er to S STAR-CCM+ - AR-CCM+ - Losses

• sses

13 13

Data T Data Transf ansfer t er to S STAR-CCM+ - AR-CCM+ - Geome eometr try

SPEED SPEED geome geometry f for: stat r: stator

• r, slo

, slot windings, windings, ro roto tor, ro roto tor b bars. CAD CAD geome geometry f for: end-windings, end- r: end-windings, end- rings, all rings, all non-activ non-active com e components (f

• nents (fan,

an, housing, e housing, etc…) c…)

SPEED > S SPEED > STAR-CCM+ Industrial Exam AR-CCM+ Industrial Example ple

Induction machine, o Induction machine, overblo erblown with f n with fan n on

• n the shaf

the shaft

– SPEED Model > loss distribution – STAR-CCM+ > Temperature profiles

• Rotor B

Bar Av Avg=148.4 C C, E End R Ring 1 1 Av Avg=144.7 C C, E End R Ring 2 2 Av Avg=147.6 C C

• Shaf

Shaft Min T t Min Temp=55.8 C, Shaf =55.8 C, Shaft Max T t Max Temp=1 =148.3 C 48.3 C

• SPEED model with r

SPEED model with rotor t r temp @ @ 148 C req 48 C requires 52.5 % ires 52.5 % of copper

• f copper

conductivity f conductivity for consist r consistent losses and per nt losses and performance at this load point.

• rmance at this load point.

16 16

Simulation St Simulation Steady Stat eady State T e Temperatures eratures

1 1 2 2

Com Comparison with Measurements arison with Measurements

• Client measurements on

Client measurements on aux an aux and main wi d main winding at 2 nding at 2 circumferential locations, circumferential locations, both for the fan (cold side) and exhau both for the fan (cold side) and exhaust (hot side) of the end winding. st (hot side) of the end winding.

• Compare with mean and standard devi

Compare with mean and standard deviat ation of temperature in outer 5mm ion of temperature in outer 5mm of end-

• f end-

winding winding

End Winding 2 (cold side)

Measurement Simulation % Error Mean 91.5 C 93.1 C 1.74 % STD 1.88 C 2.14 C

End Winding 1 (hot side)

Measurement Simulation % Error Mean 111.4 C 111.9 C 0.45 % STD 3.03 C 1.30 C

SPEED > S SPEED > STAR-CCM+ Industrial Exam AR-CCM+ Industrial Example ple

Heat Flo Heat Flow: R : Rotor and r and Stat Stator

• r

SPEED > S SPEED > STAR-CCM+ Industrial Exam AR-CCM+ Industrial Example ple

SPEED SPEED > S > STAR AR-C

• CCM+ W

+ Workflo flow

Import SPEED geometry and surrounding CAD for non-active components in to STAR-CCM+ Compute electromagnetic losses in SPEED for specific load point and import into STAR-CCM+ Define appropriate physics and boundary conditions in STAR- CCM+ Solve conjugate heat tranfer problem for specific load point in STAR- CCM+ Specify new

• perating point and

recompute temperatures

Low speed, high torque…………………High speed, low torque

What if study: V What if study: Vent nted Stat ed Stator it

• r iteration

eration

– New CAD geometry imported – Remessed and case rerun

SPEED > S SPEED > STAR-CCM+ Industrial Exam AR-CCM+ Industrial Example ple

End Winding 2 (cold side)

Orig Design Vented Stator % Mean 93.1 C 76.6 C 17.7 % STD 2.14 C 1.63 C

End Winding 1 (hot side)

Orig Design Vented Stator % Mean 111.9 C 85.9 C 23.2 % STD 1.30 C 0.97 C

Copper winding modeled with t Copper winding modeled with temperat erature dependent resistivity ure dependent resistivity, results results in in higher local heating where the coil is higher local heating where the coil is ho hott tter er. Vent nted stat ed stator sho

• r shows reduction in

s reduction in coil coil temp and and total heat load fr tal heat load from 1

• m 197

7 W t W to 1 180 W of copper losses. 80 W of copper losses.

Temperature Dependent R erature Dependent Resistivity of sistivity of Copper Copper Winding Winding

SPEED SPEED > S > STAR AR-C

• CCM+ W

+ Workflo flow

Import SPEED geometry and surrounding CAD for non-active components in to STAR-CCM+ Compute electromagnetic losses in SPEED for specific load point and import into STAR-CCM+ Define appropriate physics and boundary conditions in STAR- CCM+ Solve conjugate heat tranfer problem for specific load point in STAR- CCM+ Specify new load point and recompute temperatures Change Geometry and recompute

JMA JMAG > S > STAR-CCM+ Exam AR-CCM+ Example ple

Low speed: 600 rpm Loss density Copper loss density distribution JMAG Iron loss density distribution JMAG Magnet loss density distribution JMAG

Low speed Medium speed High speed

Low speed: 600 rpm High speed: 8,000 rpm Mapped imported heat loss distribution STAR-CCM+ Temperature distribution STAR-CCM+

JMA JMAG > S > STAR-CCM+ Exam AR-CCM+ Example ple

SPEED pr SPEED provides initial design ides initial design

– Data export for further electromagnetic and thermal analysis

PC-FEA PC-FEA

FE calculat FE calculation ion

– For detailed EMAG and loss calculation and export of loss data

STAR AR-CCM+ cooling analysis

• CCM+ cooling analysis

– Conjugate heat transfer using liquid and/or gaseous coolants – Import of thermal loading from EMAG tool

• 2D or 3D Loss distribution data is

mapped onto STAR-CCM+ grid

Combined W Combined Workflo flow

Links with o Links with other FE supplier: her FE supplier: JMAG (JSOL, Japan) and FLUX (Cedrat, France)

3.

• 3. Run thermal calculations

in Motor-CAD to check the model

2.

• 2. FE-analysis and fitting
• f the analytical model

5.

• 5. Transfer of the heat loss distri-

bution from the FE-analysis to STAR-CCM+ via the sbd-file FE-grid SPEED FV-grid STAR-CCM+

1.

• 1. Creation of the

Motor-CAD model based on geometry parameters and winding scheme or import from SPEED

Data transfer

4.

• 4. Preparation of the geometry

in STAR-CCM+ by running a Java script

• 7. Solving and post processing

in STAR-CCM+

6.

• 6. Mapping process for rotor and stator heat

losses is carried out separately and auto- matically with transfer of the values from neighbor grid node in SPEED to STAR- CCM+

Thermal Modeling (7) Thermal Modeling (7)

Links with Mo Links with Motor-CAD CAD (Motor-Design, UK)

STAR-CCM+ EMA AR-CCM+ EMAG solv solver er

Applications of Applications often allo n allow 2D w 2D reduction reduction Available in ailable in STAR AR-CCM+ 8.06

• CCM+ 8.06

Validat lidated with PC-FEA ed with PC-FEA

Achie hieving ing Coupled Models Coupled Models

Electr Electromagne

• magnetic Simulation

tic Simulation Thermal Simulat Thermal Simulation

• n

Coupled Problem

Solution Progress Solution Progress

EMAG Solution Thermal Solution Thermal Solution EMAG Solution Thermal Solution Thermal Solution

It Iterations erations It Iterations erations It Iterations erations It Iterations erations

EMAG Solution

• Mapping of distributed losses
• Heterogeneous losses
• Map between grids

Electric Machine Simulation T Electric Machine Simulation Technology chnology

St Steve Har e Hartridge ridge Direct Director

• r, Electric &

, Electric & Hybrid V Hybrid Vehicles hicles

Besides CD-adapco internal material this presentation is based on the following publications:

• Bauarten von elektrischen Antrieben und deren Kühlung, Verluste, Vor- und Nachteile, Univ.-Prof. Dr. phil. Dr. techn. habil. Harald Neudorfer,

Traktionssysteme Austria GmbH, Kolloquium Elektrische Antriebe in der Landtechnik, Wieselburg, 26. Juni 2013 – Austria

• Keith R Pullen, Professor of Energy Systems, Brunthan Yoheswaren, PhD Researcher Energy and Transport Research Centre School of Engineering and

Mathematical Sciences, Cooling of Electrical Machines, EMTM ’13, , 12 September 2013 ▪ Nottingham University – UK

• Conjugate Heat Transfer Analysis of Integrated Brushless Generators for More Electric Engines Marco Tosetti, Paolo Maggiore, Andrea Cavagnino, Senior

Member IEEE, and Silvio Vaschetto, Member IEEE, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino – Italy

• Electric Motor Thermal Management, U.S. Department of Energy, Kevin Pennion, May 11, 2011 – US
• End Winding Cooling in Electrical Machines, Christopher Micallef, BEng (Hons), PhD Thesis submitted to the University of Nottingham, September 2006 –

UK

• Script Large Generators & High Power Drives, Prof. habil. Dr.Ing. A. Binder, A., TU Darmstadt, Inst. f. Elektrische Energiewandlung, 2008 – Germany