Electric Machine Simulation TechnologySteve Hartridge

Director, Electric & Hybrid Vehicles

Intro/Session descriptionTodays demands/MotivationsEMAG and Thermal modelingCombined workflow Examples

Agenda

Over the last decade it is noticeable that there is a growing need for electric machines with • High torque or • High power density along with a • High efficiency demand or/and• Reduction in size, weight, cost

Leading to• higher temperature gradients with a higher

demand on the materials in general, but esp. on the insulation materials

• shorter lifetime expectation due to a higher risk of thermal damages (esp. in the insulation materials).

• A higher risk of demagnetization of the magnets

Source graphics: NREL

Motivation for Analysis

Motivation for Analysis

Component lifetime estimates [1]:– 22% of failures due to thermal damages in insulation– 17% further thermal damage in other components

Lifetime depends on temperature history; Temperature depends on losses and coolingInsulation 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·L T

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.

Motivation for Analysis

Electric Machine Simulation Technology

Electromagnetic Simulation• Electrical/mechanical performance of

design• Design studies of different types of

machine IMD vs. BDC• Torque and efficiency requirements are

met• Build efficiency map for machine• Detailed geometric design of

components – 2D/3D• Optimize magnet

position/shape/material• Include a simple/conduction only

thermal model

Thermal Simulation• Understand the efficiency of the cooling

system• Optimize a flow paths for a given cooling

system• Predict maximum component

temperatures at given different operating points

• Consider Conduction/convection/radiation system

• Include temperature dependent properties

CoupledProblem

MachineDesigner/Electrical

Engineer

Thermal analyst/Mechanical

engineer

The heat generated inside the motor originates from two main sources:

– Electrical losses include • the copper losses - also I2 ·R losses - in the windings

(heating effect due to copper resistance),

• core losses and(magnetic hysteresis (~ Bk · f) and eddy currents (~ B2 · f2) in iron cores)

• eddy current losses in other parts of the machine being electric conductive, e.g permanent magnets, end shields, housing parts, …

– Mechanical losses, such as• frictional losses generated by the bearings as well as • windage losses

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 IEEEPolitecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino – Italy

Brushless generator

Thermal Modeling 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 IEEEPolitecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino – Italy

Brushless generator

Thermal Modeling in Electrical Machines

Winding Temperature

Stator Core Temperature

Achieving Coupled Models

Electromagnetic Simulation Thermal Simulation

CoupledProblem

• Manual Transfer of 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

• Template based design codes• Simple circuit models

• Finite Volume flow/thermal codes• Homogeneous losses on bodies

• Rotor• Stator• Windings

• Heterogeneous losses• Map between grids

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 motor, 10KW max power

Losses in Electric Machines

Comparison of maximum temperature

Heterogeneous Homogeneous

Heterogeneous “mapped” losses lead to higher maximum temperatures

The B-field variation allows iron loss estimation– GoFER of 72 rotor positions /elec. revolution– Modified Steinmetz method in SPEED

applies also to non sinusoidal currents

Front part of the tooth sees stronger field variations which is reflected in the higher iron loss densityThe iron loss density can be visualized SPEED– Select the “Plot” Tab

Data Transfer to STAR-CCM+ - Losses

13

Data Transfer to STAR-CCM+ - Geometry

SPEED geometry for: stator, slot windings, rotor, rotor bars.

CAD geometry for: end-windings, end-rings, all non-active components (fan, housing, etc…)

SPEED > STAR-CCM+ Industrial Example

Induction machine, overblown with fan on the shaft– SPEED Model > loss distribution – STAR-CCM+ > Temperature profiles

• Rotor Bar Avg=148.4 C, End Ring 1 Avg=144.7 C, End Ring 2 Avg=147.6 C• Shaft Min Temp=55.8 C, Shaft Max Temp=148.3 C• SPEED model with rotor temp @ 148 C requires 52.5 % of copper

conductivity for consistent losses and performance at this load point.

16

Simulation Steady State Temperatures

1

1

2

2

Comparison with Measurements

• Client measurements on aux and main winding at 2 circumferential locations, both for the fan (cold side) and exhaust (hot side) of the end winding.

• Compare with mean and standard deviation of temperature in outer 5mm of end-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 > STAR-CCM+ Industrial Example

Heat Flow: Rotor and Stator

SPEED > STAR-CCM+ Industrial Example

SPEED > STAR-CCM+ Workflow

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 operating point and

recomputetemperatures

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

What if study: Vented Stator iteration– New CAD geometry imported– Remessed and case rerun

SPEED > STAR-CCM+ Industrial Example

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 temperature dependent resistivity, results in higher local heating where the coil is hotter.Vented stator shows reduction in coil temp and total heat load from 197 W to 180 W of copper losses.

Temperature Dependent Resistivity of Copper Winding

SPEED > STAR-CCM+ Workflow

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

recomputetemperatures

Change Geometry and recompute

JMAG > STAR-CCM+ Example

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 rpmMappedimported heat loss distribution STAR-CCM+

Temperature distributionSTAR-CCM+

JMAG > STAR-CCM+ Example

SPEED provides initial design– Data export for further electromagnetic

and thermal analysis

PC-FEA

FE calculation– For detailed EMAG and loss

calculation and export of loss data

STAR-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 Workflow

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

3. Run thermal calculationsin Motor-CAD to checkthe model

2. FE-analysis and fittingof the analytical model

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. Creation of theMotor-CAD model based on geometry parameters and winding scheme orimport from SPEED

Data transfer

4. Preparation of the geometryin STAR-CCM+ by running a Java script

7. Solving and post processingin STAR-CCM+

6. Mapping process for rotor and stator heatlosses is carried out separately and auto-matically with transfer of the values fromneighbor grid node in SPEED to STAR-CCM+

Thermal Modeling (7)

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

STAR-CCM+ EMAG solver

Applications often allow 2D reductionAvailable in STAR-CCM+ 8.06Validated with PC-FEA

Achieving Coupled Models

Electromagnetic Simulation Thermal Simulation

CoupledProblem

Solution ProgressSolution Progress

EMAG Solution ThermalSolutionThermal Solution EMAG Solution Thermal

SolutionThermal Solution

Iterations

Iterations

Iterations

Iterations

EMAG Solution

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

Electric Machine Simulation TechnologySteve Hartridge

Director, Electric & Hybrid Vehicles

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