The webinar reviews the different sources of losses in electric motors, focusing on the link between efficiency and cooling. The different cooling strategies are reviewed depending on motor topology. Finally, available modelling strategies and simulation software are reviewed.

1. HEAT TRANSFER IN ELECTRIC MACHINES
Overview of cooling and simulation techniques in electric machines
JANDAUD Pierre-Olivier
LE BESNERAIS Jean
20th September 2017
www.eomys.com
contact@eomys.com
1

2. 2
PRESENTATION OF EOMYS
• Innovative Company created in may 2013 in Lille, North of France (1 h from
Paris)
• Activity: engineering consultancy / applied research
• R&D Engineers in electrical engineering, vibro-acoustics, heat transfer,
scientific computing
• 80% of export turnover in transportation (railway, automotive, marine, aeronautics),
energy (wind, hydro), home appliances, industry

3. • Diagnosis and problem solving including both simulation & measurements
• Multi-physical design optimization of electrical systems
• Technical trainings on vibroacoustics of electrical systems
• MANATEE fast simulation software for the electromagnetic, vibro-acoustic and
heat transfer design optimization of electric machines
3
EOMYS can be involved both at design stage & after manufacturing of electric
machines
EOMYS SERVICES & PRODUCTS

4. 4
WEBINAR SUMMARY
• INTRODUCTION
• TYPES OF COOLING TOPOLOGIES
• SIMULATION TECHNIQUES
• CONCLUSION

5. 5
INTRODUCTION
• Why is heat management important in an electric machine?
• General introduction to Heat Transfer & Fluid Mechanics
• Types of Losses

6. 6
Why is heat management important?
• Temperature levels impact directly on the lifetime of a machine
• High temperature increases the fatigue of a material
• Each machine has an insulation class for its windings based on the nature
of the insulation material
• Basic rule of thumb: lifetime divided by two for each 10°C over the rated
temperature, multiplied by two for each 10°C below.
• Temperature levels are also important to avoid demagnetization of the
permanent magnets and efficiency reduction
• Heat Management is important for reliable and robust machines
Overheated windings (Reinap, 2015)Demagnetization and characteristic curves of a
PM (Neorec53B magnet)

7. 7
Why is heat management important?
• Temperature levels impact directly on the efficiency of the machine
• High temperatures increase linearly the electric resistance of conductors:
𝑅𝑅(𝑇𝑇) = 𝑅𝑅𝑟𝑟𝑟𝑟𝑟𝑟 1 + 𝛼𝛼(𝑇𝑇 − 𝑇𝑇𝑟𝑟𝑟𝑟𝑟𝑟)
• Higher temperatures ⇒ higher Joule losses
• Several studies show the impact of temperature on efficiency of PM
machines
• From 25°C to 100°C, the efficiency can decrease up to 5%
• Investing in the cooling system optimization at the design stage of
the machine can give significant long-term cost savings
Torque vs Temperature in a PM motor (Lungoci, 2008)
Efficiency vs Temperature for different PM (Wang 2008)

8. 8
General introduction to heat transfer in electric machines
• An electric machine is a complex system in
terms of heat transfers
• The three kind of heat transfers interact
(Conduction, Convection, Radiation)
• Heat is generated by losses in the machine
• Heat always flow from the hottest
temperature to the lowest
From Techniques de l’Ingénieur (Bertin, 1999)

9. 9
General Introduction: Conductive heat transfer
• Conduction occurs inside a body, depends on the thermal
conductivity (𝜆𝜆 in 𝑊𝑊. 𝑚𝑚−1. 𝐾𝐾−1)
• In a homogeneous body, heat flux (𝝋𝝋 in 𝑊𝑊/𝑚𝑚2
) respects a simple
PDE the Fourier’s Law, fundamental law for conduction:
𝝋𝝋 = −𝜆𝜆. 𝛁𝛁𝑇𝑇
• For an equivalent heat flux, a higher thermal conductivity means
a lower temperature gradient i.e. lower temperature levels
• Electric analogy: Ohm’s Law, Temperature is Voltage, thermal
conductivity is equivalent to electric conductivity
• Electric insulators are most of the time good thermal insulators.
• Air is one of the best insulator if it’s not moving; if there is air motion,
convective heat transfer appears
Material 𝜆𝜆 (𝑊𝑊/m/K)
Air 0.026
PVC 0.15
Epoxy 0.25
Water 0.6
Stainless Steel 30
Cast Iron 50
Aluminum 230
Copper 390
Thermal conductivities of common
materials at 20°C
Ex: thermal effect of Vaccum Pressure Impregnation (VPI) when air replaced by resin

10. 10
General Introduction: Convective heat transfer
• Convective heat transfer occurs in case of a moving fluid on a
solid body
• The convective heat flux between a solid and a fluid body is given by
Newton’s Law:
𝝋𝝋 = ℎ. (𝑇𝑇𝑠𝑠𝑠𝑠𝑠𝑠 − 𝑇𝑇𝑓𝑓𝑓𝑓𝑓𝑓)
• ℎ is the convective Heat Transfer Coefficient (HTC) in 𝑊𝑊/𝑚𝑚2
/𝐾𝐾
• The fluid can be a gas (e.g. air), or a liquid (e.g. water, oil)
• Natural convection: fluid motion due to thermal gradients (e.g. hot air
balloon, ocean currents)
• Forced convection: fluid motion due to an external source (e.g. pump,
fan)- main method to cool electric machines
Material ℎ (W/m²/K)
Air (natural
convection)
5-10
Air (forced
convection)
10-300
Water (forced
convection)
500 – 10000
Range of convective HTC for air and
water
Ex: effect of relative wind on the cooling of outer rotor wind turbine generator

11. 11
General Introduction: Radiative heat transfer
• Each body emits electromagnetic radiations depending on its
temperature levels (contactless heat transfer)
• Bodies are modelled using the gray body theory. The heat flux
exchanged with a body and its environment is:
𝝋𝝋 = 𝜎𝜎. 𝜀𝜀. (𝑇𝑇4
− 𝑇𝑇∞
4
)
• 𝜎𝜎 is the Stefan-Boltzman constant and 𝜀𝜀 is the emissivity of the body
• The emissivity is low for reflective surfaces (polished metals) and
depends strongly on the surface finish
• Radiative heat transfer is often neglected inside the machine due to
relatively low temperature levels
• Radiative heat transfer can be important as a boundary condition
especially in case of natural convection
Material 𝜺𝜺
Aluminum
(polished)
0.05
Aluminum
(strongly oxidized)
0.25
Black electrical
tape
0.95
Cast iron
(polished)
0.21
Copper (polished) 0.01
Copper (oxidized) 0.65
Galvanized steel 0.28
Ideal Black Body 1
Matt paint (oil) 0.9-0.95
Water 0.98
Emissivity values for common materials
at 20°C (Fluke)
Ex: alternator in a car exchanging heat with the other parts of the engine

12. 12
General Introduction: Fluid Mechanics considerations
• Average velocity of the fluid 𝑢𝑢0 (m/s)
• Volume flow rate (𝑄𝑄 in m3/s) through a section S: 𝑄𝑄 = 𝑢𝑢0. 𝑆𝑆. Between 2 points of a circuit, flow rate is
constant:
𝑢𝑢1 𝑆𝑆1 = 𝑢𝑢2 𝑆𝑆2
• The pressure of the fluid (𝑝𝑝 in Pa). Between 2 points of a path line, pressure and average velocities
are linked by Bernoulli equation (𝜌𝜌 is the density of the fluid in kg/m3):
𝑝𝑝1 +
1
2
𝜌𝜌𝑢𝑢1
2
= 𝑝𝑝2 +
1
2
𝜌𝜌𝑢𝑢2
2
+ 𝚫𝚫𝑷𝑷
• Δ𝑃𝑃 is the Head Loss or Pressure drop between two points of the circuits. It represents the energy
lost due to friction (on walls or due to a singularity). Equation of the hydraulic power:
𝑃𝑃𝐻𝐻 = 𝑄𝑄. ∆P
• Hydraulic power is important to evaluate the energy consumption of a cooling system
Ex: cost of cooling power consumption over 25 yrs of a wind turbine generator

13. 13
General Introduction: Dimensionless numbers
• In Fluid Mechanics and Heat Transfer, most of the phenomena are
studied using dimensionless numbers which are used also in
correlations
• The Reynolds number dimensionless number for the velocity. In a channel,
for Re < 1500 flow is laminar. For Re > 3000, flow is turbulent.
𝑅𝑅𝑒𝑒𝐷𝐷 =
𝑢𝑢. 𝐷𝐷
𝜈𝜈
• The Nusselt number is for convective heat transfer. In the scientific
literature most of the convection correlations have the form: 𝑁𝑁𝑁𝑁 = 𝛽𝛽. 𝑅𝑅𝑒𝑒 𝛼𝛼
𝑁𝑁𝑢𝑢𝐷𝐷 =
ℎ. 𝐷𝐷
𝜆𝜆
• Pressure drop coefficient is given by: 𝜅𝜅 = �Δ𝑃𝑃
1
2
𝜌𝜌𝑢𝑢2
• Friction factor in a channel of diameter D and length L is given by: 𝑓𝑓 =
𝐿𝐿
𝐷𝐷
𝜅𝜅𝑓𝑓. For laminar flow, given by an analytical expression: 𝒇𝒇 = 𝟔𝟔𝟔𝟔/𝐑𝐑𝐑𝐑. For
turbulent flow, the Moody chart must be used.
Laminar (up) and turbulent (down) rotating flow
visualizations at Re=900 and Re=5000 (Bauduin,
2014)
Moody chart for friction factor

14. 14
Heat Sources in a Machine: Losses
• Heat in the machine is generated by electromagnetic and
mechanical losses
• Losses distribution highly depends on machine topology, load and supply
conditions
• Joule losses are generated by electric currents in the windings
• Core losses include hysteresis losses, eddy-current and stray
losses, they are located in the laminations of the machine
• Magnet losses are due to eddy currents, they can be high in
concentrated winding topologies with surface magnets
• Mechanical losses include friction and windage losses (friction in
bearings, aerodynamic friction and drag)
Losses in an 4 poles IM at 50Hz (Yang,
2016)
Losses in an IPM machine (Yang, 2016)

15. 15
Heat Sources in a Machine: Joule Losses
• Joule Losses are usually the most important sources of losses in an
electric machine
• Located in windings/end-windings and rotor bars of IM
• Usually dissipated with convection on end-windings (for stator)
• Temperature dependent: higher temperatures increase electric
resistivity
• Joule Losses equation with frequency dependent effects:
𝑃𝑃𝐽𝐽 = 𝑚𝑚. 𝐼𝐼𝑝𝑝
2
𝑅𝑅𝐷𝐷𝐷𝐷 + 𝑅𝑅𝑠𝑠𝑠𝑠𝑠𝑠 𝑠𝑠 𝑓𝑓 + 𝑅𝑅𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝(𝑓𝑓)
Losses in an 4 poles IM at 50Hz (Yang,
2016)
Losses in an IPM machine (Yang, 2016)
Phase number
rms phase current
DC, Skin and
proximity components of phase
resistance

16. 16
Heat Sources in a Machine: Core Losses
• Core losses are usually the second sources of losses in a machine
• Located in the stator and rotor cores
• Combine two phenomena: eddy-current losses and hysteresis losses
• Modeling of core losses is more challenging than Joule Losses
• Steinmentz equation taking harmonic components into account:
𝑃𝑃𝑐𝑐 = �
𝑛𝑛
𝐾𝐾ℎ 𝑛𝑛 𝐵𝐵𝑛𝑛
1,6
𝑛𝑛𝑛𝑛 + 𝐾𝐾𝑒𝑒 𝑛𝑛 𝐵𝐵𝑛𝑛
2
𝑛𝑛𝑛𝑛 2
Losses in an 4 poles IM at 50Hz (Yang,
2016)
Losses in an IPM machine (Yang, 2016)
Harmonic rank
Frequency
Flux density
Hysteresis coeff.
Eddy losses coeff.

17. 17
Heat Sources in a Machine: Magnet Losses
• Magnet losses can be critical in some topologies
• Magnets can be isolated inside the machine (e.g. IPMSM) -> difficulty to
dissipate magnet losses
• Magnet Losses equation for SPMSM (Deeb et al, 2012)
𝑃𝑃𝑚𝑚 =
𝑉𝑉𝑚𝑚 𝑊𝑊𝑚𝑚
2
24 𝜌𝜌𝑚𝑚
�
𝑛𝑛
𝐵𝐵𝑛𝑛
2
𝜔𝜔2 𝑛𝑛2
Losses in an 4 poles IM at 50Hz (Yang,
2016)
Losses in an IPM machine (Yang, 2016)
Volume
Width
Resistivity
Frequency
Harmonic id
Flux density

18. 18
Heat Sources in a Machine: Mechanical losses
Bearings losses.
• They depend on the frictional moment and the rotation speed
• For some applications, an independent cooling system can be needed for
bearings (e.g. direct drive wind turbines)
Air friction losses
• Caused by the aerodynamic drag, the turbulent structures and the head
losses in the machine
• Neglectable at low speeds: for high peripheral velocity, they can be very
important (cf. example)
• For a smooth rotating cylinder of radius R and length L, equation of the
air friction losses:
𝑃𝑃𝑓𝑓 𝑎𝑎𝑎𝑎𝑎𝑎
= 𝑐𝑐𝑓𝑓 𝜋𝜋𝜌𝜌𝑎𝑎𝑎𝑎𝑎𝑎 𝜔𝜔3
𝑅𝑅4
𝐿𝐿
Overall losses (Pd) and friction losses
due to air (Pfair) in a 100W, 500k rpm PM
machine (Luomi, 2009)

19. 19
COOLING ARCHITECTURES OF ELECTRIC MACHINES
• Overview of the different cooling topologies
• Tips for designing a cooling system

20. 20
Cooling architectures: IEC standards
• Based on standard IEC 60034-6
• Primary coolant: coolant directly in contact with the machine (air most of the time)
• Secondary coolant: coolant for a primary coolant
• Designation example of a cooling circuit, designation can be different for rotor and stator if the circuits
are different:
IC 4 (A) 1 (A)
6
International Cooling Circuit arrangement
0: open circuit
4: Frame cooled
8: Heat Exchanger
Primary coolant
A: Air (omitted)
W: Water
U: Oil
Primary circuit
0: Free convection
1: Self circulation
6: Independent
system on
machine
7: Separate
component
8: Relative
displacement
Secondary
coolant
A: Air (omitted)
W: Water
U: Oil
Secondary circuit
0: Free convection
1: Self circulation
6: Independent
system on
machine
7: Separate
component
8: Relative
displacement

21. 21
Cooling architectures: Open Machines
• In an open machine, air is drawn inside the machine by openings in its
housing and directly rejected in its environment.
• Fans can be mounted on the rotor
• Examples of machines: car alternators (Valeo, Bosch, Delphi…)
• Advantages: low-cost system, no need of external power source, high
reliability, good cooling of the end-windings
• Drawbacks: highly influenced by the outer environment (external
temperature, dirt, etc.), no control of the cooling, almost no air flow in the
air gap
Delphi Alternator
Air flow in a Valeo Starter-Generator
(Jandaud, 2013)

22. 22
Cooling architectures: Self ventilated machines
• Totally enclosed machine: air motion in the machine is induced by
rotation of the rotor, a fan can blow air on the outer surface of the machine.
• Fins are often placed on the outer surface of the machine to increase
exchange surface
• Very common architecture for low voltage motors
• Not suitable for high power density machines
Full view and cutaway view through the
stator of an IM (ABB Motor)
From Techniques de l’Ingénieur (Bertin, 1999)

23. 23
Cooling architectures: Axial and Radial cooling circuits
• Air flow is controlled independently and guided inside the machine
following either an axial path or a radial path
• Air is guided inside the rotor and stator by radial and axial ventilation
ducts
• Topology for air-cooled high power machines like wind-turbines
• Advantages: good cooling inside the stator and rotor laminations, control
of the external fans possible depending on the load
• Drawbacks: heat exchanger needed to cool down the air circuit, higher
power needed for the cooling
• Axial and radial cooling can be mixed
From Techniques de l’Ingénieur (Bertin, 1999)

24. 24
Cooling architectures: Liquid Cooling
• For high power density machines, air cooling is not enough and
liquid cooling is needed
• Liquid is generally either water or oil
• Two main topologies: water jackets in the housing of the machines or
ducts inside the machine
• Very effective cooling due to the liquid state of the coolant
• High pumping power needed for the system
Water jackets topologies (Satrústegui,
2017)
Water ducts inside a stator (Kim, 2017) Porsche Carrera motor using a water
jacket
APM 120R motor for racing cars using oil
cooling through ducts (Equipmake)

25. 25
Cooling architectures: Other cooling devices
Oil jet and sprays cooling
• Impinging jets or sprays directly on the end-windings.
• Very good cooling of end-windings.
• Mostly automotive applications
Heat pipes cooling
• Heat pipes are passive cooling devices using phase change phenomena
• For high-end applications (expensive) but very effective and reliable
• Aerospace and automotive applications
Schematics of spray cooling used by
Renault (Davin, 2017)
Tesla Rotor cooling with heat pipes (Putra,
2017)
Heat pipes stator cooling (Putra, 2017)

26. 26
Design of a cooling system: How to choose?
General considerations
• What are is the loss distribution generated of the machine?
• Where are located the critical temperatures of the machine?
• What is the required power density of the machine?
Basic rules of thumb
• Based on current density range (Staton, 2014)
Cooling
System
Current
density
A/mm²
Cooling
efficiency
Complexity Energy
cost
Free
convection
1.5 – 5 Low Simple None
Forced
convection
5 – 10 Medium Medium Low
Liquid
cooling
10 – 30 High Complex High
Cooling technologies depending on cooling
target (Yang, 2015)

27. 27
Design of a cooling system: How to improve convective heat transfer?
• Convective (solid to fluid) heat transfer is the main way of cooling electric machines. How to improve it?
• Equation of heat transfer between a fluid and a solid:
Φ = ℎ. 𝑆𝑆 ( 𝑇𝑇𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑠𝑠 − 𝑇𝑇𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓)
Solid temperature: what we
want to minimize
Temperature of the coolant
Convective
Conductance
Total Losses of the machine
(W)
ℎ: convective
HTC
S: exchange surface
Better EM design to
reduce losses
Increase fluid
velocity, change
nature of coolant to
increase ℎ
Add fins, add new cooling
paths (ventilation ducts) to
increase exchange
surface
Better heat exchanger to
reduce coolant
temperature

28. 28
Design of a cooling system: Design objectives
Good practices to design a cooling system
• Keep in mind the energy cost. For a closed circuit, given by the hydraulic power divided by the electrical
and mechanical efficiency of the pump/fan:
• 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 =
Q.ΔP
𝜂𝜂𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒.𝜂𝜂 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
What are the losses generated by my machine? The location of the heat
sources is important
• A good cooling doesn’t mean the lowest possible temperatures everywhere, it is important to focus on the
critical parts of the machine
• Windings should respect the operating temperatures of their insulation classes
• Magnet temperature should be far from their demagnetization threshold
-> Fast (magneto-thermal coupling, design iterations) and accurate simulation tools are needed

29. 29
THERMAL SIMULATION TECHNIQUES
• Available methods for the thermal simulation of electric machines
• General considerations for the simulation of electric machines
• Brief overview of the different existing software (commercial + free / open-source)

30. 30
Available Simulation Techniques for Electric Machines
• Electric machines are complex systems to model combining both Heat Transfer and Fluid Mechanics
• Three main techniques with an increasing degree of complexity and accuracy exist: Lumped-Parameter
Thermal-Networks (LPTN), Thermal Finite Elements (FEM) Simulations and Computational Fluid Dynamics
(CFD).
Lumped
Parameters
CFD Simulation
FEM Simulation
Complexity
0D Simulation solving the Heat
Equation using electrical
analogy
2D/3D FEM Conductive simulation,
analytical/empirical boundary
conditions
2D/3D Fluid and solid parts are fully solved
No correlations or empirical data used

31. 31
Lumped Parameter Thermal Networks
• LPTN are based on the Electrical Analogy
• The machine is divided in small isothermal volumes linked by thermal
conductances (G) depending on the nature of the heat transfer:
𝐺𝐺𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 =
𝜆𝜆.𝑆𝑆
𝐿𝐿
𝐺𝐺𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 = ℎ. 𝑆𝑆
• Two equations, one for unsteady the other for steady state:
Unsteady: 𝐶𝐶
𝑑𝑑𝑑𝑑
𝑑𝑑𝑑𝑑
+ 𝐺𝐺. 𝑇𝑇 = 𝑃𝑃 Steady: 𝐺𝐺. 𝑇𝑇 = 𝑃𝑃
• Steady state: a simple linear system to solve
• The method is very fast and simple, allowing magnetothermal iterations
• Empirical and/or analytical correlations needed to determine the
convection coefficients
Thermal Resistances Network of an electric
machine generated by MotorCAD (Boglietti,
2009)
Results of a thermal network on a Jeumont
Electric machine (Bornschlegell, 2013)

32. 32
Thermal FEM Simulation
• Only for conductive heat transfer in solid parts of the machine
• Solves the heat equation using Finite Element Method:
𝜕𝜕𝑇𝑇
𝜕𝜕𝑡𝑡
−
𝜆𝜆
𝜌𝜌. 𝑐𝑐𝑝𝑝
𝛻𝛻𝛻 = 𝜑𝜑𝑣𝑣
• It can be both solved in steady and unsteady states
• Advantages: detecting potential hot spots as the solution is local – easily
coupled with electromagnetic FEM calculations
• Like LPTN, empirical data or correlations for convective boundary conditions
are needed, its accuracy depends greatly on them
• Can be solved in 2D or 3D.
• Heat transfer problems in a machine are often fully 3D problems
Results of a 2D thermal FEM simulation in a
BPMSM (Yang, 2016)
Results of a 3D thermal FEM simulation of a
stator (Kim, 2017)

33. 33
Full CFD simulation
• In a CFD simulation, heat equation is solved (like FEM) and the
Navier-Stokes equation is added:
𝜕𝜕𝒖𝒖
𝜕𝜕𝑡𝑡
+ 𝒖𝒖. 𝛁𝛁 . 𝒖𝒖 = −
1
𝜌𝜌
𝛻𝛻𝑝𝑝 + 𝜈𝜈Δ𝒖𝒖
• Equation usually solved in steady state as computation cost would be
too high for unsteady
• Turbulent flow must be modelled, the most common technique is to
use Reynolds Averaged Navier-Stokes equations (RANS)
• Computation cost can be very high (several hours/days)
• No correlation/empirical data needed
• Accuracy depends on turbulence modelling knowledge
Velocity field and contours of heat flux dissipated on
a machine with external cooling (Boglietti, 2009)
Surface mesh and velocity contours in a Valeo Starter-Generator (Jandaud,
2013)

34. 34
Summary of the different techniques
• All the techniques are complementary, with pros and cons
• LPTN: ideal for the early stage design of electric machines and for
optimization, gives a quick overview of the cooling in the machine
• FEM: ideal to detect eventual hotspots and model more complex geometries
(wires in slot)
• CFD: no need of empirical data but very high computation times, can be used
for validation of LPTN model
• All of these methods can be combined
• Example: CFD can be used to determine convective HTC and flow in isolated
parts of the machines (air-gap, around windings, etc.) the results can be then
used for in a thermal network or a FEM simulation.
Hot spot detection due to the air flow
using CFD in a salient pole machine
(Lancial, 2017)

35. 35
Anisotropy of materials in simulations
Windings modeling
• Windings in slots are copper wires with insulation
• Copper is a very good thermal conductor
• Electric insulators are good thermal insulators
• Using an equivalent material, radial and tangential conductivity << axial
conductivity
Laminations
• Cores are constituted of steel sheets packed with insulation layers between
them
• Axial conductivity < tangential and radial conductivities
Different types of windings arrangement
(hairpin, round wires, Litz wires) in slots (Liu,
2017)

36. 36
Steady vs Unsteady simulations
• Most of the simulation techniques are done using steady state analysis
• Time to reach thermal steady state >> electromagnetic steady state
• For a large machine (ie. wind turbine generator), steady state can be reached
in ~10 hours
• For non constant load (car motors, wind turbines), steady state analysis is not
enough
• Unsteady calculations need a lot of resources, CFD is often not an option
• For LPTN, unsteady equation is 𝐶𝐶
𝑑𝑑𝑑𝑑
𝑑𝑑𝑑𝑑
+ 𝐺𝐺. 𝑇𝑇 = 𝑃𝑃
• The capacitance matrix (𝐶𝐶) is very important for short time heat transfer, but it
is not easy to obtain from supplier datasheet or tests
• Experimental validation is needed
Material 𝒄𝒄𝒑𝒑 (J/kg/K)
Air 1006
Aluminum 890
Copper 385
Epoxy Resins 1000
Plastics 800-1200
Steel 460
Water 4181
Thermal capacities values for common
materials at 20°C

37. 37
Typical uncertainties of thermal simulations
• A good thermal simulation needs a good EM simulation to calculate losses,
location and values of losses are very important
• Boundary conditions need to be as precise as possible (especially for LPTN
and FEM)
• For each methods, mesh / discretization is important, a finer mesh is
needed in zones of high temperature gradient
• Contact resistance is important - by default, contact is assumed perfect but
real contacts increase thermal resistances, small layers of air can be added
to simulate the effect
• Differences between CAD and real geometry (e.g. airflow obstacles)
• CFD models precision +/- 5°C on steady state temperature
• Experimental validation is always important for any type of simulation
Same level of accuracy for a fine LPTN and
a 2D FEM simulation (from MANATEE
software, www.manatee-software.com)

38. 38
Overview of existing software
Examples of Commercial Software
• LPTN: MotorCAD (MDL), SPEED (Siemens)
• FEM (dedicated) : MotorSolve (infolytica),
• FEM (from EM FEM software): Flux (Altair), JMAG (JSOL), Opera
(Cobham)
• CFD packages: Ansys Fluent, Ansys CFX, Star CCM+ (Siemens),
SC/Tetra (MSC)
Opensource/Free Software
• CAD/Meshing: FreeCAD, gmsh, Salome (EDF)
• 2D FEM: FEMM
• 3D FEM: CalculiX, Code_Aster (EDF), Elmer, GetDP
• CFD package: OpenFOAM (ESI)

39. 39
CONCLUSIONS
• Better cooling means higher efficiency, extended lifetime and lower overall cost
• Cooling must be considered at the early electromagnetic design stage, similarly to noise & vibrations
(see tomorrow webinar on 21 Sept 15H CET http://go.leonardo-energy.org/170921MOTORS41_Join.html)
• Simulations methods must be chosen depending on the objectives: Lumped Parameters Network for early
design and FEM/CFD for detailed design.
• Thermal simulation workflow must be adapted and coordinated to the electromagnetic and mechanical
design workflow
• Experiments should be used to regularly check and improve model behavior (e.g. static pressure loss in cooling
chambers, flow rate of heat exchangers, end-winding hot spot, air flow homogeneity)
• Multi-objective optimization algorithms are advised to carry coupled electromagnetic and thermal design of
electric motors

40. 40
REFERENCES
• Bauduin, H., 2014. Contribution expérimentale à l’étude d’écoulements internes avec swirl.
University of Valenciennes.
• Bertin, Y., 1999. Refroidissement des machines électriques tournantes. Techniques de
l’ingénieur Généralités sur les machines électriques tournantes, base docum(ref. article :
d3460).
• Boglietti, A. et al., 2009. Evolution and Modern Approaches for Thermal Analysis of
Electrical Machines. IEEE Transactions on Industrial Electronics, 56(3), pp.871–882.
• Bornschlegell, A.S. et al., 2013. Thermal optimization of a high-power salient-pole electrical
machine. IEEE Transactions on Industrial Electronics, 60(5), pp.1734–1746.
• Davin, T. et al., 2015. Experimental study of oil cooling systems for electric motors. Applied
Thermal Engineering, 75(February 2017), pp.1–13.
• Deeb, R., Janda, M. & Makki, Z., 2012. Prediction of eddy current losses of surface mounted
permanent magnet servo motor. In 2012 XXth International Conference on Electrical
Machines. IEEE, pp. 1797–1802.
• Jandaud, P.-O., 2013. Étude et optimisation aérothermique d’un alterno-démarreur.
University of Valenciennes.
• Kim, J.H. et al., 2017. Design and Analysis of Cooling Structure on Advanced Air-Core
Stator for Megawatt-Class HTS Synchronous Motor. IEEE Transactions on Applied
Superconductivity, 27(4), pp.1–7.
• Lancial, N. et al., 2017. Taylor-Couette-Poiseuille flow and heat transfer in an annular
channel with a slotted rotor. International Journal of Thermal Sciences, 112, pp.92–103.
• Lee, K.H., Cha, H.R. & Kim, Y.B., 2016. Development of an interior permanent magnet
motor through rotor cooling for electric vehicles. Applied Thermal Engineering, 95, pp.348–
356.
• Lungoci, C. & Stoia, D., 2008. Temperature effects on torque production and efficiency of
motors with NdFeB. Revue Roumaine des Sciences Techniques, 53(4), pp.445–454.
• Luomi, J. et al., 2009. Efficiency Optimization of a 100-W 500 000-r/min Permanent-Magnet
Machine Including Air-Friction Losses. IEEE Transactions on Industry Applications, 45(4),
pp.1368–1377.
• Mingda Liu et al., 2017. Thermal management and cooling of windings in electrical
machines for electric vehicle and traction application. In 2017 IEEE Transportation
Electrification Conference and Expo (ITEC). IEEE, pp. 668–673.
• Popescu, M. et al., 2015. Modern heat extraction systems for electrical machines - A review.
In 2015 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD).
IEEE, pp. 289–296.
• Putra, N. & Ariantara, B., 2017. Electric motor thermal management system using L-shaped
flat heat pipes. Applied Thermal Engineering, pp.1–8.
• Renap, A., 2015. Direct Cooled Laminated Windings - Radially Displaced Laminated
Winding Segments, Lund.
• Satrústegui, M. et al., 2016. Design criteria for water cooled systems of induction machines.
Applied Thermal Engineering, 114, pp.1018–1028.
• Sebastian, T., 1993. Temperature effects on torque production and efficiency of PM motors
using NdFeB magnets. In Conference Record of the 1993 IEEE Industry Applications
Conference Twenty-Eighth IAS Annual Meeting. IEEE, pp. 78–83.
• Staton, D., 2014. Thermal analysis of traction motors. In 2014 IEEE Transportation
Electrification Conference and Expo (ITEC). IEEE, pp. 1–139.
• Tuysuz, A. et al., 2017. Advanced Cooling Methods for High-Speed Electrical Machines.
IEEE Transactions on Industry Applications, 9994(c), pp.1–1.
• Vu, D.T. & Hwang, P., 2013. New Cooling System Design of BLDC Motor for Electric Vehicle
Using Computation Fluid Dynamics Modeling. Journal of the Korean Society of Tribologists
and Lubrication Engineers, 29(5), pp.318–323.
• Wang, A., Heming Li & Cheng-Tsung Liu, 2008. On the Material and Temperature Impacts
of Interior Permanent Magnet Machine for Electric Vehicle Applications. IEEE Transactions
on Magnetics, 44(11), pp.4329–4332.
• Yang, Y. et al., 2017. Thermal management of electric machines. IET Electrical Systems in
Transportation, 7(2), pp.104–116.

41. 41
THANK YOU FOR YOUR ATTENTION
www.eomys.com
Q&A SESSION