A Flux Barrier Cooling for Traction Motors in Hybrid Drives

A Flux Barrier Cooling for Traction Motors
in Hybrid Drives
Alexander Nollau and Dieter Gerling, Member, IEEE
Abstract-- This paper presents a detailed cooling approach
for traction motors which are mounted in hybrid electric
vehicle (HEV) or battery electric vehicle (BEV). There are
specific guidelines for the design of a traction motor in hybrid
drives, such as the small and restricted packing area and on
the other side, the need for a high power – and torque –
density. For this vehicle powertrain application the Permanent
magnet synchronous machines (PMSM) is a common choice,
because of a high power density, a high efficiency and a small
package. Nevertheless, this machine type has several
drawbacks on the thermal design side, such as, it is susceptible
to suffer insulations failures of coils and demagnetization of
magnets under severe thermal condition. Therefore, a goal for
every thermal optimization is to increase the cooling and
generate proper heat dissipation to the cooling fluid. This
paper presents a PMSM with flux barriers in the stator and a
detailed view on the cooling system. The cooling system the
flux barriers to increase the cooling effect and therefore,
overcome the drawbacks of the PMSM. A simulation of the
fluid flow is presented by a finite volume Computational
Fluid Dynamic (CFD) model with ANSYS Fluent. This is a
useful tool to analyze the cooling flow in a traction motor with
regard to fluid velocity, flow quantity and pressure drop. In
addition, a Prototype of the cooling system is tested on a test
bench to verify the results.
Index Terms-- Cooling Method, CFD, FEA, permanent
magnet machine, thermal analysis
I. INTRODUCTION
(HEV), the thermal load environment is more complicated.
Predicting an accurate temperature distribution in different
parts of the machine is necessary in order to prevent these
damages. There are different ways to calculate the
temperature distribution inside a machine. On the one hand,
a lumped-parameter approach is used to create a thermal
model [4,5] and on the other hand, there is the finiteelement method which gives a more detailed distribution
inside the electric machine [6]. To calculate the fluid
behavior of the cooling system ANSYS FLUENT is used.
A thermal analysis calculates the temperature distribution
and related thermal quantities in a system or component.
Typical quantities of interest are temperature distribution,
thermal gradients and thermal flux. A fluent analysis
calculates the fluid velocity, flow quantity and pressure
drop. In this paper a steady state fluent analysis is
performed which determines the flow characteristics.
II. PROPOSED COOLING APPROACH
A. Machine Design
The researched machine is a 24-Teeth/28-Poles
permanent magnet (PM) – machine presented in [3]. The
following Fig. 1 shows the geometry of the designed PM
machine. The stator consists of 24 slots and the rotor
consists of 28 rectangular permanent magnets inset in the
rotor core.
T
HE PMSM is the perfect candidate for an electric
vehicle application due to a high efficiency,
compactness, fast dynamics and high torque to inertia ratio
[1, 2]. Especially the PM synchronous machine with
fractional slot concentrated windings (FSCW) is widely
used. The advantage of this solution is a short and complex
end-winding, a high slot filling factor, low cogging torque
and a low cost manufacturing process [3]. A main problem
of this machine type is the temperature sensitivity of the
permanent magnet material. This sensitivity can lead easily
to an irreversible demagnetization of the permanent
magnets. In the application of a hybrid electrical vehicle
Alexander Nollau is with the Institute for Electrical Drives,
Universitaet der Bundeswehr Muenchen, 85579, Neubiberg, Germany
(phone: 0049-89-6004-4416; e-mail: [email protected]).
Dieter Gerling is Head of the Institute for Electrical Drives,
Universitaet der Bundeswehr Muenchen, 85579, Neubiberg, Germany (email: [email protected]).
978-1-4799-7940-0/15/$31.00 ©2015 IEEE
Fig. 1. Geometry of the studied PM Machine.
The presented stator structure uses twelve simple
concentrated coils, twelve stator core modules and also
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TABLE I
THERMAL DATA OF USED MATERIAL
twelve additional stator teeth components of “T-shape”,
which are used as flux-barriers. These flux-barriers
overcome the drawback of concentrated windings, because
they reduce the air-gap flux-density sub-harmonics. The
obtained results show that the torque capability is increased
compared to a conventional design and the torque ripples
are reduced [7]. With these flux-barriers the reduction of
sub-harmonics leads to a decrease of losses inside the PM
machine [8].
B. Cooling Design
This cooling method is based on the conventional design
with a cooling jacket surrounding the stator. Nevertheless,
there is no sheet between the water jacket and the fluxbarriers. Therefore, the cooling fluid will flow inside the
flux-barriers and increase the cooling area significantly. It
has one inlet and one outlet with a diameter of 20 mm,
respectively. The fluid flow zone has a thickness of 3/4 of
the cooling jacket thickness. The flux-barriers are separated
by a thin aluminium sheet from the air-gap. This ensures
that no cooling fluid flows into the air-gap and causes a
short circuit. Fig. 2 shows the radial cooling design.
Material
k (W/(m*K))
cp (J/(kg*K))
ρ (kg/m3)
Iron
Copper
Aluminum
NdFebmagnet
Slot
insulation
Air
Water
50
387.6
210
486
381
896
7600
8978
2707
9
370
7550
0.25
2.2
2000
0.028
0.42
1013
4.12
0.013
1077
Units: W = watt, m = meter, K = kelvin, J = joule, kg = kilogram
B. Numerical Simulation
1) Shear-stress Transport (SST) k-ω Model
The shear-stress transport (SST) k-ω model was
developed by Menter [9] to effectively blend the robust and
accurate formulation of the k-ε model in the near-wall
region with the free-stream independence of the k-ω model
in the far field. The k-ε model gives an isotropic turbulence,
which is constant in all directions. However, very close to
solid walls the fluctuations in the turbulence vary greatly in
magnitude and direction. Therefore, the turbulence cannot
be considered to be an isotropic one [10]. To achieve this,
the k-ε model is converted into a k-ω formulation. The
SST k-ω model is similar to the standard k-ω model, but
includes the following refinements:
• The SST model incorporates a damped crossdiffusion derivative term in the ω equation.
• The definition of the turbulent viscosity is modified
to account for the transport of the turbulent shear
stress.
• The modeling constants are different.
Fig. 2. Preliminary cooling jacket.
III. SIMULATION SETUP
A. Heat Generation
In the finite element model different areas are used for
heat sources (losses) such as ohmic losses in stator
windings, iron losses in the yoke, iron losses in the teeth,
and power losses in the magnets. Table I shows the material
data that were applied for different parts, where k is the
thermal conductivity, cp is the specific heat capacity and ρ is
the density.
The temperature distribution is studied at peak power
condition. This investigation will determine the temperature
distribution inside the electrical machine with the new
cooling method. The power losses can be calculated
analytically or by using FE methods. For each operating
condition, the calculated losses of the electric machine have
to be distributed homogeneously in the components of the
PM machine. A complete loss calculation can be found in
[7].
These features make the SST k-ω model more accurate
and reliable for a wider class of flows than the standard k-ω
model. The reason is that the equations can be integrated
directly to the wall with no need for specialized wall
functions and no special conditions are required at solid
boundaries [11].
2) Transport Equations for the SST k-ω Model
The SST k-ω Model is represented by the following two
equations:
∂
∂
∂
∂k
(ρk ) +
( ρ kui ) =
( Γk
) + Gɶ k − Yk + Sk
∂t
∂xi
∂x j
∂x j
and
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(1)
∂
∂
∂
∂ω
( ρω ) +
( ρωu j ) =
( Γω
) + Gɶ ω − Yω + Dω + Sω
∂t
∂x j
∂x j
∂x j
• There is no influence of temperature rise on the
thermal property of materials
• The insulation material is evenly distributed
and the impregnation is good.
(2)
In these equations, Gɶ k represents the generation of
turbulence kinetic energy due to mean velocity gradients,
and describes the modeling of the turbulence production.
Gω represents the generation of ω, calculated as described
for the standard k-ω model in [12]. Γk and Γω represent the
effective diffusivity of k and ω, respectively. Yk and Yω
represent the dissipation of k and ω due to turbulence. Dω
represents the cross-diffusion term, which blends the two
models together. S k and Sω are user-defined source terms.
The 3D simulations presented in this paper are conducted
by solving the equations using the commercial software
package Ansys FLUENT. The COUPLED scheme is used
as pressure-based solver. Discretization of the transport
equation utilizes the second-order upwind scheme for all
equations. The coupled algorithm solves the momentum
and pressure-based continuity equations together. The full
implicit coupling is achieved through an implicit
discretization of pressure gradient terms in the momentum
equations, and an implicit discretization of the face mass
flux, including the Rhie-Chow pressure dissipation terms.
Convergence is achieved when the scaled residuals reach
10-4 and the mass flow rate difference is minimal, which
typically took about 250 iterations.
3) Boundary Conditions
For a simple thermal analysis, the slot region is modeled
with a homogeneous material (copper), insulated with an
equivalent insulation layer. This insulation layer is
characterized by an equivalent thermal conductivity, keq,
which takes into account the thermal conductivity of the
slot insulation layer, the air-gap between the slot insulation
and the laminations, the insulation varnish of the windings
and the air-gaps between the conductors. It has to be
mentioned here, that the simulations are made for an ideal
case. Therefore keq of the slot insulation layer is taken to be
equal to the thermal conductivity of the slot insulation
material, keq = 0.25 (W/(m*K)). A steady mass flow rate
inlet condition is applied on the inlet of the cooling system.
The mass flow rate is taken to be 10 l/min for all methods
to ensure comparable accuracy [13]. For the flow outlet the
standard pressure outlet conditions were used.
4) Assumption
The following assumptions are made to simplify the
numerical simulation:
• The ambient temperature is constant
• The heat losses are considered
homogenoulys distributed
to
be
IV. SIMULATION RESULTS
A. Enhanced Design
During the design process different optimization steps were
applied to enhance the turbulent flow and therefore,
increase the cooling effect. As shown in Fig. 3 different
parameters (P1, P2, P3) were applied.
Fig. 3. Parameter assignment in the flux barrier area.
During the optimization process the turbulent flow in the
flux barriers was increased significantly from close to 0 m/s
up to 0.128 m/s in average, while the pressure drop changes
only by 24% to 1194 Pa. Fig. 4a and 4b shows the
difference in fluid flow through the flux barriers.
a)
b)
Fig. 4. a) Fluid flow through the preliminary cooling channel; b) Fluid
flow through the final cooling channel.
B. Thermal Analysis
The equivalent thermal conductivity for the transition
between stator yoke and cooling channel is calculated
according to [14]. Simulations of the transient temperature
distribution are made using initial conditions. The initial
temperature for all elements of the machine is taken to be 0
°C.
The temperature difference is about 20 K for the two
cooling methods. The final maximum temperature for the
flux barrier cooling is 190 °C in the slot as an end
temperature. The final temperature for the standard cooling
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is 210 °C in slot. Fig. 5 and Fig. 6 show the temperature
distribution with and without the flux barrier cooling.
V. VERIFICATION
A. Pressure Drop
The machine is still in production and the final results
will be presented as soon as possible. Nevertheless, a
prototype of the cooling jacket was build and measured.
Fig. 8 shows the measurement setup. The calculated
pressure drop could be confirmed by the experiment.
Fig. 5. Thermal Analysis for the flux barrier cooling.
Fig. 8. Measurement Setup
Table II shows the results of the pressure drop
measurement. All measurements are done at a fluid
temperature of 35 °C. This is due to the used material for
the prototype cooling jacket.
Fig. 6. Thermal Analysis for a standard cooling jacket.
TABLE II
COMPARISON BETWEEN SIMULATED AND MEASURED PRESSURE DROP
It should be mentioned here that the fluid will be heated
up as it flows from the inlet to the outlet. The temperature
distribution of the PMSM will not be axially symmetrical.
The difference between the inlet temperature and outlet
temperature is about 10 K. This leads to a higher
temperature in the windings near the outlet. Therefore, the
inlet and outlet position were changed accordingly to [15].
Fig. 7 illustrates the new position for the inlet and outlet.
This decreases the inlet and outlet temperature difference to
4 K.
Fluid Flow
Simulation
[Pa]
Measurement
[Pa]
3 l/min
5 l/min
7 l/min
10 l/min
431
900
1535
2581
652
940
1755
3311
Units: Pa = Pascal
It can easily be seen that the Measurement is in the range of
the simulation. Based on the setup and measurement
method the deviation can be explained. Also the used
material explains the difference in the results, because the
exact roughness constant for the wall is not kown.
Fig. 7. New inlet and outlet position.
B. Ink – testing
To visualize the flow inside the cooling jacket and the
flux barriers ink is injected in the fluid. The bluish color of
the ink highlights the fluid flow and therefore, a detailed
view of the distribution of the flow can be seen. Fig. 9
shows this distribution. It is also visible that the fluid will
flow through every area of the flux barrier and no deadwater zone will be created. This leads to a highly turbulent
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flow which enhances the cooling effect of the flux barrier
cooling jacket.
reach 90 % of the end temperature of 35 °C. Fig. 10 a) - e)
shows the designated procedure.
a) Closed inlet valve
b) Open valve – time: 20 seconds
c) Open valve – time: 40 seconds
Fig. 9. Water with injected ink flows through the cooling jacket.
C. Thermography techniques
To check if all areas of the cooling jacket will heat up
homogenously the following procedure was accomplished:
The cooling fluid is set to 10 °C. This will cool down the
entire cooling jacket to the temperature of the fluid. The
water inlet valve is then closed and the cooling fluid was
heated up to 35 °C outside the cooling jacket. After the
heating the inlet valve was opened again and the heating of
the cooling jacket is captured by a thermographic camera.
Through this test it can be observed that the flux barrier end
region is not heated up homogenously. This is based on the
fact, that the lower part of the flux barrier is not perfused as
the rest of the flux barrier. The region is quite marginal,
though. Therefore, the influence for the cooling can be
neglected. It takes two minutes for the cooling jacket to
d) Open valve – time: 60 seconds
d) Open valve – time: 120 seconds
Fig. 10. Fluid heats up the cooling jacket
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VI. CONCLUSSION
This report uses a finite-element method (FEM) to model
the fluid flow inside a new designed cooling jacket. The
studied machine is a 24-Teeth/28-Poles PM machine. The
PM machine is simulated for the transient-state condition.
Based on the results in the previous sections, the following
conclusions can be stated: The flux barrier cooling can
enhance the cooling by 10 % for this PMSM. The
temperature difference is 20 K for peak power condition in
the slot region. With the support of CFD it was possible to
predict and model the fluid flow inside the new designed
cooling jacket. A more turbulent flow was created, which
results in a higher heat dissipation. Due to the turbulent
flow and the enhanced cooling area, this cooling method
can be a good alternative to the standard jacket in a small
and harsh environment. Based on the preliminary
measurements the simulation prediction can be confirmed.
The next steps of this work consist in testing the final motor
and validate the numerical simulation.
VII. REFERENCES
[1]
J. X. Fan, C. N. Zhang, Z. F. Wang, et al.: “Thermal Analysis of
Permanent Magnet Motor for the Electric Vehicle Application
Considering Driving Duty Cycle”, IEEE Transactions on Magnetics,
2010.
[2] F. Jinxin, Z. Chengning, W. Zhifu, et al.: “Thermal analysis of water
cooled surface mount permanent magnet electric motor for electric
vehicle”, International Conference on Electrical Machines and
Systems, ICEMS, 2010, Incheon, South Korea.
[3] G. Dajaku, D.Gerling, "Low Costs and High-Efficiency Electric
Machines," 2nd International Electric Drives Production Conference
2012, EDPC-2012, Erlangen-Nürnberg, Germany, 2012
[4] G. Dajaku, D. Gerling: “An Accurate Electromagnetic and Thermal
Analysis of Electric Machines for Hybrid Electric Vehicle
Application”, The 22nd International Battery, Hybrid and Fuel Cell
Electric Vehicle Symposium & Exposition, 2006, Yokohama, Japan.
[5] D. Gerling, G. Dajaku: “Thermal calculation of systems with
distributed heat generation”, The Tenth Intersociety Conference on
Thermal and Thermomechanical Phenomena in Electronics Systems,
ITHERM '06, 2006, San Diego, CA.
[6] A. Nollau, D. Gerling, "A new cooling approach for traction motors
in hybrid drives", 2013 IEEE International Electric Machines &
Drives Conference (IEMDC), pp.456-461, 12-15 May 2013.
[7] Spas, S.; Dajaku, G.; Gerling, D., "Comparison of PM machines with
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[8] G. Dajaku, D. Gerling, "A Novel Tooth Concentrated Winding with
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[9] F. R. Menter. "Two-Equation Eddy-Viscosity Turbulence Models
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VIII. BIOGRAPHIES
Alexander Nollau was born in Dresden, Germany, on June 20, 1987. He
received the M.Sc. degree in electrical engineering from the Universität
der Bundeswehr München (University of Federal Defense Munich,
Germany). During his studies he had multiple stays at the Technical
University Dresden and the Lawrence Berkeley National Laboratory,
USA. He is currently with the Universität der Bundeswehr München,
Chair of Electrical Drives and Actuators and is working on his Ph. D.
thesis in the field of cooling electrical machines for traction drives.
Dieter Gerling Born in 1961, Prof. Gerling got his diploma and Ph.D.
degrees in Electrical Engineering from the Technical University of
Aachen, Germany in 1986 and 1992, respectively. From 1986 to 1999 he
was with Philips Research Laboratories in Aachen, Germany as Research
Scientist and later as Senior Scientist. In 1999 Dr. Gerling joined Robert
Bosch GmbH in Bühl, Germany as Director, being responsible for New
Electrical Drives and New Systems. Since 2001 he is Full Professor and
Head of the Institute of Electrical Drives at the University of Federal
Defense Munich, Germany.
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