Calculation of Friction in High Performance Engines
Ricardo Software European User Conference 2010
Phil Carden
Ricardo UK
www.ricardo.com
RD.10/174701.1
© Ricardo plc 2010
Presentation contents

Introduction

Some general comments and issues

Semi-empirical models  FAST

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Introduction

Minimising friction in motorsport engines is vital because
– power is required elsewhere…
– high friction often means high wear
– high friction leads to unnecessary heat generation and greater need for cooling

Knowledge of friction level is required
– to evaluate potential of alternative low friction designs, coatings etc
– as input to performance simulation models

Measurement of engine friction is
– highly problematic, particularly at high engine speed
– the results are often obtained too late to make key design changes
– but measurements are useful for validation of calculation methods

Analytical tools are beginning to reach required level of fidelity
– but there are still some problems and mysteries…
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Presentation contents

Introduction

Some general comments and issues

Semi-empirical models  FAST

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Which losses are included in “engine friction” ?
Definitely included
Piston ring/liner friction
Piston skirt/liner friction
Small end bearing friction
Big end bearing friction
Main bearing friction
Thrust bearing friction
Valve train friction
Camshaft bearing friction
Optional
Definitely not included
Losses due to pumping of
crankcase gas below pistons
Pumping of gas above piston
Windage losses in engine
Oil churning losses in engine
Power required to drive
auxiliaries (oil pump, water
pump, alternator)
Transmission losses (gears,
bearings, seals, windage, oil
churning etc)
Timing drive friction
Balancer bearing friction
Seal friction
Auxiliaries friction (oil pump,
water pump, alternator,
scavenge pumps etc)
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Stribeck curve
Friction coefficient at any lubricated contact depends on relative speed, normal load, oil
viscosity, shape of contacting parts, roughness of contacting parts, temperature,
materials of contacting parts etc
0.22
Boundary
lubrication
Mixed
lubrication
0.2
0.18
Elastohydrodynamic
lubrication
Hydrodynamic
lubrication
Cam/follower
0.16
friction coefficient

Piston rings / liner
0.14
0.12
Crankshaft bearings
0.1
0.08
0.06
0.04
0.02
0
0
2
4
6
8
10
12
14
16
18
20
Duty parameter (viscosity x speed / load)
or specific film thickness (film thickness / surface roughness)
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How to measure friction ?
Motored test
Description
Simply connect engine to motor


Drive the engine without firing and
measure the torque

Need to control temperature of oil and
water carefully



Test can be extended by progressively
stripping engine to give approximate
breakdown in friction by subsystem

Issues
Fired test
Operate engine normally
Measure cylinder pressure (with very
good knowledge of TDC) and brake torque
as accurately as possible
Calculate FMEP from IMEP – BMEP
Can extend test to make more detailed
measurements

When the whole engine is motored then  FMEP is small compared to IMEP and
pumping loss cannot be separated from
BMEP so any measurement error is
friction by measurement
magnified

No combustion so gas load due to
compression only

No way to account for increased local
temperatures due to combustion

Use of more intrusive instrumentation
usually involved changes to components
and this can affect durability

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What kinds of calculation are performed ?
Semi-empirical approach
Advantages

Very quick to set up and run
Can potentially account for most
sources of loss

Limitations

Need lots of test data to develop tool
Accuracy depends of how similar
engine is to those in database

Cannot accurately predict effect of
detail design changes

Advanced CAE approach
Potentially good accuracy for any
contact if suitable model is available

Can account for differences in load,
detailed component geometry, oil grade,
temperature etc


Potentially long set up times

Potentially long run times
Need different tools to analyse all
contacts


Some losses are very difficult to model

Easy to lose sight of “big picture”
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Some special problems of motorsport engines
Friction testing usually calls for prolonged operation
under stabilised conditions
– Many motorsport engines cannot be operated under
stabilised conditions at high speed/load
– During a race the piston temperature varies
significantly and can approach the limit at end of
straights after ~15 seconds
450
average piston temperature (deg C)

– In typical passenger car engine friction reduces from
initial value for at least 20-30 hours
– Motorsport engines are sometimes used straight from
new build so friction level is reducing all the time
300
250
200
150
Simulation of 1 lap at Monza
100
50
0
10 20 30 40 50 60 70 80 90 100 110
time (sec)
2.2
2
1.8
1.6
FMEP (bar)
Motorsport engines are often not run-in properly before
use
350
0
– If the engine is held at full load the piston temperature
will rise significantly affecting clearances, local oil
temperature and so piston friction before failure

400
1.4
1.2
Measurement on passenger
car engine at 4000 rpm
5% reduction in 40 hours
1
0.8
0.6
0.4
0.2
0
0
5 10 15 20 25 30 35 40 45 50 55 60
Time (hours)
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Presentation contents

Introduction

Some general comments and issues

Semi-empirical models  FAST

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Semi-empirical models - FAST

FAST (Friction Assessment Simulation Tool) is a semi-empirical engine friction
prediction program used internally by Ricardo

FAST predicts friction loss across the engine speed range for individual subsystems
and for the whole engine

FAST uses semi-empirical equations
– Coefficients and exponents were developed by Ricardo to give improved agreement
with the latest measured data obtained from motored teardown tests on modern
passenger car engines and with other published measured data
– New equations were developed for systems not covered by published sources
– Latest version extended to enable prediction of friction under fired conditions

FAST currently requires ~50 input values such as bore, stroke, bearing diameter, valve
train type etc. to make a prediction of motored friction loss
– All input values can be obtained easily from drawings or components
– More detailed information such as cylinder pressure, piston mass, rod mass, ring
tension etc. is required to calculate the increase in piston friction under fired engine
conditions
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Typical results for reciprocating group
CPMEP
CPMEP
FIRST RING
SECOND RING
OIL CONTROL RING
PISTON SKIRT
BIG END BEARINGS
0.9
SECOND RING
Engine speed (rpm)
7000
7000
6500
6000
5500
5000
4500
4000
3500
0
3000
0
2500
0.1
2000
0.1
6500
0.2
6000
0.2
0.3
5500
0.3
0.4
5000
0.4
0.5
4500
0.5
0.6
4000
0.6
0.7
3500
MEASURED
0.7
0.8
3000
BIG END BEARING
2500
PISTON SKIRT
1000
Gasoline reciprocating group friction - full load (bar)
OIL CONTROL RING
0.8
2000
FIRST RING
1500
0.9
1500
Prediction
under full load
conditions
shows
significant
increase in
friction at top
piston ring and
skirt
1
1000

Predictions
under motored
conditions
compared with
measured data
from motored
teardown test
Gasoline reciprocating group friction - motored (bar)

1
Engine speed (rpm)
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V6 gasoline valvetrain group friction (bar)
0.35
WINDAGE
0.3
SEALS
MAINS BEARINGS
0.25
MEASURED DATA
0.2
0.15
0.1
0.05
0
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500
TIMING BELT
DIRECT ACTING HYDRAULIC VALVETRAINS
CAMSHAFT SEALS
CAMSHAFT BEARINGS
MEASURED DATA
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500
Engine speed (rpm)
Engine speed (rpm)
0.2
0.2
FAST V2
Measured data
0.18
I4 gasoline alternator friction (bar)
Results
accurate to
+/-20% for
each
subsystem
and often
much better
than this
I4 gasoline oil pump friction (bar)

V6 gasoline crankshaft group friction (bar)
Typical results for other systems
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
1000
1500
2000
2500
3000
3500 4000
4500
Engine speed (rpm)
5000
5500
6000
0.18
0.16
FAST V2
Measured data
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
1000
1500 2000
2500 3000
3500
4000 4500 5000 5500 6000
Engine speed (rpm)
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Typical results for high performance sports car engine
2.4
Auxiliaries group
2.2
Crankshaft group
Crankshaft group
2
8000
7500
7000
6500
6000
8000
7500
7000
6500
6000
0
5500
0
5000
0.2
4500
0.2
4000
0.4
3500
0.4
3000
0.6
2500
0.6
5500
0.8
5000
0.8
1
4500
1
1.2
4000
1.2
1.4
3500
1.4
1.6
3000
Whole engine - full load (bar)
1.6
2000
Reciprocating group
1.8
Reciprocating group
1500
1.8
Valvetrain group
2500
Valvetrain group
1000
2
2000
Auxiliaries group
2.2
1500
FAST has
not been
validated
for
engines
designed
to rev
higher
than 8000
rpm
2.4
1000

For whole
engine
friction the
results are
generally
accurate
to within
+/-10%
Whole engine - no load (bar)

Engine speed (rpm)
Engine speed (rpm)
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Presentation contents

Introduction

Some general comments and issues

Semi-empirical models  FAST

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Piston assembly friction prediction

Piston assembly friction
– involves losses at many sliding interfaces
– is very difficult to measure even if cost is not an issue

Analysis can offer insights not possible by measurement

Need for validated software but
– Losses and rings and skirt are inter-related
– Some key inputs are hard to determine
• Temperature of surfaces and oil
• Film thickness on liner
• Worn surface shapes of skirt and rings
– The lubrication regime, and so the effective friction
coefficient, , can change dramatically during each
half stroke
rings
skirt
• boundary at end of stroke ( = ~0.1)
• hydrodynamic at mid stroke ( = ~0.005)
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Ricardo Software - PISDYN and RINGPAK

PISDYN can calculate
– friction loss due to oil shearing
effects and asperity contact
• at skirt/liner contact
• at small end bearing
– piston secondary motion
– wear loads
Top Ring Groove
Friction Force
– oil consumption
– blow-by and blow-back
Crown Land
Profiles
Bore Temps.
(Viscosity effect)
Asperity
Contact
Skirt Oil Film
Hydrodynamics
(Pressure)
RINGPAK can calculate
– friction loss due to oil shearing
effects and asperity contact
• at each ring/liner contact
– wear loads
Bore Distortion
Crown Contact
and Friction
Cylinder
Dynamics

Secondary Motions
Lubrication
Elastic
Deformation
Thermal / Pressure
Inertial Skirt
Deformation
Cut Outs
Cylinder oil
evaporation
Ring lubrication,
friction
Dispersed
oil flow
Inter-ring
gas flows
Ring
dynamics
Ring - bore
conformability
Piston tilt
Oil supply
Pin bearing
eccentricity
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Model validation at low engine speed

Predictions validated at low engine speed (up to 2500
rpm) using force difference method

Measured cylinder pressure, connecting rod strain,
crankshaft angular position, liner temperature, piston
temperature etc.

Piston friction force calculated from gas force, inertia
force and rod force

Future plans for validation at higher speed as part of
ENCYCLOPAEDIC project
Results at
2000 rpm
full load
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Experience at high speed

Ricardo have used PISDYN and
RINGPAK to calculate piston friction at
very high engine speeds
– Credible ring/liner friction results
obtained from RINGPAK
– But at high speed losses are
dominated by piston/skirt asperity
contact which is predicted to occur in
each stroke even for a well-developed
piston skirt profile

rings
rings
Skirt/liner friction power loss shows strong
sensitivity to
– component temperature
• governs clearance, component
distortion, and local oil temperature
– oil supply assumptions
skirt
– component surface texture
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High Speed Case Study

Predicted result shows asperity contact pressure at 15000 rev/min
Wear region above rings
Each skirt has patches of wear,
either side of the central region
And
Centrally under the rings
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Presentation contents

Introduction

Some general comments and issues

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Fluid film bearing friction

0.30
Journal bearings normally operate in the
hydrodynamic lubrication regime
Total Main Bearing FMEP (bar)

Losses are dominated by oil shearing effects
– Relatively easy to quantify using simple
bearing analysis methods
– Can be used to study the effects of bearing
dimensions, clearance, oil viscosity etc
0.25
0.20
0.15
Oil A
Oil B
0.10
0.05
0.00
4000
6000
8000
10000
12000
14000
16000
18000
Engine Speed (rpm)
1
2
Surface contact (and so boundary or mixed
lubrication) is possible during running-in
process or if bearing is overloaded
– Friction prediction is theoretically possible
using elasto-hydrodynamic analysis with
asperity contact model but
3
4
5
6
• Measured worn axial bearing profiles
and distorted shapes are needed for
sensible results
• so not very useful for design
No axial profile
Bearing wear depth (µ)

Main 2
rear
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Axial profile
Bearing axial position (mm)
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Camshaft bearing friction – effect of ENGDYN model level
100

Front camshaft bearings often exhibit edge wear due to
loads from the timing drive
90
– This wear usually occurs during run-in period and
then stabilises
70
ENGDYN used to predict friction at camshaft bearings
– Simple rigid model gives power loss due to oil shear
effects
– With flexible camshaft model edge contact leads to
high friction loss
– When worn profile is introduced friction loss is
similar to results from simple model
80
power loss (W)

60
50
40
30
20
statically determinate loading
10
dynamic loading
dynamic loading - with axial profile
0
600
800
1000
1200
1400
1600
1800
2000
camshaft speed (rpm)
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Presentation contents

Introduction

Some general comments and issues

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Crankcase pumping loss - WAVE

Crank case pumping incurs a power loss
– Power required to pump crankcase gas from one
bay to the next as the pistons move up and down
– This can be significant loss on high speed
engines
• so “dry sump” designs with scavenge pumps
are often used to minimise this

Ricardo and others have used 1D gas dynamics
modelling software such as WAVE to predict crank
case pumping loss with some success
– Complex geometry of crank case from CAD and
then automatically reduced to 1D network
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Crankcase pumping loss - WAVE
CPMEP
BREATHER AREA
Max CPMEP at
a Critical
Breather Area
> Critical Breather Area
 Losses reduce with
increase in area
 Reduced resistance to
inter-bay flow exchange
0
-0.02
-0.04
< Critical Breather Area
 Losses increase with increase in area
 Increasing inter-bay flow exchange
 Reduced recovery of compression work
CPMEP (bar)
-0.06
-0.08
-0.1
7000
-0.12
8500
11000
-0.14
13500
-0.16
16000
-0.18
0
300
600
900
1200
1500
2
EFFECTIVE BREATHER AREA (mm )
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Crankcase pumping loss - WAVE
Inter-bay breathing
holes removed
Single external breather
exit through balancer
shaft center
4 scavenge points
ENGINE SPEED (rpm)
8000
10000
12000
14000
16000
18000
20000
22000
0.0
-0.05
-0.5
-0.10
-1.0
-0.15
-1.5
-0.20
-0.25
0.38
bar
-0.30
4.7
kW
-2.0
-2.5
-3.0
-0.35
-3.5
-0.40
-4.0
-0.45
-4.5
-0.50
-5.0
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POWER (kW)
Wet
Sump
CPMEP (bar)
6000
0.00
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Dry
Sump
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Presentation contents

Introduction

Some general comments and issues

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Valve train friction prediction

At system level valve train friction is reasonably well-understood
– The mean friction level of valve trains can be measured by driving the camshaft using
an electric motor and measuring mean drive torque

However
– These system level measurements mask the fact that the detailed sources of loss are
not very well understood
– Especially since the measurements often include the timing drive as well as the valve
train
0.6
Motorsport engines nearly always have
sliding contacts between cam and
tappet to enable use of a lightweight
follower and optimise high speed
dynamics
– Friction loss is dominated by losses
at the these highly-loaded sliding
contacts
0.5
FMEP (bar)

0.4
0.3
total gear losses
0.2
camshaft bearings
tappet/bore contacts
0.1
cam/tappet contacts
0
9000
10000
11000
12000
13000
14000
15000
16000
Engine speed (rpm)
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Cam/follower friction – sliding contact
VALDYN can calculate friction power loss at sliding
contacts between cam/tappet or cam/follower
– Friction due to oil shear and asperity contact are
calculated separately
– Friction is therefore dependent on oil viscosity as
well as surface texture
– The model also considers
• friction between tappet and cylinder
• tappet rotation
0.060
Mean Effective Friction Coefficient

0.050
0.040
0.030
Oil A
Oil B
0.020
0.010
0.000
4000
6000
8000
10000
12000
14000
16000
18000
Engine Speed (rpm)
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Timing drive friction - VALDYN
VALDYN has the capability to calculate
the losses in chain timing drives
– Models have been validated validated
against measured data at passenger
car engine speeds
– Results can be very dependent on
tensioner design
1800
1600
1400
power loss (W)

link/guide
roller/sprocket
pin/bush
1200
cam bearings
1000
idler bearings
800
measured
600
400
200
0
1000
1500
2000
2500
3000
3500
4000
4500
5000
5500
engine speed (rpm)
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Timing drive friction - VALDYN

VALDYN has gear models for
calculation of contact forces and
sliding speeds
– Friction coefficients can be entered
to calculate losses at gear meshes
– But actual losses in high speed
gears are mostly caused by
windage and oil churning effects
which cannot be modelled with
confidence

Camshafts
VALDYN can model belt drive
dynamics but detailed sources of loss
are not understood so cannot be
predicted
– Belt material hysteresis?
Tensioner
– Rubbing losses between teeth and
pulleys?
– Pumping air out during meshing?
Crankshaft
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Presentation contents

Introduction

Some general comments and issues

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Case study

The following slides illustrate the use of CAE tools and the results of motored teardown
test to understand the distribution of friction in a racing engine

The engine was motored and a 4-stage teardown test was made
– 1 Whole engine with intake and exhaust systems
– 2 Intake and exhaust systems removed
– 3 Cylinder head removed
• including upper timing gears
• Cylinder head removed by plate to maintain bolt loads on structure
• Plate was non restrictive so no pumping losses
– 4 Pistons and rods removed
• Replaced by dummy weights

All stages include driven oil pump, water pump and transmission
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Case study - Valve train group friction



1.8
– Test 2 – Test 3
1.4
Pumping loss under motored
conditions calculated using
WAVE
1.6
FMEP (bar)

2
Measured data obtained by
subtraction
1
0.8
0.2
0
9000
Cam/tappet losses and
tappet/bore losses calculated
using VALDYN
– Windage losses estimated
1.2
0.4
Camshaft bearing friction
calculated using ENGDYN
Gear contact losses estimated
using loads from VALDYN and
friction coefficients
pumping loss
total gear losses
camshaft bearings
tappet/bore contacts
cam/tappet contacts
measured data
0.6
10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
2
1.8
FMEP (bar)

1.6
total gear losses
1.4
camshaft bearings
1.2
1
tappet/bore contacts
0.8
cam/tappet contacts
0.6
measured data minus
predicted PMEP
0.4
0.2
0
9000 10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
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Case study - Reciprocating component group friction

Measured data obtained by
subtraction
– Test 3 – Test 4
2
piston skirt
oil control rings
top piston ring
crankcase pumping
small end bearings
big end bearings
measured data
1.8
1.6



Piston skirt friction loss and
small end bearing loss
calculated using PISDYN
Piston rings friction loss
calculated using RINGPAK
1.4
FMEP (bar)

1.2
1
0.8
Crankcase pumping loss
calculated using WAVE
0.6
Big end bearing loss
calculated using ENGDYN
0.2
0.4
0
9000
10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
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Crankshaft/transmission group friction




Measured data
obtained directly Test 4
Main bearing loss
calculated using
ENGDYN
Windage losses
estimated using simple
approach
Gear contact losses
estimated using simple
approach
Oil pump losses and
water pump losses
estimated
2
FMEP (bar)

1.8
water pump
1.6
gear windage
1.4
oil pump
seals
1.2
balancer windage
1
rolling element bearings
0.8
gear meshes
0.6
crankshaft windage
0.4
main bearings
0.2
measured data
0
9000 10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)

Rolling element bearing losses calculated using
calculated loads and friction coefficients

Seals losses estimated using suppliers database
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Whole engine motored friction loss (1)


With motored pumping
losses included
pumping loss
Additional loads at main
bearings due to inertia of
pistons and rods
accounted
Allowance in calculations
for additional loads at
pistons and bearings due
to motored gas force
with cylinder head on
timing gears
4.5
camshaft bearings
tappet/bore contacts
4
cam/tappet contacts
piston skirt
3.5
oil control rings
top piston rings
FMEP (bar)

5
3
crankcase pumping
small end bearings
big end bearings
2.5
water pump
gear windage
2
oil pump
seals
1.5
balancer windage
rolling element bearings
1
gear meshes
crankshaft windage
0.5
main bearings
measured data
0
9000 10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
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Whole engine motored friction loss (2)


5
Same data but with results grouped
by subsystem
valve trains and drive
4.5
Pumping losses excluded
4
At 15000 rpm
– Crankshaft 25.1%
– Transmission 7.9%
– Pumps 11.4%
– Crankcase pumping 8.5%
– Pistons 33.9%
– Valve trains 13.2%
3.5
FMEP (bar)

piston assemblies
crankcase pumping
oil and water pumps
transmission (inc balancer)
crankshaft
measured minus pumping loss
3
2.5
2
1.5
1
0.5
0
9000 10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
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Full load fired friction loss by analysis

Next step was to use CAE tools to model the
following under fired engine conditions
– Piston rings
– Piston skirt
– Small end bearing
– Big end bearings
– Main bearings

The following were accounted for
– Increased cylinder pressure
– Increased component temperature and
effect on clearances
– Increased oil temperature and effect on
oil viscosity
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Full load fired friction loss at piston group (1)
FMEP (bar)
Fired conditions lead to
– slightly higher loss at small end
bearings
– no significant change at top piston
rings
– reduced loss at oil control rings
– significantly increased loss at piston
skirt (particularly at lower engine
speeds)
2.50
piston skirts
2.25
2.00
1.00
motored
full load fired
0.75
0.50
0.25
0.00
9000
small end bearings
10000
11000
12000
13000
motored
full load fired
14000
15000
16000
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
9000
top piston rings
10000
11000
12000
13000
motored
full load fired
14000
15000
16000
Engine speed (rpm)
1.50
FMEP (bar)
FMEP (bar)
1.75
1.25
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
9000
Engine speed (rpm)
FMEP (bar)

10000
11000
12000
13000
14000
15000
16000
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
9000
oil control rings
motored
full load fired
10000
Engine speed (rpm)
11000
12000
13000
14000
15000
16000
Engine speed (rpm)
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Full load fired friction loss at piston group (2)
Predicted losses at piston
skirt are highly sensitive to
skirt/liner clearance which is
sensitive to assumed
component temperatures
– Results shown with +/-5
micron clearance
– No change in component
or oil temperatures

Model could be refined with
better knowledge of
component temperatures
2.50
2.25
2.00
1.75
FMEP (bar)

1.50
1.25
1.00
0.75
0.50
0.25
0.00
9000
10000
11000
12000
13000
14000
15000
16000
Engine speed (rpm)
motored
full load fired (nominal)
full load (5um reduced clearance)
full load (5um increased clearance)
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Full load fired friction loss at crank train bearings
0.3
– but similar losses at
high speed as inertia
forces dominate
0.25
FMEP (bar)
Fired conditions lead to
– slightly higher loss at
lower speeds
0.2
0.15
0.1
Main
bearings
motored
full load fired
0.05
0
9000 10000 11000 12000 13000 14000 15000 16000
0.3
Engine speed (rpm)
0.25
FMEP (bar)

0.2
Big end
bearings
0.15
motored
full load fired
0.1
0.05
0
9000 10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
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Whole engine full load fired friction loss
5
Results grouped by subsystem

Pumping losses excluded

Measured line is whole engine
motored data for comparison

At 15000 rpm
– Crankshaft 22.2%
– Transmission 6.9%
– Pumps 10.0%
– Crankcase pumping 7.5%
– Pistons 41.9%
– Valve trains 11.5%
4.5
4
valve trains and drive
piston assemblies
crankcase pumping
oil and water pumps
transmission (inc balancer)
crankshaft
measured minus pumping loss
3.5
FMEP (bar)

3
2.5
2
1.5
1
0.5
0
9000 10000 11000 12000 13000 14000 15000 16000
Engine speed (rpm)
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Presentation contents

Introduction

Some general comments and issues

Piston assembly friction  PISDYN and RINGPAK

Fluid film bearing friction  ENGDYN

Crankcase pumping loss  WAVE

Valve train and timing drive friction  VALDYN

Case study

Conclusions
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Conclusions

Overall friction level can be estimated easily based on historical data

If more complex calculations are performed there are many problems
– All major contacts involve asperity contact losses and oil shear losses
– Asperity contact losses dominate if dimensions from drawings are used
• but as components wear during run-in period these losses reduce
– This makes true prediction difficult
• but if worn component geometry and surface roughness data are used as model
inputs then better results are possible

Some interesting insights can be obtained by
– use of relatively inexpensive motored strip test
– combined with use of advanced CAE tools

But to make further progress we need
– measured data from fired engines at high speed to validate software
– improved models of mixed lubrication including 3D surface texture effects
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Thank you for your attention
Any Questions?
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