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Hinduja Tech Limited A Hinduja Group Company
Lubrication System Analysis and Oil Pump Power Consumption Reduction
Author: Madhusudhan R Co Author: Prasanth B
Contributor: Meenakshi Sundaram I
www.hindujatech.com
Contents
Objective and overview
Methodology
GT-Suite 1D Simulation model
Single cylinder analysis
Component characteristics
Results
Optimisation
Summary
2
Objective and Overview
Flow Distribution and Power Consumption
Product Development Time reduction
Improving System Reliability
Competency Building
1D System Model in GT-Suite
Single cylinder GT-SUITE model
Full scale GT-SUITE model
Validation with test results
Optimisation of configuration
Optimized lubrication system
Lubrication system layout Work flow
3
Methodology
Model Verification
The GT-SUITE-model is validated against the
test bed results and found to have acceptable
correlation with variation of less than 10%.
1
1.5
2
2.5
3
3.5
4
0 1000 2000 3000 4000
MO
G p
res
su
re (
ba
r)
Speed (RPM)
Test result GT - Simulation
Predicted vs Tested Results
•Layout of the system
•Gallery dimension
•Component locations
•Components
Characteristic
•Oil pump
•Oil filter
•Oil cooler
•Piston cooling jet
•HLA
Bearings
1. Predictive method
2. Mean value
Pump
1.Pump flow
2.Pump positive
displacement
3.Pump external gear
4.Pump
5.Detailed Pump model
Clearances
1.Constant
2.Non-constant
Flow
1.Geometry
2.Predictive method
3. Flow map
Lubrication system 1D MODEL GT-SUITE
•Oil characteristics
•Speed and Bearing load
Bearing load
1.Auto
2.User defined
•Analysis
•Periodic analysis
•Explicit Solver
Output
•Gallery pressure
•Bearing performance
•Flow distribution
•Pump flow
•Power consumption
4
GT-SUITE 1D Model
Main bearing Conrod bearing PCN Oil gallery
Cranktrain
Cam bearing Oil cooler and oil filter
Oil Pump
HLA Oil Rail
5
Single Cylinder Analysis
• Optimize bearing groove size
Groove Volume
• To locate oil hole in bearing
Oil hole angle & size
• For optimal gallery pressure
Gallery diameter
Inputs and Considerations
1. Single cylinder pressure profile
2. Constant pump flow based on
flow estimation
Outcome
1. Bearing geometry is finalized
Single cylinder model Objective
Results
Gallery pressure for different oil inlet hole location and diameter 6
Oil Pump Characteristics
Pump type used is Gerotor pump
The Oil pump sizing is done based on the initial
flow estimation
Initial flow estimation is given a flow rate
cushioning of 1.45 times of flow requirement for
vapor loses, pump wear, hot idle condition etc.
Physical model of the pump was tested and flow
rates are input in GT-SUITE model
Pump flow characteristics are imposed in the
Lubrication model through “Pump” template.
Pump map is given for temperature values of 95
and 110˚C
7
Relief Valve Characteristics
Relief valve was constructed as spring based
conventional type
Pressure relief valve senses pump exit pressure
Relief valve is modeled through predictive method
Stiffness of Pressure relief valve is set as 2.95
N/mm
Physical model tested and input to GT-SUITE
model as a ‘FlowMap’ template
Oil Properties
Oil grade used is SAE 5W-30
Properties Unit Value
Kinematic viscosity @ 40˚C cSt 65
Kinematic Viscosity @100˚C cSt 11.2
Density @ 15˚C Kg/m3 863
0
5
10
15
20
25
30
35
0 200 400 600 800
Flo
w (
lpm
)
Pressure (kPa)
Relief Valve Characteristics
8
Oil filter & PCN Characteristics Oil cooler and oil filter are given are imposed in the GT-
SUITE model in the form of ‘PressureLossConn’ object
The Oil filter are given as Pressure drop vs. Oil flow
rate curves through ‘FlowPDropTable’.
Piston Cooling Nozzle (PCN)
• Piston cooling nozzle is separately made
as a predictive model
•Obtained flow rates are imposed in the
lubrication model as flow map.
•The spring based cooling nozzle’s
stiffness was set to 0.597N/mm
GT-SUITE – PCN Predictive model
0
0.5
1
1.5
2
2.5
0 1 2 3 4 5
Flo
w (
lpm
)
Pressure (bar)
PCN flow map
9
Bearings Characteristics
• Bearings are modeled through Predictive method
• Bearings are assumed to be constant clearances
• Bearings are assumed to remain as circular geometry
• Cylinder pressure profiles calculated from GT-POWER are fed in lubrication model to calculate
bearing loads
• Martin and modified martin equations are chosen for main and conrod bearings respectively
Cylinder Pressure Profile
Design inputs from single cylinder analysis
• Based on single cylinder analysis the following
data were finalized
-Oil entry hole diameter of main bearing
-Oil entry hole location
-Groove depth and width
10
Results Gallery pressure Gallery pressure fluctuation
Flow Distribution Oil film thickness
Max gallery pressure was 502kPa Pressure fluctuation in oil gallery was <50kPa
Oil film thickness in main bearing and
conrod bearing was 0.75 and 0.48microns
11
Optimisation
Objective
•Oil pump power consumption to be reduced
Scope
•Higher gallery pressure observed in prediction
•Flow through relief valve provided large scope
for optimisation
•Relief valve spring optimisation was done GT-
SUITE
Reduced pump flow Optimized relief valve
Pump flow
Relief Valve
Power Saving
Reduce pump flow
Modify relief valve
setting
0
2
4
6
8
10
12
14
16
18
0 100 200 300 400 500 600
Flo
w (
lpm
)
Pressure (kPa) 12
Results Gallery pressure
Flow Distribution Power Consumption comparison
0
50
100
150
200
250
300
350
0 1 2 3 4
Po
we
r (W
)
X1000 RPM
Pump- 1
Pump 2
Film thickness
Oil gallery pressure reduced to 396kPa Film thickness of main bearing and conrod bearing
were 0.71 and .46 microns
13
Summary & Future Work
Influence of various component features on lubrication system studied.
A complete engine model was built in GT-SUITE to estimate system pressure and flow.
To optimize power consumption, pump flow and relief valve characteristics were modified.
The optimized pump flow lowered the operational pressure of oil gallery uncompromised operating
condition for bearings, HLA, turbocharger.
Maximum oil gallery pressure was reduced by 20% without affecting the performance of critical
components
Power saving of 8%was achieved by optimising the oil pump flow and relief valve setting
Future work
Modeling oil pump in 1D platform
Coupling thermal and frictional model with lubrication system to understand the dynamic conditions
Oil carry over estimation and Oil life estimation
14
Contributors
• Meenakshi Sundaram I
• Sriprakash D B
• Balaji V
• Balasubramani K
• Bharathan S
• Vignesh J
• Prasanth B
• Varun V
15
THANK YOU !!!
16