Research Papers: Design Automation

Sequential Multi-Objective Optimization for Lubrication System of Gasoline Engines With Bilevel Optimization Structure

[+] Author and Article Information
Jizhou Zhang

University of Michigan—Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China

Yu Qiu

SAIC Motor Technical Centre,
Shanghai 201804, China

Mian Li

University of Michigan—Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China;
National Engineering Laboratory for Automotive
Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn

Min Xu

National Engineering Laboratory for Automotive
Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received April 3, 2016; final manuscript received December 8, 2016; published online January 5, 2017. Assoc. Editor: Massimiliano Gobbi.

J. Mech. Des 139(2), 021405 (Jan 05, 2017) (11 pages) Paper No: MD-16-1266; doi: 10.1115/1.4035493 History: Received April 03, 2016; Revised December 08, 2016

The lubrication system is one of the most important subsystems in gasoline internal combustion engines (ICEs), which provides hydrodynamic lubrication for friction pairs. The performance of the lubrication system affects the performance of the engine directly. The objective of this work is to reduce the friction loss of the engine and the driven power of the oil pump through design optimization. Two most important oil consumers in the lubrication system are investigated using multibody dynamics (MBD) and elastohydrodynamics (EHD). Considering that MBD and EHD analyses are time-consuming, Kriging is applied to establish the approximation models for bearings. Multi-objective optimization of bearings based on approximation models is formulated and conducted. Given the difference among multiple cylinders in the engine, a bilevel optimization framework is used to perform bearing optimization. The oil consumption and the friction loss of the bearings are reduced within the entire speed range. After that, the pipe diameters of the lubrication system are optimized with optimized bearings to reduce the flow resistance. With the optimization of both bearings and lubrication pipes in a sequential manner, the oil pressure is maintained at the baseline level while the oil pump size is reduced, and the driven power is averagely dropped over the entire speed range.

Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.


Lo, R. S. , 1971, “ Digital Simulation of Engine Lubrication Systems,” SAE Paper No. 710205.
Chun, S. M. , Y. H., and Jang, S. , 2000, “ A Study on Engine Lubrication System by Optimized Network Analysis—Part I: Case Study,” SAE Paper No. 2000-01-2921.
Chun, S. M. , Park, Y. W. , and Jang, S. , 2000, “ A Study on Engine Lubrication System by Optimized Network Analysis-Part II: Parametric Study,” SAE Paper No. 2000-01-2923.
Klingebiel, F. , and Kahlstorf, U. , 2000, “ Simulating Engine Lubrication Systems With 1-D Fluid Flow Models,” SAE Paper No. 010284.
Cehreli, Z. N. , and Durgun, Z. T. , 2007, “ Lubrication System Development on 5-Cylinder Engine,” SAE Paper No. 2007-01-2577.
Senatore, A. , Cardone, M. , Buono, D. , and Dominici, A. , 2007, “ Fluid-Dynamic Analysis of a High Performance Engine,” SAE Paper No. 2007-01-1963.
Tao, W. , Yuan, Y. , Liu, E. A. , Hill, J. , Zou, Q. , and Barber, G. , 2007, “ Robust Optimization of Engine Lubrication System,” SAE Paper No. 2007-01-1568.
Dowson, D. , and Ashton, J. N. , 1976, “ Optimum Computerized Design of Hydrodynamic Journal Bearings,” Int. J. Mech. Sci., 18(5), pp. 215–222. [CrossRef]
Dowson, D. , Blount, G. N. , and Ashton, J. N. , 1977, “ Optimization Methods Applied to Hydrodynamic Bearing Design,” Int. J. Numer. Methods Eng., 11(6), pp. 1005–1027. [CrossRef]
Xu, H. , Wang, D. C. , and Poynton, W. A. , 1999, “ Effects of Oil Groove Locations on the Performance of the Big End Bearing of a Medium Speed Diesel Engine,” SAE Paper No. 1999-01-1316.
Wang, D. , Parker, D. , and Williams, B. , 2000, “ Correlation of Measured and Predicted Oil Flow for a Big-End Bearing,” SAE Paper No. 2000-01-2919.
Choi, J. , Kim, S. S. , Rhim, S. S. , and Choi, J. H. , 2012, “ Numerical Modeling of Journal Bearing Considering Both Elastohydrodynamic Lubrication and Multi-Flexible-Body Dynamics,” Int. J. Automot. Technol., 13(2), pp. 255–261. [CrossRef]
Xing, H. , Zhang, H. , Wu, Q. , and Duan, S. L. , 2012, “ Full Shafting-Based Elstohydrodynamic Lubrication Simulation for Main Bearings of Marine Diesel Engine,” Adv. Mater. Res., 479–481, pp. 1119–1123. [CrossRef]
Pereira, M. F. S. , and Ambrósio, J. A. , 1995, Computational Dynamics in Multibody Systems, Kluwer Academic Publishers, Dordrecht, The Netherlands.
Papalambros, P. Y. , and Michelena, N. F. , 2000, “ Trends and Challenges in System Design Optimization,” International Workshop on Multidisciplinary Optimization, Pretoria, South Africa.
Guyan, R. J. , 1965, “ Reduction of Stiffness and Mass Matrices,” AIAA J., 3(2), p. 380. [CrossRef]
Reynolds, O. , 1886, “ On the Theory of Lubrication and Its Application to Mr. Beauchamp Tower's Experiments, Including an Experimental Determination of the Viscosity of Olive Oil,” Proc. R. Soc. London, 40(242–245), pp. 191–203. [CrossRef]
Jakobsson, B. , and Floberg, L. , 1957, The Finite Journal Bearing, Considering Vaporization: Das Gleitlager Von Endlicher Breite Mit Verdampfung, Gumpert, Goteberg, Sweden.
Olsson, K. , 1965, Cavitation in Dynamically Loaded Bearing, Scandinavian Univ. Books: Akademiförlaget-Gumpert, Goteborg, Sweden.
Patir, N. , and Cheng, H. S. , 1978, “ An Average Flow Model for Determining Effects of Three-Dimensional Roughness on Partial Hydrodynamic Lubrication,” J. Lubr. Technol., 100(1), pp. 12–17. [CrossRef]
Ma, M. T. , McLuckie, I. R. W. , Poynton, A. , and Garner, D. , 2001, “ An EHD Study of a Connecting Rod Bigend Bearing Including Elasticity and Inertia Effects of the Bearing Structure,” World Tribology Conference, Vienna, Austria.
da Cruz, R. F. , and Galli, L. A. F. , 2010, “ Comparison of Hydrodynamic and Elastohydrodynamic Simulation Applied to Journal Bearings,” SAE Paper No. 2010-36-0360.
Giunta, A. A. , Watson, L. T. , and Koehler, J. , 1998, “ A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models,” NASA Langley Research Center, Hampton, VA, Report No. AIAA-98-4758.
Simpson, T. W. , Poplinski, J. D. , and Koch, P. N. , 2001, “ Metamodels for Computer-Based Engineering Design: Survey and Recommendations,” Eng. Comput., 17(2), pp. 129–150. [CrossRef]
Simpson, T. W. , Booker, A. J. , Ghosh, D. , Giunta, A. A. , Koch, P. N. , and Yang, R.-J. , 2004, “ Approximation Methods in Multidisciplinary Analysis and Optimization: A Panel Discussion,” Struct. Multidiscip. Optim., 27(5), pp. 302–313. [CrossRef]
Sacks, J. , Welch, W. J. , Mitchell, T. J. , and Wynn, H. P. , 1989, “ Design and Analysis of Computer Experiments,” Stat. Sci., 4(4), pp. 409–435. [CrossRef]
Lophaven, S. N. , Nielsen, H. B. , and Søndergaard, J. , 2002, “ DACE, a Matlab Kriging Toolbox,” Informatics and Mathematical Modelling, Technical University of Denmark, DTU, Kongens Lyngby, Denmark.
Srinivas, N. , and Deb, K. , 1994, “ Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms,” Evol. Comput., 2(3), pp. 221–248. [CrossRef]
Workspace, A. V. L. , 2008, “ Excite PowerUnit_UserGuide,” AVL LIST Gmbh, Graz, Austria.


Grahic Jump Location
Fig. 4

Pressure loss in lubrication system

Grahic Jump Location
Fig. 3

Average oil flow rate distribution

Grahic Jump Location
Fig. 2

Simulation model validation

Grahic Jump Location
Fig. 1

Optimization scope in this paper

Grahic Jump Location
Fig. 5

Multibody dynamics model on excite power unit

Grahic Jump Location
Fig. 6

Optimization process

Grahic Jump Location
Fig. 7

Performance of main bearings

Grahic Jump Location
Fig. 8

Performance of conrod bigend bearings

Grahic Jump Location
Fig. 10

Bilevel bearing optimization

Grahic Jump Location
Fig. 9

Pareto front of bearing optimization

Grahic Jump Location
Fig. 11

Oil pressure of the main gallery with optimized bearings

Grahic Jump Location
Fig. 12

Average oil flow rate distribution after bearing optimization

Grahic Jump Location
Fig. 14

Oil pressure of main gallery

Grahic Jump Location
Fig. 15

Oil flow rate of main gallery

Grahic Jump Location
Fig. 16

Pressure loss between main gallery and cylinder head in lubrication system

Grahic Jump Location
Fig. 17

Optimization results of crankshaft friction power loss

Grahic Jump Location
Fig. 18

Saved power loss and proportion of total friction loss

Grahic Jump Location
Fig. 19

Power consumption of oil pump

Grahic Jump Location
Fig. 20

Saved driven power and proportion of baseline driven power

Grahic Jump Location
Fig. 21

Improvement of engine economy by the optimization of lubrication system

Grahic Jump Location
Fig. 13

Pareto front of lubrication pipes



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In