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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.

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References

Figures

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Fig. 1

Optimization scope in this paper

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Fig. 2

Simulation model validation

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Fig. 3

Average oil flow rate distribution

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Fig. 4

Pressure loss in lubrication system

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Fig. 5

Multibody dynamics model on excite power unit

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Fig. 6

Optimization process

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Fig. 7

Performance of main bearings

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Fig. 8

Performance of conrod bigend bearings

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Fig. 9

Pareto front of bearing optimization

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Fig. 10

Bilevel bearing optimization

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Fig. 11

Oil pressure of the main gallery with optimized bearings

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Fig. 12

Average oil flow rate distribution after bearing optimization

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Fig. 13

Pareto front of lubrication pipes

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Fig. 14

Oil pressure of main gallery

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Fig. 15

Oil flow rate of main gallery

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Fig. 16

Pressure loss between main gallery and cylinder head in lubrication system

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Fig. 17

Optimization results of crankshaft friction power loss

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Fig. 18

Saved power loss and proportion of total friction loss

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Fig. 19

Power consumption of oil pump

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Fig. 20

Saved driven power and proportion of baseline driven power

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Fig. 21

Improvement of engine economy by the optimization of lubrication system

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