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.
Skip Nav Destination
Article navigation
February 2017
Research-Article
Sequential Multi-Objective Optimization for Lubrication System of Gasoline Engines With Bilevel Optimization Structure
Jizhou Zhang,
Jizhou Zhang
University of Michigan—Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
Search for other works by this author on:
Yu Qiu,
Yu Qiu
SAIC Motor Technical Centre,
Shanghai 201804, China
Shanghai 201804, China
Search for other works by this author on:
Mian Li,
Mian Li
University of Michigan—Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China;
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
Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn
Search for other works by this author on:
Min Xu
Min Xu
National Engineering Laboratory for Automotive
Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Search for other works by this author on:
Jizhou Zhang
University of Michigan—Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
Yu Qiu
SAIC Motor Technical Centre,
Shanghai 201804, China
Shanghai 201804, China
Mian Li
University of Michigan—Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China;
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
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
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. Feb 2017, 139(2): 021405 (11 pages)
Published Online: January 5, 2017
Article history
Received:
April 3, 2016
Revised:
December 8, 2016
Citation
Zhang, J., Qiu, Y., Li, M., and Xu, M. (January 5, 2017). "Sequential Multi-Objective Optimization for Lubrication System of Gasoline Engines With Bilevel Optimization Structure." ASME. J. Mech. Des. February 2017; 139(2): 021405. https://doi.org/10.1115/1.4035493
Download citation file:
Get Email Alerts
Cited By
Multi-Split Configuration Design for Fluid-Based Thermal Management Systems
J. Mech. Des (February 2025)
Related Articles
Multiple Surrogate-Assisted Many-Objective Optimization for Computationally Expensive Engineering Design
J. Mech. Des (May,2018)
Beyond Mean–Variance: The Mean–Gini Approach to Optimization Under Uncertainty
J. Mech. Des (March,2018)
Ranking Ideas for Diversity and Quality
J. Mech. Des (January,2018)
A Novel Sequential Multi-Objective Optimization Using Anchor Points in the Design Space of Global Variables
J. Mech. Des (December,2016)
Related Chapters
A Collaborative Framework for Distributed Multiobjective Combinatorial Optimization
International Conference on Computer and Computer Intelligence (ICCCI 2011)
A Learning-Based Adaptive Routing for QoS-Aware Data Collection in Fixed Sensor Networks with Mobile Sinks
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
A Multi-Objective Optimization Model for Developing Emergency Evacuation Plans (PSAM-0466)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)