Technical Brief

Integrated Mechanical and Thermodynamic Optimization of an Engine Linkage Using a Multi-Objective Genetic Algorithm

[+] Author and Article Information
Thomas A. Sullivan, Kieran McCabe

Department of Mechanical Engineering,
University of Minnesota,
Minneapolis, MN 55455

James D. van de ven

Assistant Professor
Department of Mechanical Engineering,
University of Minnesota,
Minneapolis, MN 55455
e-mail: vandeven@umn.edu

William F. Northrop

Assistant Professor
Department of Mechanical Engineering,
University of Minnesota,
Minneapolis, MN 55455

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 20, 2014; final manuscript received November 18, 2014; published online December 8, 2014. Assoc. Editor: Gary Wang.

J. Mech. Des 137(2), 024501 (Feb 01, 2015) (4 pages) Paper No: MD-14-1063; doi: 10.1115/1.4029220 History: Received January 20, 2014; Revised November 18, 2014; Online December 08, 2014

In order to improve the thermodynamic efficiency of an internal combustion engine (ICE), a Stephenson-III six-bar linkage is optimized to serve as a replacement for the traditional slider–crank. Novel techniques are presented for formulating the design variables in the kinematic optimization that guarantee satisfaction of the Grashof condition and of transmission angle requirements without the need for an explicit constraint function. Additionally, a nested generalization of the popular NSGA-II algorithm is presented that allows simultaneous optimization of the kinematic, dynamic, and thermodynamic properties of the mechanism. This approach successfully solves the complex six-objective optimization problem, with challenges for future refinement including improvement of the combustion simulation to attain better accuracy without prohibitive computational expense.

Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.


Heywood, J. B., and Welling, O. Z., 2009, “Trends in Performance Characteristics of Modern Automobile SI and Diesel Engines,” SAE Int. J. Engines, 2(1), pp. 1650–1662. [CrossRef]
Shaik, A., Moorthi, N. S. V., and Rudramoorthy, R., 2007, “Variable Compression Ratio Engine: A Future Power Plant for Automobiles—An Overview,” Proc. Inst. Mech. Eng., Part D, 221(9), pp. 1159–1168. [CrossRef]
Ozcan, H., and Yamin, J. A., 2008, “Performance and Emission Characteristics of LPG Powered Four Stroke SI Engine Under Variable Stroke Length and Compression Ratio,” Energy Convers. Manage., 49(5), pp. 1193–1201. [CrossRef]
Yamin, J. A., and Dado, M. H., 2004, “Performance Simulation of a Four-Stroke Engine With Variable Stroke-Length and Compression Ratio,” Appl. Energy, 77(4), pp. 447–463. [CrossRef]
Lipson, H., 2008, “Evolutionary Synthesis of Kinematic Mechanisms,” Artif. Intell. Eng. Des. Anal. Manuf., 22(03), pp. 195–205. [CrossRef]
Clune, J., Beckmann, B. E., Pennock, R. T., and Ofria, C., 2011, “Hybrid: A Hybridization of Indirect and Direct Encodings for Evolutionary Computation,” Advances in Artificial Life. Darwin Meets von Neumann, Springer, Berlin, Germany, pp. 134–141.
Sibling, K., and Woschni, G., 1979, “Experimental Investigation of the Instantaneous Heat Transfer in the Cylinder of a High Speed Diesel Engine,” SAE Technical Paper No. 790833. [CrossRef]
Heywood, J., Higgins, J. M., Watts, P. A., and Tabaczynski, R. J., 1979, “Development and Use of a Cycle Simulation to Predict SI Engine Efficiency and NOx Emissions,” SAE Technical Paper No. 7902981. [CrossRef]
Arakelian, V., and Smith, M., 1999, “Complete Shaking Force and Shaking Moment Balancing of Linkages,” Mech. Mach. Theory, 34(8), pp. 1141–1153. [CrossRef]
Sobieszczanski-Sobieski, J., 1982, “A Linear Decomposition Method for Large Optimization Problems: Blueprint for Development,” NASA, Washington, DC, Technical Report No. NASA-TM-83248.
Sobieszczanski-Sobieski, J., James, B. B., and Dovi, A. R., 1985, “Structural Optimization by Multilevel Decomposition,” AIAA J., 23(11), pp. 1775–1782. [CrossRef]
Sullivan, T. A., and van de ven, J. D., 2014, “Multi-Objective, Multi-Domain Genetic Optimization of a Hydraulic Rescue Spreader,” Mech. Mach. Theory, 80, pp. 35–51. [CrossRef]
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T., 2002, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II,” IEEE Trans. Evol. Comput., 6(2), pp. 182–197. [CrossRef]


Grahic Jump Location
Fig. 3

Determination of minimum connecting rod length

Grahic Jump Location
Fig. 4

Nested optimization structure

Grahic Jump Location
Fig. 5

Skeleton diagram of typical solution




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