Intelligent Design of Internal Combustion Engine in Hybrid Genetic Algorithm

Jiang Zhu; Ping Yuan Xi

doi:10.4028/www.scientific.net/AMM.26-28.186

Paper Titles

Analysis and Control of Fretting Wear for Blade Bearing in Wind Turbine
p.167

Design and Implement of Project Production Technique Preparation Cooperative Platform Based on Unified Modeling Language
p.171

Decision Process Knowledge Acquisition through Integration of Rough Set and Ontology Technology
p.176

Performance of Wood-Polymer Composite Prepared by In Situ Polymerization of Styrene
p.181

Intelligent Design of Internal Combustion Engine in Hybrid Genetic Algorithm
p.186

Chaos Prediction of Rolling Bearing Friction Torque
p.190

Modeling and Simulation of a Six-Leg-Wheel Hybrid Mobile Robot Based on ADAMS
p.194

Finite Element Analysis for Machine Joint
p.198

Quality Management Mode and Process in Concurrent Engineering
p.204

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 26-28Intelligent Design of Internal Combustion Engine...

Intelligent Design of Internal Combustion Engine in Hybrid Genetic Algorithm

Abstract:

The basic parameters of internal combustion engines reflect the working performance and quality of the internal combustion engine. Therefore it is of great significance to design the operating parameters of vehicle engine by design optimization method. In this paper, hybrid genetic algorithm is adopted to optimize operating parameters of vehicle engine, so that optimization process was simplified and the global optimal solution is ensured reliably. Being satisfied with the heating loading, mechanical loading and the conditions of gas mixture of engine and boundary constraints, the optimization mathematical model is created which is to minimize the heating surface area of engine. Considering the problem of low efficiency and local optimum caused by traditional optimal methods, the hybrid Genetic Algorithm are adopted to solve the optimization model. So that the optimization process is simplified and global optimum is acquired reliably.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 26-28)

Pages:

186-189

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.26-28.186

Citation:

Cite this paper

Online since:

June 2010

Authors:

Jiang Zhu, Ping Yuan Xi

Keywords:

Hybrid Genetic Algorithm, Internal Combustion Engine (ICE), Optimization Design, Piston

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Zhu Fangjun, Wu Jian, Working process numerical calculation and optimization of internal combustion engine. Beijing: National Defense Industry Press, (1997).

Google Scholar

[2] Wang Xiaoping, Theory, applying and software of Genetic Algorithm. Xi'an: Xi'an Jiaotong University Press, (2002).

Google Scholar

[3] Xi Pingyuan, Optiminization of the Crank-rocker Mechanism with Fuzzy Analysis, China manufacturing Information. Nanjing, 2004. 11 , pp.90-91.

Google Scholar

[4] T.T.H. Ng, G.S.B. Leng, Engineering Applications of Artificial Intelligence, Department of Mechanical Engineering, National University of Singapore. Singapore, 2005. 5, pp.439-445.

Google Scholar

[5] Panting J, Pullen K R, Martinez-Botas R F. Turbocharger motor-generator for improvement of transient performance in an internal combustion engine. Proc IMechE, Part D.

DOI: 10.1243/0954407011525700

Google Scholar