This content is not included in your SAE MOBILUS subscription, or you are not logged in.
The Optimization of Intake Port using Genetic Algorithm and Artificial Neural Network for Gasoline Engines
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2015 by SAE International in United States
Annotation ability available
The flow performance of intake port significantly affects engine output power, fuel economy, and exhaust emissions in gasoline engines. Thus, optimal intake port geometry is desired in gasoline engines. To optimize the flow performance of intake port, a new optimization method combining genetic algorithm (GA) and artificial neural network (ANN) was proposed.
First, an automatic system for generating the geometry of the tangential intake port was constructed to create various port geometries through inputting the 18 pre-defined structural parameters.
Then, the effects of four critical structural parameters were investigated through numerical simulation. On the basis of the computational results, an ANN was used to model the flow performance of the intake port, and a genetic algorithm was simultaneously employed to optimize the flow performance by optimizing the four important structural parameters.
Finally, the optimization results were verified through numerical simulation. The results show that, compared to the original design, the tumble ratio significantly increases (about 6.12%), while flow coefficient remains nearly unchanged in the new design of the intake port.
CitationSun, Y., Wang, T., Lu, Z., Cui, L. et al., "The Optimization of Intake Port using Genetic Algorithm and Artificial Neural Network for Gasoline Engines," SAE Technical Paper 2015-01-1353, 2015, https://doi.org/10.4271/2015-01-1353.
- Kono , S. , Nagao , A. , and Motooka , H. Prediction of in-cylinder flow and spray formation effects on combustion indirect injection diesel engines Mazda Motor Corp. Hiroshima 1985
- Gale , N. Diesel Engine Cylinder Head Design: The Compromises and the Techniques SAE Technical Paper 900133 1990 10.4271/900133
- Widener , S. Parametric Design of Helical Intake Ports SAE Technical Paper 950818 1995 10.4271/950818
- Affes , H. , Trigui , N. , Smith , D. , and Griaznov , V. Shape Optimization of IC Engine Ports and Chambers SAE Technical Paper 980127 1998 10.4271/980127
- Blaxill , H. , Downing , J. , Seabrook , J. , and Fry , M. A Parametric Approach to Spark-Ignition Engine Inlet-Port Design SAE Technical Paper 1999-01-0555 1999 10.4271/1999-01-0555
- Bates , M. and Heikal , M. A Knowledge-Based Model for Multi-Valve Diesel Engine Inlet Port Design SAE Technical Paper 2002-01-1747 2002 10.4271/2002-01-1747
- Lu , Z. , Wang , T. , Li X. , Li , L. et al. Parametric design of the tangential intake port in diesel engines Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 227 3 409 421 2012 10.1177/0954407012461118
- Lu , Z. Parametric study of the tangential port with complex surface in internal combustion engine based on multiple constraints Ph.D. thesis Mechanical Engineering Department, Tianjin University Tianjin 2014
- De Jong , KA. Analysis of the behavior of a class of genetic adaptive systems Ph.D. Thesis the University of Michigan Michigan 1975
- Whitley , D. , Rana , S. , Dzubera , J. , Mathias , KE. Evaluating evolutionary algorithms Artificial intelligence 85 1 245 276 1996 10.1016/0004-3702(95)00124-7
- Renner , G. and Ekárt A. Genetic algorithms in computer aided design Computer-Aided Design 35 8 709 726 2003 10.1016/S0010-4485(03)00003-4
- Koza , J.R. Genetic programming: A paradigm for genetically breeding populations of computer programs to solve problems 1990 Stanford University, Department of Computer Science
- Oduguwa , V. , Tiwari , A. , and Roy , R. Evolutionarycomputing in manufacturing industry: an overview ofrecent applications Applied Soft Computing 5 3 281 299 2005 10.1016/j.asoc.2004.08.003
- Shi , Y. and Reitz , R. Optimization study of the effects of bowl geometry, spray targeting, and swirl ratio for a heavy-duty diesel engine operated at low and high load International Journal of Engine Research 9 4 325 346 2008 10.1243/14680874JER00808
- Ge , H. , Shi , Y. , Reitz , R. , Wickman , D. et al. Optimization of a HSDI Diesel Engine for Passenger Cars Using a Multi-Objective Genetic Algorithm and Multi-Dimensional Modeling SAE Int. J. Engines 2 1 691 713 2009 10.4271/2009-01-0715
- Wickman , D. , Senecal , P. , and Reitz , R. Diesel Engine Combustion Chamber Geometry Optimization Using Genetic Algorithms and Multi-Dimensional Spray and Combustion Modeling SAE Technical Paper 2001-01-0547 2001 10.4271/2001-01-0547
- Ge , H. , Shi , Y. , Reitz , R. , Wickman , D. et al. Heavy-Duty Diesel Combustion Optimization Using Multi-Objective Genetic Algorithm and Multi-Dimensional Modeling SAE Technical Paper 2009-01-0716 2009 10.4271/2009-01-0716
- Fisher , K. The application of genetic algorithms to optimising the design of an engine block for low noise 1st International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications(GALESIA) 18 22 1995 10.1049/cp:19951018
- Ahmadi , M. Intake, Exhaust and Valve Timing Design Using Single and Multi- Objective Genetic Algorithm SAE Technical Paper 2007-24-0090 2007 10.4271/2007-24-0090
- Xiaolong , Y. , Ming H. , and Biao L. Optimization of intake and exhaust system of a gasoline engine based ongenetic algorithm Computer-Aided Industrial Design &Conceptual Design 2009 IEEE 10th International Conference on 10.1109/CAIDCD.2009.5374945
- Kim , M. , Liechty , M. , and Reitz , R. Application of Micro-Genetic Algorithms for the Optimization of Injection Strategies in a Heavy-Duty Diesel Engine SAE Technical Paper 2005-01-0219 2005 10.4271/2005-01-0219
- Kim , D. and Park , S. Optimization of injection strategy toreduce fuel consumption for stoichiometric dieselcombustion Fuel 93 229 237 2012 10.1016/j.fuel.2011.08.067
- Genzale , C. , Reitz , R. , and Wickman , D. A Computational Investigation into the Effects of Spray Targeting, Bowl Geometry and Swirl Ratio for Low-Temperature Combustion in a Heavy-Duty Diesel Engine SAE Technical Paper 2007-01-0119 2007 10.4271/2007-01-0119
- Senecal , P. and Reitz , R. Simultaneous Reduction of Engine Emissions and Fuel Consumption Using Genetic Algorithms and Multi-Dimensional Spray and Combustion Modeling SAE Technical Paper 2000-01-1890 2000 10.4271/2000-01-1890
- Su , W. and Huang H. Development and calibration of areduced chemical kinetic model of n-heptane for HCCI engine combustion Fuel 84 9 1029 1040 2005 10.1016/j.fuel.2005.01.015
- Hiroyasu , H. , Miao , H. , Hiroyasu , T. , Miki , M. et al. Genetic Algorithms Optimization of Diesel Engine Emissions and Fuel Efficiency with Air Swirl, EGR, Injection Timing and Multiple Injections SAE Technical Paper 2003-01-1853 2003 10.4271/2003-01-1853
- Yun , H. and Reitz , R. An Experimental Study on Emissions Optimization Using Micro-Genetic Algorithms in a HSDI Diesel Engine SAE Technical Paper 2003-01-0347 2003 10.4271/2003-01-0347
- Canakci , M. and Reitz , R. Experimental optimization of a DI-HCCI-gasoline engine using split injections with fully-automatic micro-genetic algorithms International Journal of Engine Research 4 1 47 60 2003
- Thiel , M. , Klingbeil , A. , and Reitz , R. Experimental Optimization of a Heavy-Duty Diesel Engine Using Automated Genetic Algorithms SAE Technical Paper 2002-01-0960 2002 10.4271/2002-01-0960
- Canakci , M. and Reitz , R. Experimental optimization of a DI-HCCI-gasoline engine's performance and emissions using split injections with fully-automatic micro-genetic algorithms ASME Journal of Gas Turbines and Power 126 1 167 177 2004
- Hamosfakidis , V. and Reitz , R. Optimization of a hydrocarbon fuel ignition model for two single component surrogates of diesel fuel Combustion and Flame 132 3 433 450 2003 10.1016/S0010-2180(02)00489-3
- Elliott , L. , Ingham , D. , Kyne , A. , Mera , N. et al. Genetic algorithms for optimisation of chemical kinetics reaction mechanisms Progress in Energy and Combustion Science 30 3 297 328 2004 10.1016/j.pecs.2004.02.002
- Polifke , W. , Geng , W. , and Döbbeling , K. Optimization of rate coefficients for simplified reaction mechanisms with genetic algorithms Combustion and Flame 113 1 19 134 1998 10.1016/S0010-2180(97)00212-5
- Elliott , E. , Ingham , D. , Kyne , A. , Mera , N. et al. A novel approach to mechanism reduction optimization for anaviation fuel/air reaction mechanism using a geneticalgorithm Journal of engineering for gas turbines and power 128 2 255 263 2006 10.1115/1.2131887
- Atashkari , K. , Nariman-Zadeh , N. , Gölcü , M. , Khalkhali , A. et al. Modelling and multi-objective optimization of a variable valve-timing spark-ignition engine using polynomial neural networks and evolutionary algorithms Energy Conversion and Management 48 3 1029 1041 2007 10.1016/j.enconman.2006.07.007
- Alonso , J. , Alvarruiz , F. , Desantes , J. , Hernandez , L. et al. Combining neural networks and genetic algorithms to predict and reduce diesel engine emissions Evolutionary Computation, IEEE Transactions on 11 1 46 55 2007 10.1109/TEVC.2006.876364
- Kesgin , U. Genetic algorithm and artificial neural network for engine optimisation of efficiency and NOx emission Fuel 83 7 885 895 2004 10.1016/j.fuel.2003.10.025
- Johnson J. and Rahmat-Samii , V. Genetic Algorithms in Engineering Electromagnetics IEEE Antennas and Propagation Magazine 39 4 7 21 1997 10.1109/74.632992