This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Application of the Neural Network Mapping Air-Fuel Ratio with Combustion Products Components
Technical Paper
2008-01-1720
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
In this paper, the computed results to the Air-Fuel Ratio (A/F) using three chemical equations are compared with the test results. With these four methods and the engine combustion product components, the A/F is deducted, and the results are different. Using neural networks (NN) mapping ability, the relation is found between A/F and combustion products components. Sample is fabricated and learned using those known information as input and output of NN. A/F can be mapping with combustion products components for engine by generalization of interpolation and extrapolation; prime information feature is abstracted based compared and verified with multi means. A/F can be well mapping in all work conditions with combustion products components. Each means restrict is solved and deduced precision is heightened. Through analyzing exhaust composition of engine with certain working condition, it shows that the maximal mapping error is 0.58%, which can satisfy measuring requirement of accurate control of present automobile to A/F. In addition, mapping of neural network to A/F has the characteristic of intelligence and flexibility. After learning and training of sample, using the extrapolation capability of network, the more accurate A/F can be mapping by mean of the engine emission information.
Recommended Content
Authors
Topic
Citation
Gao, Y., Wang, A., and Qiao, A., "Application of the Neural Network Mapping Air-Fuel Ratio with Combustion Products Components," SAE Technical Paper 2008-01-1720, 2008, https://doi.org/10.4271/2008-01-1720.Also In
References
- Xing-Hu Li Zhang Bo-Yan Ji Chang-Wei Lei Yan Han Ai-Min “Study on the relation between fuel-air ratio and combustion products” SAE paper 2002-01-1687 2002
- Wendeker Mirotaw Czarnigowski Jacek “Hybrid Air/Fuel ratio control using the adaptive estimation and neural network” SAE paper 2000-01-1248 2000
- Haskew H. Liberty T. “In-use emissions with today's closed-loop systems” SAE paper 910339 1991
- Hendricks E. “Transient A/F ratio errors in conventional SI engine controllers” SAE paper 930856 1993
- Lenz U. Schroeder D. “Transient air-to-fuel ratio control using artificial intelligence” SAE paper 970618 1997
- Sekozawa T. Takahashi S. Shioya M. “Development of a highly accurate air-fuel ratio control method based on internal state estimation” SAE paper 920290 1992
- Yaozhang B. Yiqun H. “Decrease emissions by adaptative air-fuel ratio control” SAE paper 910391 1991
- Spindt RS “Air-fuel ratios from exhaust gas analysis” SAE paper 650507 1965
- Stivender Donald L. “Development of a fuel-based mass emission measurement procedure” SAE paper 710604 1971