Earticle

초록

영어

Automobile exhaust emissions is one of the important pollution sources. How to reduce automobile emission is a hot topic in the research field. Research on the alternative fuel and alternative fuel engine has great potential application. CNG engine is more promising due to its less emission and relatively rich resource. Existing research on the combustion process of CNG engine realize that the performance is affected by the boundary conditions, and the ignition time is a key parameter in reducing the emission and improving the efficiency. In this paper, an adaptive control method, which is based on radial basis (RBF) network method, has been proposed for the optimal ignition advance angle. According to the training sample, the simulation results have great coincidence with the experiment results. According to the experiment, the necessity of the control method is proven, and the validity of the RBF neural network applied in the calculation of the ignition advance angle has been proven.

목차

Abstract
 Introduction
 2. The Control Method
  2.1 Test System
  2.2 The Adaptive Control Method
 3. Verification
  3.1 The CNG Engine
  3.2 Analysis of the Results
 4. Conclusion
 References

키워드

저자

• WANG Xiang-qian [ College of Teachers’ Education, Pingdingshan University, Pingdingshan, Henan 467000, China ]
• Quan Gan [ College of Information Engineering, PINGDINGSHAN University, Pingdingshan Henan, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605