Detecting automotive exhaust gas based on fuzzy inference system

• Main Authors: LI. Shujin, BAI, Ming, WANG, Quan, CHEN, Bo, ZHAO, Xiaobing, YANG, Ting, WANG, Zhaoxia
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2009
• Subjects: Automotive exhaust gas; Fuzzy inference; Infrared analyzer; Temperature compensation; Numerical Analysis and Scientific Computing; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/5552; https://ink.library.smu.edu.sg/context/sis_research/article/6555/viewcontent/Detecting_Automotive_Exhaust_Gas_av.pdf
• Institution: Singapore Management University

This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.