Research on Feature Detection of Light Vehicle Emission Pollution Under the Control of Artificial Intelligence
Keywords:Artificial Intelligence, Light Vehicle, Pollution Emission, Pollution Detection.
Most modern cars use electronically controlled fuel injection engines. Because the fuel injection rate is strictly in accordance with the intake port, the combustion is more thorough and cleaner, so it usually has better emission performance. However, when there is a problem with it, it will have a great impact on its emission characteristics. By conducting exhaust emission experiments under WLTC, NEDC, and FTP-75 operating conditions, the emission characteristics of exhaust gases under various operating conditions were compared. Through comparative analysis, it is concluded that under WLTC conditions, the strictness of vehicle exhaust emissions has increased compared with the past, which provides a basis for automobile manufacturers to manage vehicle exhaust in the new technical environment.
Hu Wei, Zhong Nengchao, Jiang Yichun. Research on WLTC cycle emission and fuel consumption of light-duty vehicles under different drum loading resistance. Times Auto, Vol. 2(2023) No.6, p. 163-165.
Wang Rong. Research on Motor Vehicle Environmental Pollution Detection Based on Big Data. Leather Production and Environmental Technology, Vol. 3(2022) No.5, p. 52-53.
Zhao Cunbin, Shao Jianwen, Ye Zhenzhou, et al. Research and Application of Key Technologies for Motor Vehicle Emission Pollutant Detection. China Science and Technology Achievements, Vol. 24(2023) No.6, p. 12-16.
Li Guodong, Guo Xiaoxin, Zhao Shuo, et al. Study on the Quantitative Emission Characteristics of Particulate Matter from Light Vehicles. Small Internal Combustion Engine and Vehicle Technology, Vol. 50(2021) No.5, p. 45-48.
Song Haotian. Design of Image Recognition Feature Extraction Device Based on Artificial Intelligence. Automation Today, Vol. 1(2023) No.1, p. 95-98.
Wang Jinglin, Wang Dongsheng, Yuan Hongying, et al. Research on the application of fingerprint technology and artificial intelligence in the traceability and analysis of pollutants. Environmental Protection Science, Vol. 48(2022) No.6, p. 130-137.
Wei Xiaoshu, Gao Hongjie, Chen Yuanhang, et al. Research progress of artificial intelligence technology in the field of water pollution control. Journal of Environmental Engineering Technology, Vol. 12(2022) No.6, p. 78-82.
Deng Jiaowuxin. Effect of ambient temperature on actual road emission test results of light vehicles. Small Internal Combustion Engine and Vehicle Technology, Vol. 51(2022) No.4, p. 56-59.
How to Cite
This work is licensed under a Creative Commons Attribution 4.0 International License.