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A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence

文献类型：期刊论文

作者Xu, Zhenyi1,2; Wang, Ruibin1,3; Kang, Yu1,4,5,6; Zhang, Yujun7; Xia, Xiushan5; Wang, Renjun1,3
刊名JOURNAL OF ADVANCED TRANSPORTATION
出版日期2021-12-30
卷号2021
ISSN号0197-6729
DOI10.1155/2021/4892855
通讯作者Xu, Zhenyi(xuzhenyi@mail.ustc.edu.cn) ; Kang, Yu(kangduyu@ustc.edu.cn)
英文摘要By installing on-board diagnostics (OBD) on tested vehicles, the after-treatment exhaust emissions can be monitored in real time to construct driving cycle-based emission models, which can provide data support for the construction of dynamic emission inventories of mobile source emission. However, in actual vehicle emission detection systems, due to the equipment installation costs and differences in vehicle driving conditions, engine operating conditions, and driving behavior patterns, it is impossible to ensure that the emission monitoring data of different vehicles always follow the same distribution. The traditional machine learning emission model usually assumes that the training set and test set of emission test data are derived from the same data distribution, and a unified emission model is used for estimation of different types of vehicles, ignoring the difference in monitoring data distribution. In this study, we attempt to build a diesel vehicle NOx emission prediction model based on the deep transfer learning framework with a few emission monitoring data. The proposed model firstly uses Spearman correlation analysis and Lasso feature selection to accomplish the selection of factors with high correlation with NOx emission from multiple sources of external factors. Then, the stacked sparse AutoEncoder is used to map different vehicle working condition emission data into the same feature space, and then, the distribution alignment of different vehicle working condition emission data features is achieved by minimizing maximum mean discrepancy (MMD) in the feature space. Finally, we validated the proposed method with the diesel vehicle OBD data that were collected by the Hefei Environmental Protection Bureau. The comprehensive experiment results show that our method can achieve the feature distribution alignment of emission data under different vehicle working conditions and improve the prediction performance of the NOx inversion model given a little amount of NOx emission monitoring data.
资助项目National Natural Science Foundation of China[62103124] ; National Natural Science Foundation of China[62033012] ; National Natural Science Foundation of China[61725304] ; Major Special Science and Technology Project of Anhui, China[201903a07020012] ; Major Special Science and Technology Project of Anhui, China[202003a07020009] ; China Postdoctoral Science Foundation[2021M703119] ; National Key R&D Program of China[2018YFE0106800]
WOS研究方向Engineering ; Transportation
语种英语
出版者WILEY-HINDAWI
WOS记录号WOS:000788641100004
资助机构National Natural Science Foundation of China ; Major Special Science and Technology Project of Anhui, China ; China Postdoctoral Science Foundation ; National Key R&D Program of China
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/131517]  
专题中国科学院合肥物质科学研究院
通讯作者Xu, Zhenyi; Kang, Yu
作者单位1.Hefei Comprehens Natl Sci Ctr, Inst Artificial Intelligence, Hefei 230088, Peoples R China
2.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230026, Peoples R China
3.Anhui Univ, Sch Comp Sci & Technol, Hefei 230601, Peoples R China
4.Univ Sci & Technol China, Dept Automat, Hefei 230026, Peoples R China
5.Univ Sci & Technol China, Inst Adv Technol, Hefei 230088, Peoples R China
6.Chinese Acad Sci, Key Lab Technol GeoSpatial Informat Proc & Applic, Beijing 100192, Peoples R China
7.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Environm Opt & Technol, Hefei 230031, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Zhenyi,Wang, Ruibin,Kang, Yu,et al. A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence[J]. JOURNAL OF ADVANCED TRANSPORTATION,2021,2021.
APA Xu, Zhenyi,Wang, Ruibin,Kang, Yu,Zhang, Yujun,Xia, Xiushan,&Wang, Renjun.(2021).A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence.JOURNAL OF ADVANCED TRANSPORTATION,2021.
MLA Xu, Zhenyi,et al."A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence".JOURNAL OF ADVANCED TRANSPORTATION 2021(2021).

入库方式： OAI收割

来源：合肥物质科学研究院

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