دورية أكاديمية

Analysis of the influence of RDE test data processing methods on the emission results of China 6 light duty vehicles

التفاصيل البيبلوغرافية
العنوان: Analysis of the influence of RDE test data processing methods on the emission results of China 6 light duty vehicles
المؤلفون: Wang Zhihong, Wu Penghui, Yu Nenghui, Zhang Yuanjun, Wang Zhijun
المصدر: E3S Web of Conferences, Vol 268, p 01022 (2021)
بيانات النشر: EDP Sciences, 2021.
سنة النشر: 2021
المجموعة: LCC:Environmental sciences
مصطلحات موضوعية: china 6 light duty vehicle, co2 moving averaging window method, power binning method, rde, Environmental sciences, GE1-350
الوصف: The CO2 moving average window(MAW) method is used to process RDE (real drive emissions) emissions data in China 6 light duty vehicle emissions regulations, while the Euro 6 light duty vehicle emission regulations allow to use both of MAW and power binning(PB) method to deal with RDE emission data. In order to study the difference between the two data processing methods and analyze the differences in the emission results, 10 different types of light duty vehicles are conducted RDE test with PEMS (portable emissions measurement system), and the test data are processed by the two methods separately. The results show that there is a little difference between MAW and PB, while both of them can satisfy the vehicle emission assessment. The PB method calculates the emission factors higher than the MAW method. After removing the cold start and idle condition data, the results of PB is similar to MAW. Besides, reducing the average speed limit of urban working conditions in PB has a greater impact on the urban driving condition emission factor, but less on the whole cycle emission factor.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
French
تدمد: 2267-1242
Relation: https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/44/e3sconf_vesep2020_01022.pdf; https://doaj.org/toc/2267-1242
DOI: 10.1051/e3sconf/202126801022
URL الوصول: https://doaj.org/article/adb98abe7f5242b0b631187716eb760d
رقم الأكسشن: edsdoj.b98abe7f5242b0b631187716eb760d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22671242
DOI:10.1051/e3sconf/202126801022