| Issue |
E3S Web Conf.
Volume 630, 2025
2025 International Conference on Eco-environmental Protection, Environmental Monitoring and Remediation (EPEMR 2025)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 7 | |
| Section | Smart Technologies for Environmental Monitoring and Pollution Mitigation | |
| DOI | https://doi.org/10.1051/e3sconf/202563001002 | |
| Published online | 22 May 2025 | |
Research on the Assessment Method of Heavy-Duty Vehicle Emission Levels Using Remote Monitoring Data
1 China Automotive Technology Research Center Co., Ltd., Tianjin, China
2 Jilin University, Jilin, China
3 CATARC Automotive Test Center (Tianjin) Co., Ltd., Tianjin, China
The emission problem of heavy-duty vehicles constitutes an urgent environmental challenge within the transportation sector. Scientifically assessing the emission levels of heavy-duty vehicles forms the foundation for their effective control. This paper utilizes remote monitoring data from heavy-duty vehicles to compare five widely employed methods for assessing heavy-duty vehicle emissions: the power-based window method, moving average window method, three-bin moving average window method, VSP-Bin window di- vision method, and data reconstruction PEMS window division method. The fundamental principles and op- erational adaptability characteristics of the five emission assessment methods are introduced. The distinctive evaluation characteristics of each method for assessing heavy-duty vehicle emissions are delineated. The re- search findings reveal that each evaluation method demonstrates unique adaptability under high-load, low- load, and complex mixed conditions, thereby laying a crucial foundation for enhancing the accuracy and effectiveness of emission assessments.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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