Research on the Assessment Method of Heavy-Duty Vehicle Emission Levels Using Remote Monitoring Data

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.