基于远程监控数据修正的重型车队碳排放水平研究  

Research on Carbon Emission Level of Heavy-duty Fleet based on Remote Monitoring Data Correction

作　　者：刘文彬 华维銮 Liu Wenbin;Hua Weiluan

机构地区：[1]中汽研汽车检验中心(天津)有限公司,天津300300

出　　处：《时代汽车》2025年第7期4-6,共3页Auto Time

摘　　要：重型车队碳排放水平精准评估对于交通领域“双碳”目标的实现具有重要意义。然而,由于远程监控数据存在数据质量问题,严重影响了基于远程监控数据的车辆碳排放核算精度。为此,本文开展了基于远程监控数据修正的重型车队碳排放水平研究。定义了远程监控数据异常问题,并构建了一种远程监控数据异常修正模型,对数据异常问题进行修正与优化。基于此,提出了一种重型车队排放水平评估方法,引入碳排放强度,考虑车队内结构因素,实现了重型车队碳排放水平综合评估。The accurate assessment of carbon emission level of heavy-duty fleet is of great significance for the realization of "dual carbon" target in transportation field.However,due to the data quality problems of remote monitoring data,the accuracy of vehicle carbon emission accounting based on remote monitoring data is seriously aff ected.Therefore,research on the carbon emission level of heavy-duty fleet based on modified remote monitoring data were carried out in this paper.This paper defines the remote monitoring data anomaly problem,and constructs a remote monitoring data anomaly correction model to correct and optimize the data anomaly problem.Based on this,an emission level assessment method for heavy-duty vehicle fleet was proposed.By introducing carbon emission intensity and considering the structural factors within the vehicle fleet,comprehensive assessment of carbon emission level of heavy-duty vehicle fleet was realized.

关 键 词：重型车 碳排放 数据异常修正 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]