基于多信息源融合的国六重型柴油车OBD-Ⅲ系统设计

俞妍,庞海龙,卜建国,雷威,张衡

车用发动机 ›› 2022, Vol. 0 ›› Issue (6) : 65-70.

车用发动机 ›› 2022, Vol. 0 ›› Issue (6) : 65-70. DOI: 10.3969/j.issn.1001-2222.2022.06.011
栏目

基于多信息源融合的国六重型柴油车OBD-Ⅲ系统设计

  • 俞妍1,庞海龙1,卜建国1,雷威1,张衡2
作者信息 +

Design of OBD-Ⅲ System for China Ⅵ Heavy-Duty Diesel Vehicle-Based on Multiple Information Fusion

  • YU Yan1,PANG Hailong1,BU Jianguo1,LEI Wei1,ZHANG Heng2
Author information +
文章历史 +

摘要

依据《重型柴油车污染物排放限值及测量方法(中国第六阶段)》规定,国六车辆应装备远程数据采集系统,即OBD-Ⅲ系统。基于目前OBD-Ⅲ系统数据有限,缺少对车辆的全面了解的情况,设计并研制了基于多信息源融合的国六重型柴油车OBD-Ⅲ系统,采取多源信息融合的方法采集传感器节点、发动机动力CAN、车辆OBD诊断接口的数据,信息更加全面。通过滑动平均法对数据样本进行预处理,处理后的数据与便携式排放测试系统(Portable Emission Measurement System,PEMS) 实测数据结果基本一致,对管理部门监测车辆排放更具有现实意义。

Abstract

According to the legislation "Limits and measurement for emissions from diesel fuelled heavy-duty vehicles (China Ⅵ)", the China Ⅵ vehicle should be equipped with remote data acquisition system, that is OBD-Ⅲ system. The current data from OBD-Ⅲ system were insufficient and could not grasp the vehicle comprehensively. The OBD-Ⅲ system of China Ⅵ heavy-duty diesel vehicle was designed and developed based on multiple information fusion. The data of sensor node, engine CAN bus and vehicle OBD diagnostic interface were all collected with multiple information fusion technology, and hence the information was more comprehensive. The data samples were preprocessed by the moving average method, and the processed results were basically consistent with the measured results of portable emission measurement system (PEMS), which had a realistic meaning to vehicle emissions monitoring for the management department.

关键词

重型柴油车 / 远程数据采集系统(OBD-Ⅲ) / 多信息源融合 / 滑动平均法

Key words

heavyduty diesel vehicle / remote data acquisition system(OBD-Ⅲ) / multiple information fusion / moving average method

引用本文

导出引用
俞妍,庞海龙,卜建国,雷威,张衡. 基于多信息源融合的国六重型柴油车OBD-Ⅲ系统设计[J]. 车用发动机. 2022, 0(6): 65-70 https://doi.org/10.3969/j.issn.1001-2222.2022.06.011
YU Yan,PANG Hailong,BU Jianguo,LEI Wei,ZHANG Heng. Design of OBD-Ⅲ System for China Ⅵ Heavy-Duty Diesel Vehicle-Based on Multiple Information Fusion[J]. Vehicle Engine. 2022, 0(6): 65-70 https://doi.org/10.3969/j.issn.1001-2222.2022.06.011

Accesses

Citation

Detail

段落导航
相关文章

/