汽车工程学报2024，Vol.14Issue(3)：511-518,8.DOI:10.3969/j.issn.2095‒1469.2024.03.18
基于神经网络的重型车辆远程监控NOx传感器露点保护过程数据修复方法
Neural Network-Based Data Repair Method During NOx Sensor Dew Point Protection in Remote Monitoring of Heavy-Duty Vehicles
摘要
Abstract
To solve the problem of invalid data during the dew point protection phase of NOx sensors in the remote monitoring of heavy-duty vehicles,the paper used the PEMS tests on a China VI heavy-duty vehicle to investigate the high NOx emissions during this protection period.Furthermore,the feasibility of using a neural network algorithm to repair the data and improve the utilization rate of remote monitoring data was verified.The results show that the dew point protection leads to more than 30%NOx emissions not being recorded.During this protection phase,over 90%of the data revealed that the vehicle speed was below 54 km/h,the engine coolant temperature was below 82 ℃,the SCR inlet temperature was below 245 ℃,and the SCR outlet temperature was below 225 ℃.The neural network algorithm effectively repaired the invalid NOx measurements during dew point protection,with errors of less than 4%.关键词
神经网络/远程监控数据/NOx排放/重型车/露点保护Key words
neural network/remote monitoring data/NOx emissions/heavy-duty vehicles/dew point protection分类
能源与动力引用本文复制引用
刘春涛,张帆,吴春玲,裴毅强,陈淑鑫,何颖..基于神经网络的重型车辆远程监控NOx传感器露点保护过程数据修复方法[J].汽车工程学报,2024,14(3):511-518,8.基金项目
国家重点研发计划项目(2022YFC3701805,2022YFC3703600) （2022YFC3701805,2022YFC3703600）
