基于远程监控三区移动平均窗口法的重型车排放特征

doi:10.3969/j.issn.1674-8484.2023.03.013

汽车安全与节能学报 ›› 2023, Vol. 14 ›› Issue (3): 375-384.DOI: 10.3969/j.issn.1674-8484.2023.03.013

基于远程监控三区移动平均窗口法的重型车排放特征

任烁今¹(), 张超¹, 李刚²^,^*(), 李腾腾¹, 于全顺¹, 关敏², 吉喆², 景晓军¹

1.中汽研汽车检验中心（天津）有限公司，天津300300，中国
2.中国环境科学研究院国家环境保护机动车污染控制与模拟重点实验室，北京100012，中国

收稿日期:2022-12-13 修回日期:2023-02-12 出版日期:2023-06-30 发布日期:2023-06-30
通讯作者: 李刚
作者简介:*李刚，高级工程师。E-mail：ligang@vecc.org.cn。
任烁今（1990—），男（汉），河北，高级工程师。E-mail： renshuojin@163.com。
基金资助:
中国环境科学研究院中央级公益性科研院所基本科研业务专项资助(2021-JY-23)

Heavy-duty vehicle emission characteristics based on the remote-monitoring three-bin moving-average window method

REN Shuojin¹(), ZHANG Chao¹, LI Gang²^,^*(), LI Tengteng¹, Yu Quanshun¹, GUAN Min², JI Zhe², JING Xiaojun¹

1. CATARC Automotive Test Center (Tianjin) Co., Ltd., Tianjin 300300, China
2. State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Beijing 100012, China

Received:2022-12-13 Revised:2023-02-12 Online:2023-06-30 Published:2023-06-30
Contact: LI Gang

摘要/Abstract

摘要：

为了研究实际道路上重型车的排放特征，提出了一种基于远程监控数据的三区移动平均窗口（3B-MAW）模型，并与功基窗口法分析结果进行了对比。模型中远程监控无效数据主要包含NO_x传感器未正常传输的数据和发动机停机后仍然上传的数据。每个数据点有可能落在1种、2种或3种区内，三区划分的比例与车辆的实际行驶工况有关。为了同时兼顾排放结果计算的准确性和所需数据量不过大，最小窗口数、窗口宽度、第1划分线和第2划分线这4个模型主要参数应分别设置在2 400、300 s，6%和20%附近。由于不受窗口功率阈值限制，相对于功基窗口法，3B-MAW模型能够实现对低负荷排放更为有效的核查，适合对实际道路随机工况进行分析。

关键词: 重型车, 实际道路排放, 移动平均, 远程监控, 功基窗口法

Abstract:

A three-bin moving average window (3B-MAW) model was proposed and compared with the work-based window method (WB-WM) to investigate the on-road emission characteristics of heavy-duty vehicles. The invalid data of remote monitoring were mainly composed of the NO_x sensor’s abnormal data and the uploaded data after the engine shutdown. In the 3B-MAW model, each data was attributed to one, two or three bins. The percentage of the three bins were linked to the vehicle’s real driving conditions. In order to gain the emission calculation accuracy and a smaller scale of required data, the value of the four main parameters, i.e., the minimum window number, the window width, the first cut-off and the second cut-off are set around 2 400 s, 300 s, 6% and 20%, respectively. Since the window power threshold is no longer required, the 3B-MAW method is able to capture the low load emission characteristics more effectively, compared to the WB-WM. Therefore, the 3B-MAW method is a more appreciate approach to analyse on-road random driving conditions.

Key words: heavy-duty vehicle, moving average, remote monitoring, work-based window method

中图分类号:

X831

任烁今, 张超, 李刚, 李腾腾, 于全顺, 关敏, 吉喆, 景晓军. 基于远程监控三区移动平均窗口法的重型车排放特征[J]. 汽车安全与节能学报, 2023, 14(3): 375-384.

REN Shuojin, ZHANG Chao, LI Gang, LI Tengteng, Yu Quanshun, GUAN Min, JI Zhe, JING Xiaojun. Heavy-duty vehicle emission characteristics based on the remote-monitoring three-bin moving-average window method[J]. Journal of Automotive Safety and Energy, 2023, 14(3): 375-384.

图/表 19

参考文献 16

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名称	分类	最大总质量 / t	体积排量 / L	额定功率 / kW	M_CO2 / [g·(kW·h)^-1]	数据量 / s
货车1	N2	4.5	2.29	96	670.2	258 196
货车2	N3	18.0	4.58	162	583.9	222 072
货车3	N3	31.0	9.50	289	609.1	739 538
牵引1	N3	18.0	10.52	327	602.7	963 274
牵引2	N3	25.0	12.90	426	552.0	784 589
客车1	M3	16.0	7.80	235	696.4	204 990

名称	分类	最大总质量 / t	体积排量 / L	额定功率 / kW	M_CO2 / [g·(kW·h)^-1]	数据量 / s
货车1	N2	4.5	2.29	96	670.2	258 196
货车2	N3	18.0	4.58	162	583.9	222 072
货车3	N3	31.0	9.50	289	609.1	739 538
牵引1	N3	18.0	10.52	327	602.7	963 274
牵引2	N3	25.0	12.90	426	552.0	784 589
客车1	M3	16.0	7.80	235	696.4	204 990

分区	限值
分区	CARB	WVU
怠速区	CF×IDLE限值	15~45 g/h
低负荷区	CF×LLC限值	0.4 g/(kWh)
中高负荷区	CF×FTP/RMC限值	0.1~0.4 g/(kWh)

分区	限值
分区	CARB	WVU
怠速区	CF×IDLE限值	15~45 g/h
低负荷区	CF×LLC限值	0.4 g/(kWh)
中高负荷区	CF×FTP/RMC限值	0.1~0.4 g/(kWh)

样车	最大总质量 t	排量 L	循环功 kWh	加载 %
1	4.5	2.49	10.0	94.3
2	4.5	2.29	6.7	82.8
3	10.5	5.19	10.5	40.0
4	31.0	7.80	22.3	0.0
5	49.0	13.00	36.0	90.0

基于远程监控三区移动平均窗口法的重型车排放特征

Heavy-duty vehicle emission characteristics based on the remote-monitoring three-bin moving-average window method

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样车	有效数据量/s	WB-WM			3B-MAW
		窗口通过率/%	平均排放 / [g·(kWh)^-1]		怠速区		低负荷区		中高负荷区
		窗口通过率/%	有效窗口	所有窗口	窗口数	排放/(g·h^-1)	窗口数	排放/[g·(kWh)^-1]	窗口数	排放/[g·(kWh)^-1]
1	8 537	100	0.006 7	0.007 1	0	—	5 527	0.12	2 710	0.004
2	6 429	100	0.229 6	0.189 1	396	0.47	2 646	0.77	3 087	0.130
3	9 975	80	0.591 1	0.619 6	305	9.42	6 789	0.64	2 581	0.480
4	8 588	100	0.030 1	0.453 7	2 821	29.02	2 665	0.09	2 802	0.007
5	13 510	0	2.776 2	2.714 1	2 534	58.15	4 776	3.38	5 900	1.880

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