Research on Mass Estimation Algorithm of Intelligent and Connected Commercial Vehicle Based on Cloud Road Map

被引：0
作者：
Zhang A. [1 ]
Li S. [1 ]
Gao B. [2 ]
Wan K. [1 ]
Zhou G. [3 ]
Cao T. [3 ]
机构：
[1] College of Engineering, China Agricultural University, Beijing
[2] School of Vehicle and Mobility, Tsinghua University, Beijing
[3] Shenzhen Deeproute. ai Co. ，Ltd., Shenzhen
来源：
Qiche Gongcheng/Automotive Engineering | 2024年 / 46卷 / 06期
关键词：
cloud control system; extended Kalman filtering; intelligent and connected vehicle; mass estimation;
D O I：
10.19562/j.chinasae.qcgc.2024.06.007
中图分类号：
学科分类号：
摘要：
Vehicle mass is a key state variable of vehicle dynamics parameters. In the driver assistance system，accurate estimation of the vehicle mass is important for the planning and control algorithms. Traditional mass estimation algorithms face challenges in estimating road slope and vehicle mass at the same time. In particular，the error of slope estimation may seriously affect the accuracy of mass estimation. Currently，the cloud control platform provides high-precision road map information，which provides a new idea for further optimizing the mass estimation algorithm. Based on the vehicle-cloud collaborative framework of the cloud control platform，the system architecture of commercial vehicle mass estimation under the cloud control system is designed in this paper. Then，based on the extended Kalman filter theory，combining with the road map information in the cloud，the commercial vehicle mass estimation algorithm is developed. The vehicle mass is estimated by taking the road slope as a known parameter rather than a variable state parameter，and the algorithm is compared and verified by the driving data collected by the real vehicle test. The experimental results show that the mass estimation algorithm based on cloud slope information can achieve fast convergence under no-load and full-load conditions，and the absolute percentage error of the estimated mass is within 3%. Compared with the traditional algorithm of simultaneous estimation of mass and slope，it can converge to the real mass of the vehicle faster and more accurately. © 2024 SAE-China. All rights reserved.
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页码：1006 / 1014
页数：8
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