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新型横向轮胎力传感器在电动汽车车辆参数估计中的应用

Application of Novel Lateral Tire Force Sensors to Vehicle Parameter Estimation of Electric Vehicles.

作者信息

Nam Kanghyun

机构信息

School of Mechanical Engineering, Yeungnam University, 280 Daehak-ro, Gyeongsan 712-749, Korea.

出版信息

Sensors (Basel). 2015 Nov 11;15(11):28385-401. doi: 10.3390/s151128385.

DOI:10.3390/s151128385
PMID:26569246
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4701285/
Abstract

This article presents methods for estimating lateral vehicle velocity and tire cornering stiffness, which are key parameters in vehicle dynamics control, using lateral tire force measurements. Lateral tire forces acting on each tire are directly measured by load-sensing hub bearings that were invented and further developed by NSK Ltd. For estimating the lateral vehicle velocity, tire force models considering lateral load transfer effects are used, and a recursive least square algorithm is adapted to identify the lateral vehicle velocity as an unknown parameter. Using the estimated lateral vehicle velocity, tire cornering stiffness, which is an important tire parameter dominating the vehicle's cornering responses, is estimated. For the practical implementation, the cornering stiffness estimation algorithm based on a simple bicycle model is developed and discussed. Finally, proposed estimation algorithms were evaluated using experimental test data.

摘要

本文介绍了利用轮胎侧向力测量来估计车辆横向速度和轮胎侧偏刚度的方法，这两个参数是车辆动力学控制中的关键参数。作用在每个轮胎上的侧向力由NSK有限公司发明并进一步开发的负载感应轮毂轴承直接测量。为了估计车辆横向速度，使用考虑侧向载荷转移效应的轮胎力模型，并采用递推最小二乘算法来识别作为未知参数的车辆横向速度。利用估计出的车辆横向速度，估计轮胎侧偏刚度，它是主导车辆转弯响应的一个重要轮胎参数。为了实际应用，开发并讨论了基于简单自行车模型的侧偏刚度估计算法。最后，利用实验测试数据对所提出的估计算法进行了评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/3d8d2c1e3426/sensors-15-28385-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/3d8d2c1e3426/sensors-15-28385-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/a3caeb64e7dc/sensors-15-28385-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/878947727672/sensors-15-28385-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/c35777dc8b25/sensors-15-28385-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/d11cef77fbc8/sensors-15-28385-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/fe7b43f001c8/sensors-15-28385-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/36bf0d040126/sensors-15-28385-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/b8298ac9d30b/sensors-15-28385-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/84b98a66629e/sensors-15-28385-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/5a94e594e07c/sensors-15-28385-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/17f462b4ea6a/sensors-15-28385-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9e5/4701285/3d8d2c1e3426/sensors-15-28385-g014.jpg

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本文引用的文献

1
Vehicle lateral state estimation based on measured tyre forces.基于实测轮胎力的车辆横向状态估计。
Sensors (Basel). 2009;9(11):8761-75. doi: 10.3390/s91108761. Epub 2009 Oct 30.
Sensors (Basel). 2016 Aug 19;16(8):1328. doi: 10.3390/s16081328.