基于多传感器信息融合的轮毂机动车辆速度估计研究

Q4 Engineering

International Journal of Vehicle Systems Modelling and Testing Pub Date : 2021-06-20 DOI:10.1504/ijvsmt.2021.10038929

Mingyue Zhang, Xiao-bin Fan, Jing Gan

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引用次数: 2

摘要

精确获取车辆的纵向和横向速度在现代汽车控制系统中起着重要作用。本文的车速测试系统由多个传感器、数据采集板（NI cDAQ9137）和LabVIEW软件组成。利用该测速系统实现了轮毂机动车前轮角、轮速、纵向加速度、横向加速度和横摆角速度的实时采集。在实际道路试验结果的基础上，利用卡尔曼滤波技术获得了车速估计值，并与参考车辆动力学模型进行了比较。比较结果表明，车辆速度估计具有较高的精度，能够满足状态参数估计的要求。该算法具有结构简单、计算量小、易于实现的优点，可以为汽车控制系统提供更多的信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Research on speed estimation of hub-motor vehicle based on multi-sensor information fusion

Accurate acquisition of longitudinal and lateral velocity of the vehicle plays an important role in the modern automobile control system. In this paper, the vehicle speed test system is composed of multiple sensors, data acquisition board (NI cDAQ9137) and LabVIEW software. The real-time acquisition of front-wheel angle, wheel speed, longitudinal acceleration, lateral acceleration, and yaw velocity of the hub-motor vehicle is completed by using the speed measuring system. Based on the real road test results, the vehicle speed estimation is obtained by Kalman filter technology and compared with the reference vehicle dynamics model. The comparison results show that the vehicle speed estimation has high accuracy and can meet the requirements of state parameter estimation. The algorithm has the advantages of simple structure, small computation and easy implementation and can provide more information for the automobile control system.

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来源期刊

International Journal of Vehicle Systems Modelling and Testing Engineering-Automotive Engineering

CiteScore

0.50

自引率

0.00%

发文量

期刊介绍： IJVSMT provides a resource of information for the scientific and engineering community working with ground vehicles. Emphases are placed on novel computational and testing techniques that are used by automotive engineers and scientists.