Longitudinal Vehicle Speed Estimation for Four-Wheel-Independently-Actuated Electric Vehicles Based on Multi-Sensor Fusion

Xiaolin Ding, Zhenpo Wang, Lei Zhang*, Cong Wang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

154 引用 (Scopus)

摘要

In this paper, an enabling multi-sensor fusion-based longitudinal vehicle speed estimator is proposed for four-wheel-independently-actuated electric vehicles using a Global Positioning System and Beidou Navigation Positioning (GPS-BD) module, and a low-cost Inertial Measurement Unit (IMU). For accurate vehicle speed estimation, an approach combing the wheel speed and the GPS-BD information is firstly put forward to compensate for the impact of road gradient on the output horizontal velocity of the GPS-BD module, and the longitudinal acceleration of the IMU. Then, a multi-sensor fusion-based longitudinal vehicle speed estimator is synthesized by employing three virtual sensors which generate three longitudinal vehicle speed tracks based on multiple sensor signals. Finally, the accuracy and reliability of the proposed longitudinal vehicle speed estimator are examined under a diverse range of driving conditions through hardware-in-the-loop tests. The results show that the proposed method has high estimation accuracy, robustness, and real-time performance.

源语言英语
文章编号9204583
页(从-至)12797-12806
页数10
期刊IEEE Transactions on Vehicular Technology
69
11
DOI
出版状态已出版 - 11月 2020

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