Position detection for electric vehicle DWCS using VI-SLAM method

被引:3
作者
Cheng, Jun [1 ]
Zhang, Liyan [1 ]
Chen, Qihong [1 ]
Long, Rong [2 ]
机构
[1] Wuhan Univ Technol, Sch Automat, 122 Luoshi Rd, Wuhan 430070, Hubei, Peoples R China
[2] Huazhong Agr Univ, Sch Sci, 1 Shizishan St, Wuhan 430070, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicle; DWCS; VI-SLAM; Graph optimization; Position detection; WIRELESS; SYSTEM;
D O I
10.1016/j.egyr.2021.09.086
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The dynamic wireless charging system (DWCS) is developed to solve the problems of large battery volume and mileage anxiety of electric vehicles. However, the accurate position detection for electric vehicle DWCS is facing challenge. The traditional communication, detection and estimation methods are difficult to accurately obtain the position. To tackle this problem, the visual inertial simultaneous localization and mapping (VI-SLAM) method is applied to the electric vehicles DWCS. Firstly, the graph optimization based tight coupling method is used to integrate the monocular visual and inertial measurement unit (IMU) measurements. Secondly, the NVIDIA TX2 and MYNT VI-sensor suite are assembled, which the MTi300-IMU is treated as the ground truth system. Finally, the mobile vehicle is controlled to race on the simulated DWCS pathway. The experimental result shows that the method achieves great performance with the accuracy of centimeter level. In particular, the root mean square error (RMSE) of pose (i.e. position and orientation) in X, Y, Z directions are 0.086 m, 0.092 m, 0.102 m and 2.423 degrees, 1.682 degrees, 2.501 degrees, respectively. Compared with the smooth variable structure filter (SVSF) based SLAM method, 0.106 m, 0.098 m, 0.130 m and 3.069 degrees, 3.261 degrees, 2.961 degrees, the accuracy of ours is increased by 18.87%, 6.12%, 21.54% and 21.05%, 45.42%, 15.54%, respectively. (C) 2021 The Author(s). Published by Elsevier Ltd.
引用
收藏
页码:1 / 9
页数:9
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