Position detection for electric vehicle DWCS using VI-SLAM method
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...
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Elsevier
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/e9eb0e26d36c4d5eb0c0e6a3db01413f |
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| Résumé: | 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°, 1.682°, 2.501°, respectively. Compared with the smooth variable structure filter (SVSF) based SLAM method, 0.106 m, 0.098 m, 0.130 m and 3.069°, 3.261°, 2.961°, the accuracy of ours is increased by 18.87%, 6.12%, 21.54% and 21.05%, 45.42%, 15.54%, respectively. |
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