Deep Learning-based UWB Distance Measurement for Wireless Power Transfer of Autonomous Vehicles in Indoor Environment


KIPS Transactions on Computer and Communication Systems, Vol. 13, No. 1, pp. 21-30, Jan. 2024
https://doi.org/10.3745/KTCCS.2024.13.1.21,   PDF Download:
Keywords: UWB, Indoor Localization, wireless power transfer, SAE J2954, Autonomous vehicle
Abstract

As the self-driving car market continues to grow, the need for charging infrastructure is growing. However, in the case of a wireless charging system, stability issues are being raised because it requires a large amount of power compared with conventional wired charging. SAE J2954 is a standard for building autonomous vehicle wireless charging infrastructure, and the standard defines a communication method between a vehicle and a power transmission system. SAE J2954 recommends using physical media such as Wi-Fi, Bluetooth, and UWB as a wireless charging communication method for autonomous vehicles to enable communication between the vehicle and the charging pad. In particular, UWB is a suitable solution for indoor and outdoor charging environments because it exhibits robust communication capabilities in indoor environments and is not sensitive to interference. In this standard, the process for building a wireless power transmission system is divided into several stages from the start to the completion of charging. In this study, UWB technology is used as a means of fine alignment, a process in the wireless power transmission system. To determine the applicability to an actual autonomous vehicle wireless power transmission system, experiments were conducted based on distance, and the distance information was collected from UWB. To improve the accuracy of the distance data obtained from UWB, we propose a Single Model and Multi Model that apply machine learning and deep learning techniques to the collected data through a three-step preprocessing process.


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Cite this article
[IEEE Style]
H. Kim, Y. Park, S. Han, "Deep Learning-based UWB Distance Measurement for Wireless Power Transfer of Autonomous Vehicles in Indoor Environment," KIPS Transactions on Computer and Communication Systems, vol. 13, no. 1, pp. 21-30, 2024. DOI: https://doi.org/10.3745/KTCCS.2024.13.1.21.

[ACM Style]
Hye-Jung Kim, Yong-ju Park, and Seung-Jae Han. 2024. Deep Learning-based UWB Distance Measurement for Wireless Power Transfer of Autonomous Vehicles in Indoor Environment. KIPS Transactions on Computer and Communication Systems, 13, 1, (2024), 21-30. DOI: https://doi.org/10.3745/KTCCS.2024.13.1.21.