실내환경에서의 자율주행차 무선 전력 전송을 위한딥러닝 기반 UWB 거리 측정
Deep Learning-based UWB Distance Measurement for Wireless Power Transfer of Autonomous Vehicles in Indoor Environment
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초록
최근 자율주행차 시장이 지속해 성장함에 따라 충전 인프라에 대한 필요성이 커지고 있다. 그러나 무선 충전 시스템의 경우 기존 유선 충전에비해 대출력이 요구되어 안정성 문제가 제기되고 있다. 자율주행차 무선 충전 인프라를 구축하기 위한 표준으로는 SAE J2954가 존재하며 해당표준에서는 차량과 전력 전송 시스템 간의 통신 방법에 대해 정의한다. SAE J2954에서는 자율주행차량의 무선 충전 통신 방법으로 Wi-Fi, Bluetooth및 UWB와 같은 물리적 미디어를 사용해 차량과 충전 패드 간의 통신을 활성화할 것을 권장한다. 특히 UWB는 실내 환경에서 견고한 통신 능력을보이고 간섭에 민감하지 않기 때문에 실내외 충전 환경에서 적합한 솔루션이다. 해당 표준에서는 무선전력전송 시스템을 구축하기 위한 프로세스로충전 시작부터 충전 완료까지를 여러 단계로 구분하였다. 본 연구에서는 UWB 기술을 사용하여 무선전력전송 시스템의 한 가지 프로세스인 Finealignment의 수단으로 사용한다. 실제 자율주행차 무선전력전송 시스템에 적용 가능성을 판단하기 위해 거리에 따라 실험을 수행하였으며 UWB로부터 거리 정보를 수집하였다. UWB로부터 얻어진 거리 데이터의 정확도를 향상시키기 위해 수집한 데이터를 세 단계의 전처리 과정을 거쳐 머신러닝과딥러닝 기법을 적용한 Single Model과 Multi Model을 제안한다.
Abstract
As the self-driving car market continues to grow, the need for charging infrastructure is growing. However, in the case of a wirelesscharging 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 communicationmethod between a vehicle and a power transmission system. SAE J2954 recommends using physical media such as Wi-Fi, Bluetooth, andUWB as a wireless charging communication method for autonomous vehicles to enable communication between the vehicle and thecharging pad. In particular, UWB is a suitable solution for indoor and outdoor charging environments because it exhibits robustcommunication capabilities in indoor environments and is not sensitive to interference. In this standard, the process for building a wirelesspower transmission system is divided into several stages from the start to the completion of charging. In this study, UWB technologyis used as a means of fine alignment, a process in the wireless power transmission system. To determine the applicability to an actualautonomous vehicle wireless power transmission system, experiments were conducted based on distance, and the distance informationwas collected from UWB. To improve the accuracy of the distance data obtained from UWB, we propose a Single Model and Multi Modelthat apply machine learning and deep learning techniques to the collected data through a three-step preprocessing process.
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