论文标题
基于LSTM的自适应车辆位置控制动态无线充电
LSTM-Based Adaptive Vehicle Position Control for Dynamic Wireless Charging
论文作者
论文摘要
动态无线充电（DWC）是一项新兴技术，允许电动汽车（EV）在运动中无线充电。它正在获得巨大的动力，因为它可以解决电动汽车的范围限制问题。但是，由于无线功率传输引起的大量功率损失，提高充电效率仍然是DWC系统的主要挑战。本文介绍了第一个用于DWC的基于LSTM的车辆运动控制系统，旨在最大化充电效率。 DWC系统发射器线圈产生的电磁场的动力学是基于多层LSTM建模的。 LSTM模型用于预测电磁强度最大的横向位置，并相应地控制EV运动以优化充电效率。进行了仿真，以证明与最先进的车辆运动控制系统相比，我们基于LSTM的方法的充电效率提高了162.3％，该系统的重点是将EV保持在车道的中心。
Dynamic wireless charging (DWC) is an emerging technology that allows electric vehicles (EVs) to be wirelessly charged while in motion. It is gaining significant momentum as it can potentially address the range limitation issue for EVs. However, due to significant power loss caused by wireless power transfer, improving charging efficiency remains as a major challenge for DWC systems. This paper presents the first LSTM-based vehicle motion control system for DWC designed to maximize charging efficiency. The dynamics of the electromagnetic field generated by the transmitter coils of a DWC system are modeled based on a multi-layer LSTM. The LSTM model is used to make a prediction of the lateral position where the electromagnetic strength is expected to be maximal and to control the EV motion accordingly to optimize charging efficiency. Simulations were conducted to demonstrate that our LSTM-based approach achieves by up to 162.3% higher charging efficiency compared with state-of-the-art vehicle motion control systems focused on keeping an EV in the center of lane.
