Optimal Path Configuration with Coded Laser Pilots for Charging Electric Vehicles Using High Intensity Laser Power Beams

Abstract

Wireless power transmission (WPT) for wireless charging has been gaining wide attention as a promising approach to miniaturizing the battery size and increasing the maximal total range of an electric vehicle (EV). With an appropriate charging infrastructure, WPT holds great potential to accelerate the acceptance of EVs through users’ higher satisfaction, reducing EV cost, and increasing the driving range and capability. A WPT system based on high-intensity laser power beaming (HILPB) provides an optimal solution for wirelessly charging electric vehicles from a distance of several meters. Despite a large number of WPT approaches, the problem of optimal path configuration for charging EV remains an unexplored area. This paper proposes a method to determine the optimal power transmission path in environments where multiple power transmitters (PTXs) and power receivers (PRXs) are operated simultaneously. To this end, we modeled the HILPB power that reaches a PRX equipped with a photovoltaic (PV) array and validated the model by simulating the WPT process in an environment with multiple PTXs and PRXs using a direct-sequence optical code division multiple access (DS-OCDMA) system. In the simulation environment, upon receiving a request from a PRX, a PTX sent its power channel information through optically encoded laser pulses using each available wireless power channel (WPC). The PRX calculated the maximum deliverable power of a PTX and WPC based on the received channel power indicator of the incident laser beam. Based on the calculation results, it selected the optimal PTX and WPC for its maximum power requirement (MPQ). The MPQ of each PRX was satisfied by applying the algorithm for selecting the PTX according to the alignment and characteristics of the PTXs and PRXs. We modeled a power reception model of the PRX based on a PV array using coded laser pilots and validated it through experimentation. We discussed some algorithms that select the most suitable PTX among several PTXs for which several EVs receive the power it needs.