Interactive Wireless Charging In A Cyclic Mobispace

With the development of science and technology,the application of various types of battery-driven mobile agents,such as mobile phones and tablet computers in daily life,drones and robots in specialized fields,and even electric vehicles,has become increasingly popular.Meanwhile,the energy limitation of these mobile agents has become increasingly serious.As the mobile agents’ battery capacity is limited,the mobile agents need to be replenished frequently.But the mobile agents need to be continuously operational,therefore,how to charge the in-motion agents is a challenge.Moreover,with the wide usage of the mobile agents,how to effectively charge these agents and guarantee the operation of each mobile agent is an emerging concern.For these problems,wireless power transfer(WPT)technology can provide a promising solution.We make two observations:the development on the circuit design of energy trans-mit antennas can render mobile agents to be able to bi-directionally,highly efficiently wirelessly transfer energy between themselves;mobile agents tend to have repetitive motions and may cyclically encounter with each other.We combine the bi-directionally wireless transfer technology and the cyclic motion of mobile agents and investigate the following questions which no prior research has investigated.(1)We consider the deployment of charging lanes in a cyclic mobispace.We introduce the problem that maximizing the average efficiency of charging lanes on the basis of the satisfaction of the total energy cost of all EVs in the cyclic mobispace.We propose an algorithm based on greedy strategy.The simulation results show the proposed algorithm can reduce the number of charging lanes by 67.6%on average and improve the average charging efficiency by 2.08 times on average.(2)We investigate the re-distribution of energy among mobile agents in an interac-tive manner.We consider the cases of both loss-less and lossy energy transfer between mobile agents.In both cases,we formulate the problem of minimizing the time need-ed(or energy transferred)to reach a given energy distribution into a series of linear programming problems.When compared with a state-of-the-art algorithm,extensive simulation results show that the proposed algorithms can reduce the balancing time and energy loss by up to 70.60%and 36.59%,respectively.