Research On Swarm Intelligence Optimization For Wireless Power Transmission Array Antenna Synthesis

Wireless power transmission is a technology that transmits energy wirelessly.The system can be optimized by synthesizing antenna array.Antenna array synthesis mainly includes two aspects.On the one hand,the antenna pattern is studied,that is,the array antenna is synthesized according to the antenna pattern target;On the other hand,the beam collection efficiency of the antenna is studied,that is,taking the beam collection efficiency as the objective function,various parameters of the array antenna are optimized.At present,wireless power transmission technology has been gradually applied in many aspects of life,such as mobile phone,computer charging,electric car power supply and so on.Other applications envisaged include supplying energy to various terminal nodes,as well as applications such as solar satellites.Therefore,it is of great significance to study wireless power transmission.In this thesis,the efficiency of antenna beam collection is studied mainly through various swarm intelligence optimization algorithms.Swarm intelligence optimization algorithm is a new optimization method,which simulates various biological characteristics to optimize various practical engineering problems.Common algorithms include artificial bee colony algorithm,ant colony algorithm,particle swarm optimization algorithm,etc.The appearance of swarm intelligence optimization algorithm provides a great help for people to solve optimization problems.Therefore,in recent years,researchers at home and abroad have more and more studies on swarm intelligence optimization algorithm,and put forward many new swarm intelligence optimization algorithm.Existing antenna synthesis methods are not ideal in terms of accuracy and efficiency.How to further improve the accuracy and efficiency of the beam collection efficiency has become a problem to be solved at present.To solve this problem,this thesis combines swarm intelligence optimization algorithm with wireless power transmission to study the accuracy and efficiency of beam collection efficiency.Specific research contents are as follows:(1)Based on the geometric models of the one-dimensional antenna array and the twodimensional planar antenna array,the expression of the array factor and the beam collection efficiency of the corresponding antenna array is given in this thesis.All the studies in this thesis are based on these two expressions.On this basis,this thesis firstly studies the synthesis of onedimensional and two-dimensional antenna arrays based on solving the generalized characteristic equation,and analyzes the results obtained.(2)Under the framework of one-dimensional antenna array,the optimization of beam collection efficiency by genetic algorithm and brainstorming algorithm is studied.Firstly,the algorithm models of genetic algorithm and brainstorming algorithm were established with the beam collection efficiency as the objective function.Then,constraints such as antenna aperture and minimum adjacent array element interval were added to optimize the beam collection efficiency,so as to obtain the optimal results.The optimal value and average value of the results obtained by the two algorithms are compared one by one.The results show that the optimal value and average value obtained by brainstorming algorithm are better than those obtained by using genetic algorithm.(3)Under the framework of two-dimensional planar antenna array,the optimization of beam collection efficiency by particle swarm optimization algorithm and brainstorming algorithm is studied.Similarly,taking the beam collection efficiency as the objective function,the algorithm models of particle swarm optimization(PSO)and brainstorming algorithm are established.In addition to constraints such as antenna aperture and minimum adjacent array element interval,constraints of side lobe level are also added to optimize the beam collection efficiency,so as to obtain the optimal results.The optimal value and average value of the results obtained by the brainstorming algorithm are compared with the results in the literature one by one.The results show that the optimal value and average value obtained by the brainstorming algorithm are better than the results obtained by the literature.