Maximum Efficiency Tracking Method for Electric Vehicle Magnetically Coupled Wireless Charging System

Abstract

The invention discloses a maximum efficiency tracking method of an electric automobile magnetic coupling wireless charging system. First of all, mutual inductance between an emission coil and a receiving coil is derived through an initial power supply extraction frequency, and a fitness function is converted into an only frequency-related function; and particle swarm scale in a general particle swarm algorithm is set apart, which is respectively a maximum particle swarm scale Nmax=30 and a minimum particle swarm scale Nmin=2, and the particle swarm scale is gradually decreased as the iteration frequency is increased. According to the invention, redundant particles are reduced from a particle swarm algorithm, the particle swarm scale is changed, the algorithm is concise, and the convergence speed of the algorithm is accelerated. The particle swarm algorithm enables selection of particle scale to be reliably based, the algorithm has a quite large self-learning capability and a social learning capability at a search early stage, and at a later search stage, the convergence speed is accelerated, and the algorithm search time is reduced.

Description

technical field [0001] The present invention relates to the technical field of finding the maximum efficiency of a magnetic coupling wireless charging system for an electric vehicle, in particular to the technical field of searching for system transmission efficiency in a magnetic coupling resonance wireless power transmission system, and specifically relates to a maximum efficiency tracking of a magnetic coupling wireless charging system for an electric vehicle method. Background technique [0002] The charging of electric vehicles has always been a research hotspot. With the development of electric vehicles, convenient and diverse charging methods are becoming more and more popular. The wireless charging technology is convenient and safe to use, has less dust accumulation on the equipment, and has no problems such as contact loss. Therefore, wireless charging technology has received more and more attention in the field of electric vehicles. There are three main ways of wi...

AI Technical Summary

Problems solved by technology

The particle swarm optimization algorithm has advantages in finding multi-peak function values, but for the magnetically coupled wireless power output system, the system efficiency function will have a single or two extreme points. When a single extreme point occurs, use When the basic particle swarm algorithm searches for it, there will be a short-term stagnation phenomenon in the later stage of the algorithm search; for the algorithm itself, too large a particle size will cause the algorithm to perform redundant calculations and take up computing time, while a small size will cause the particles to directly miss the overall situation. The optimal value, even the extreme point cannot be found

According to literature search, the general particle size is set between 20-40, but the precise selection of the particle size has always been based on the individual's continuous attempts to solve the problem, which is very blind

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