Coupler Loss Analysis of Magnetically Coupled Resonant Wireless Power Transfer System

The demand for electric vehicles has increased over the past few years.Wireless power transfer for electric vehicles provides more flexibility than traditional plug-in charging technology.Charging couplers are critical components in wireless power transfer systems.The thermal effect produced by the magnetic coupler in work will cause the temperature of the device to rise rapidly,affecting the work efficiency,transfer power,operation reliability,and service life.This paper modeled and analyzed each component's temperature distribution characteristics and thermal behavior.Firstly,the magnetic coupler's mutual inductance and magnetic circuit model are established,and the thermal model of the magnetic coupler analyzes the heat generation process.The thermal models of the coupler under three different magnetic core distributions are established,and the temperature rise of each component is obtained.The temperature rise of different parts of the coupler is verified by the temperature rise test structure of the experiment.

Magnetic Coupler Robust Optimization Design for Electric Vehicle Wireless Charger Based on Improved Simulated Annealing Algorithm

Fleets of autonomous vehicles including shuttle buses,freight trucks,and road sweepers will be deployed in the Olympic Vil-lage during Beijing 2022 Winter Olympics.This requires intelligent charging infrastructure based on wireless power transfer technology to be equipped.To increase the misalignment tolerance of a high-power wireless charger,the robustness of the magnetic coupler should be optimized.This paper presents a new type of unipolar coupler,which is composed of three con-nected coils in series.The dimensional configuration of the coils is analyzed by the finite element method.The characteristic parameters of the coil are identified with their influence on the self-inductance and coupling coefficient.An expert model is built,whose feasibility can be verified in the aimed design domain.Combined with the expert model,an improved simulated annealing algorithm with a backtracking mechanism is proposed.The primary coil can reach the expected characteristics from any starting parameter combination through the proposed optimization algorithm.Under the same conditions in terms of external circuit parameters,ferrite usage,and aluminum shielding,the offset sensitivity of the magnetic coupler can be reduced from 58.79%to 18.89%.A prototype is established,validating the feasibility of the proposed coil structure with the optimized parameter algorithm.

Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

The permanent magnet eddy current coupler(PMEC)solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems.It provides torque to the load and generates heat and losses,reducing its energy transfer efficiency.This issue has become an obstacle for PMEC to develop toward a higher power.This paper aims to improve the overall performance of PMEC through multi-objective optimization methods.Firstly,a PMEC modeling method based on the Levenberg-Marquardt back propagation(LMBP)neural network is proposed,aiming at the characteristics of the complex input-output relationship and the strong nonlinearity of PMEC.Then,a novel competition mechanism-based multi-objective particle swarm optimization algorithm(NCMOPSO)is proposed to find the optimal structural parameters of PMEC.Chaotic search and mutation strategies are used to improve the original algorithm,which improves the shortcomings of multi-objective particle swarm optimization(MOPSO),which is too fast to converge into a global optimum,and balances the convergence and diversity of the algorithm.In order to verify the superiority and applicability of the proposed algorithm,it is compared with several popular multi-objective optimization algorithms.Applying them to the optimization model of PMEC,the results show that the proposed algorithm has better comprehensive performance.Finally,a finite element simulation model is established using the optimal structural parameters obtained by the proposed algorithm to verify the optimization results.Compared with the prototype,the optimized PMEC has reduced eddy current losses by 1.7812 kW,increased output torque by 658.5 N·m,and decreased costs by 13%,improving energy transfer efficiency.