The Design And Implementation Of A Magnetic Resonance Based System For Simultaneous Wireless Information And Power Transfer

Wireless power transfer(WPT)technology is an important supporting technology in the era of the Internet of Everything.It can freely and autonomously supply power to electrical equipment in a space to ensure the operation of the equipment.Although the technology is light,clean and efficient,it can be widely used in many fields such as electric vehicles,portable devices,and the Internet of Things.However,the wireless power transfer system is in a working state for a long time,which will cause a waste of resources,especially when working at high frequency and high power.The magnetic resonance wireless power transfer technology is more prominent.In this thesis,the Simultaneous Wireless Information and Power Transfer(SWIPT)system,a technology that combines traditional electromagnetic waves with information transfer technology,and simultaneously transmits power and information,is applied to device detection and identification to further reduce the loss of system resources.The main work of this thesis includes:1.An out-of-band SWIPT equipment detection scheme based on Air Fuel standard is proposed.This solution mainly uses out-of-band Bluetooth communication to exchange information with the system,and combines circuit phase shift detection to jointly detect and identify devices,reducing the possibility of detection errors and interference from foreign objects.This solution can accurately detect and identify electronic devices in the charging area,but the out-of-band SWIPT system increases the complexity of the system.2.Designed an in-band SWIPT system based on signal modulation,so that power and information are transmitted in the same channel.The system design utilizes the high-speed signal processing capability of the Field Programmable Logic Gate Array(FPGA),and uses the FSK signal modulation method to load information into the power signal to form an power-carrying signal,which simplifies the circuit of the out-of-band SWIPT system,and the system data transfer rate is up to 1Mbps.3.An online training and information demodulation system based on machine learning SVM is proposed.This system optimizes the problem of high error rate of traditional demodulation caused by frequency separation and circuit impedance mismatch in electromagnetic field coupling.Using machine learning classifiers to classify and demodulate power-carrying signals can improve demodulation performance.In addition,in view of the problem of signal synchronization communication,a signal modulation method and communication protocol fused with FSK and ASK are designed to ensure the quality of communication and the accuracy of demodulation.In general,with the increasing demand for power and the rapid development of information technology,SWIPT technology not only needs to reduce power loss,but also improve the accuracy of information transmission.Adopting a suitable system architecture,adopting a reasonable work plan,and adopting an efficient classification algorithm are important means to improve the performance of the SWIPT system.