A Reinforcement Learning-Based Data-Driven Voltage Regulator for Wireless Chargers of Electric Vehicles

Jiaxin Teng, Lizhi Qu, Dariusz Czarkowski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As a critical component in the concept of smart cities, autonomous vehicles are under extensive investigation. The need for intelligent fueling without human assistance stimulates the development of wireless charging. There are, however, several issues to be addressed to enhance the efficiency and reliability of charging. The vehicle battery exhibits varying resistance during the charging process. Additionally, the alignment and gap may change with external positioning, which affects the coupling coefficient of the transmitter and receiver coils. Thus, a data-driven control scheme is desired to tackle these environmental uncertainties. This paper adopts the control scheme of embedding a Buck converter at the receiver side. Different from state-of-the-art literature, a reinforcement learning-based data-driven control approach is employed to regulate the charging voltage. Stable charging voltage is attained regardless of the knowledge of the coupling coefficient, load variations, or component values. System simulations in Simulink have proved the effectiveness of the proposed control method.

Original languageEnglish (US)
Title of host publicationECCE 2020 - IEEE Energy Conversion Congress and Exposition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3199-3204
Number of pages6
ISBN (Electronic)9781728158266
DOIs
StatePublished - Oct 11 2020
Event12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020 - Virtual, Detroit, United States
Duration: Oct 11 2020Oct 15 2020

Publication series

NameECCE 2020 - IEEE Energy Conversion Congress and Exposition

Conference

Conference12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020
CountryUnited States
CityVirtual, Detroit
Period10/11/2010/15/20

Keywords

  • Reinforcement learning-based data-driven control
  • Wireless power transfer

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology

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