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Deep Learning Based Error Control in Electric Vehicle Charging Systems Using Power Line Communication

전력선 통신을 이용한 전기자동차 충전 시스템에서 딥 러닝 기반 오류제어

  • Sun, Young Ghyu (Dept. of Wireless Communications Eng., Univ. of Kwangwoon) ;
  • Hwang, Yu Min (Dept. of Wireless Communications Eng., Univ. of Kwangwoon) ;
  • Sim, Issac (Dept. of Wireless Communications Eng., Univ. of Kwangwoon) ;
  • Kim, Jin Young (Dept. of Wireless Communications Eng., Univ. of Kwangwoon)
  • Received : 2018.06.27
  • Accepted : 2018.08.21
  • Published : 2018.08.31

Abstract

In this paper, we introduce an electric vehicle charging system using power line communication and propose a method to correct the error by applying a deep learning algorithm when an error occurs in the control signal of an electric vehicle charging system using power line communication. The error detection and correction of the control signal can be solved through the conventional error correcting code schemes, but the error is detected and corrected more efficiently by using the deep learning based error correcting code scheme. Therefore, we introduce deep learning based error correction code scheme and apply this scheme to electric vehicle charging system using power line communication. we proceed simulation and confirm performance with bit error rate. we judge whether the deep learning based error correction code scheme is more effective than the conventional schemes.

본 논문에서는 전력선 통신을 이용하는 전기자동차 충전 시스템에 대해 소개하고 전력선 통신을 이용하는 전기자동차 충전 시스템의 제어 신호에 오류가 발생했을 때 딥 러닝 알고리즘을 적용하여 오류를 정정하는 방식을 제안한다. 제어 신호의 오류 발견과 정정은 기존의 오류정정부호 기법을 통해 해결할 수 있으나 딥 러닝 기반의 오류정정부호 기법을 이용하여 더욱 효율적으로 오류를 발견하고 정정한다. 그래서 딥 러닝 기반의 오류정정부호 기법에 대해 소개하며 이 기법을 전력선 통신을 이용하는 전기자동차 충전 시스템에 적용하여 시뮬레이션을 진행하고 비트 오류율로 성능을 확인하여 딥 러닝 기반의 오류정정부호 기법이 기존의 기법보다 효율적인지를 판단한다.

Keywords

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