$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

Parameter Estimation by OE model of DC-DC Converter System for Operating Status Diagnosis 원문보기

KIEE international transactions on electrical machinery and energy conversion systems, v.4B no.4, 2004년, pp.206 - 210  

Jeon, Jin-Hong (Industry Applications Research Laboratory, Korea Electro-technology Research Institute) ,  Kim, Tae-Jin (Industry Applications Research Laboratory, Korea Electro-technology Research Institute) ,  Kim, Kwang-Su (Industry Applications Research Laboratory, Korea Electro-technology Research Institute) ,  Kim, Kwang-Hwa (Industry Applications Research Laboratory, Korea Electro-technology Research Institute)

Abstract ▼ AI-Helper 아이콘AI-Helper

This paper deals with a parameter estimation of the DC-DC converter system for its diagnosis. Especially, we present the results of parameter estimation for the DC-DC converter model by the system identification method. The parameter estimation for the DC-DC converter system aims at the diagnosis of...

주제어

#DC-DC Converter   #on-line diagnosis   #parameter estimation   #system identification  

AI 본문요약
AI-Helper 아이콘 AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

제안 방법

  • In this paper, we present the parameter estimation results of the DC-DC converter system by using an OE model for its diagnosis and verify its estimated results by comparing measured frequency response with HP4194. From these results, this paper comes up with the possibility of on-line diagnosis for power conversion devices by a system identification method. Hereafter, study will involve another applicable model for system identification and on-line diagnosis.
  • In this paper, we present the parameter estimation results of the DC-DC converter system by using an OE model for its diagnosis and verify its estimated results by comparing measured frequency response with HP4194. From these results, this paper comes up with the possibility of on-line diagnosis for power conversion devices by a system identification method.
  • In this study, we compose the test system displayed in Fig. 6in order to verify an estimated transfer function that used an OE model to measure a frequency response of the DC-DC converter that was used in the experiment by utilizing an HP4194 control system measuring instrument.
  • Therefore, for system identification, we can extract the input white noise components and their output voltage components from the experimental results. In this study, we estimate the major parameter of the DC- DC converter by using the system identification toolbox of MATLAB from extracted input and output data. The results comparing the estimated values with the calculated theoretical values are listed in Table 3.
  • Therefore, for systemic diagnosis during on-line status, this paper deals with parameter estimation of the DC-DC converter system. In particular, we present the results of parameter estimation for the DC-DC converter model by the system identification method.

이론/모형

  • As estimate coefficients of the transfer function, we applied the OE (output-error) model in this study. The structure of the OE model is like as in the following equation 2 and Fig.
본문요약 정보가 도움이 되었나요?

참고문헌 (8)

  1. A.J. Margues Cardoso, ‘Converter Fault Diagnosis in Variable Speed DC Drives, by Park's Vector’, ISIE'97, pp. 497-500 

  2. A. Landi, L. Sani, 'Modulating function testing the performance of switch mode converter', IEEE. SDEMPED 01, pp.195-200 

  3. CLERC Guy, etc. ‘Cegely's Diagnostic tools for electrical drives’, IEEE. SDEMPED 01, pp. 85-89 

  4. Amini Lahyani, etc, ‘Failure Prediction of Electrolytic Capacitors during Operation of a Switch mode Power Supply’, IEEE Transaction on PE., Vol.13, No.6, Nov. 1998 

  5. Tae-Jin KIM, etc. 'Diagnosis of DC/DC converter aging with parasitic resistance', KIPE. PEAC 2003, 2003. 7, pp. 97-101 

  6. Lennart Ljung, System Identification, Pentice Hall, 1999 

  7. Jin-Hong JEON, etc, 'The Design and Implementation of Platform for DC-DC Converter Diagnosis Using Java Virtual Machine', The Energy Engineering Journal, Volume 13-A Number 3 pp.213-218, September 2004 

  8. Jin-Hong JEON, etc, ‘Parameter Estimation of DC-DC Converter System for Operating Status Diagnosis’, The ICEE2004, pp.881-884, July 2004, Sapporo, Japan 

관련 콘텐츠

섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로