제주대학교 Repository

전기자동차 모델링 및 확장 칼만필터를 이용한 배터리 SOC 추정에 관한 연구

Metadata Downloads
Alternative Title
A Study on EV Modeling and Battery SOC Estimation Using Extended Kalman Filter
Abstract
In order to improve battery state of charge (SOC) estimation methods, this research developed an electric vehicle (EV) model using Matlab/Simulink software and compared the modelled performance with test data of an EV developed for actual use. To develop a 28 kW EV using an induction motor, a gearbox with a 1 : 5.5 ratio was used in the powertrain. We utilized an 11.1 kWh battery pack, which included a battery management system (BMS), using 20x2 lithium-polymer battery cells. An on-board charger (OBC) with 220V (AC) input and 22A output was used to charge the battery pack. The technical specifications were obtained through various experiments.
Accurate estimation of battery SOC is one of the key problems in a BMS. This paper proposes a battery SOC estimation method using an extended Kalman filter for lithium-polymer batteries. An electric circuit model (ECM) was set up to represent different degrees of parameter shift due to chemistry, charging, discharging, temperature, and age. Numerical simulation and hardware test results indicate that the proposed algorithm is very useful with respect to improving the accuracy of battery SOC estimation.
Author(s)
양승용
Issued Date
2017
Awarded Date
2017. 8
Type
Dissertation
URI
http://dcoll.jejunu.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000008194
Alternative Author(s)
Yang, Seung Yong
Affiliation
제주대학교 대학원
Department
대학원 에너지응용시스템학부 전기공학전공
Advisor
김호찬
Table Of Contents
그 림 목 차 ⅱ
표 목 차 ⅲ
SUMMARY ⅳ
Ⅰ. 서론 1
Ⅱ. 28 kW급 전기자동차 구성 3
2.1 28 kW급 전기자동차 개요 3
2.2 인덕션 모터 4
2.3 리튬 폴리머 배터리 6
2.4 BMS 7
Ⅲ. 전기자동차 모델링 및 성능 분석 10
3.1 Matlab/Simulink를 사용한 전기자동차 모델링 10
3.2 시뮬레이션 결과 및 전기자동차 운행 성능 분석 16
Ⅳ. 확장 칼만 필터를 이용한 배터리 SOC 추정 24
4.1 배터리의 전기적 등가회로 모델 24
4.2 확장 칼만 필터를 이용한 배터리 SOC 추정 28
V. 결론 34
참 고 문 헌 35
Degree
Master
Publisher
제주대학교 일반대학원
Citation
양승용. (2017). 전기자동차 모델링 및 확장 칼만필터를 이용한 배터리 SOC 추정에 관한 연구
Appears in Collections:
Faculty of Applied Energy System > Electrical Engineering
Authorize & License
  • AuthorizeOpen
Files in This Item:

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.