30권 4호 297-304 2022 [한국자동차공학회 논문집 ]
| 제목 | 확장칼만필터 기반 실시간 노이즈 파라미터 보정을 적용한 적응형 클라우드 배터리시스템 구현 |
|---|---|
| 분야 | 전기동력자동차 |
| 언어 | Korean |
| 저자 | 이동재(충남대학교), 이평연(충남대학교), 박진형(충남대학교), 권상욱(충남대학교), 김종훈(충남대학교) |
| Key Words | Battery management system(배터리관리시스템), Cloud platform(클라우드 플랫폼), Extended Kalman filter(확장칼만필터), Internet-of-things(사물 인터넷), State-of-charge estimation(충전 상태 추정) |
| 초록 |
In this paper, the cloud platform-based battery management system(BMS) is implemented to control the EKF noise parameter in real-time. To build a stable communication environment, the message queuing telemetry transport(MQTT) protocol is selected, optimized for Internet-of-things(IoT) communication with commercial cloud platform. For verification in the dynamic system, the BMS is verified through the dynamic stress test(DST) profile, which is one of the electric vehicle(EV) driving profiles. In this result, we propose an adaptive cloud battery management system that can be applied to specific situations by enabling bi-directional control between the cloud server and the battery management system. |
| 원문(PDF) | 다운로드 Journal Site |