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실시간 전기자동차 주행 데이터를 이용한 배터리 건강상태(SOH) 추측 알고리즘 연구A Study on Battery State of Health(SOH) Estimation Algorithm Using Real-time Electric Vehicles Data
- Other Titles
- A Study on Battery State of Health(SOH) Estimation Algorithm Using Real-time Electric Vehicles Data
- Issue Date
- Mar-2025
- Publisher
- 사단법인 한국자동차안전학회
- Keywords
- Electric vehicle(전기자동차); Battery(배터리); BMS(배터리관리시스템); SOH(배터리 잔존가치 수명률); RLS(회귀최소자승법); DEKF(이중확장칼만필터)
- Citation
- 자동차안전학회지, v.17, no.1, pp 48 - 53
- Pages
- 6
- Indexed
- KCI
- Journal Title
- 자동차안전학회지
- Volume
- 17
- Number
- 1
- Start Page
- 48
- End Page
- 53
- ISSN
- 2005-9396
- Abstract
- Recently, the number of electric vehicles has increased due to carbon reduction policies. As the number of electric vehicles registrations increases, research is being conducted to evaluate the batteries installed in electric vehicles. In this study, battery evaluation was performed using real-time driving data of electric vehicles. The RLS (Recursive Least Squares) algorithm and the DEKF (Double Extended Kalman Filter) algorithm were applied using MATLABTM, and BMS data and simulation data were compared for the battery SOC and SOH. As a result, the S OC error rate was confirmed to be less than 2.5% and S OH less than 5.0%. We plan to continuously improve the accuracy of the algorithm by collecting operating data for more than one year.
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Related Researcher
- Park, Sungwook
- COLLEGE OF ENGINEERING (SCHOOL OF MECHANICAL ENGINEERING)