원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.8 No.7
2015.07
pp.199-206
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Power battery's remaining capacity is affected by many interior and exterior uncertainties during use. To achieve estimate of current remaining measurable battery power by using battery measurable parameter data, which has always been the core issue of electric vehicle battery management system and the technical difficulties need to be resolved. In this paper, Kalman filtering theory is introduced in estimation algorithm, and then combined with open circuit voltage method and ampere measurement method, the SOC estimation according with the requirements of the electric car is achieved.
목차
Abstract
1. Introduction
2. Extended Kalman Filtering Algorithm
2.1 Kalman Filter Algorithm
2.2 Extended Kalman Filter Algorithm
3. Realization Of Kalman Filtering Algorithm
4. SOC Algorithm Test
5. Concluding Remarks
Acknowledgements
References
1. Introduction
2. Extended Kalman Filtering Algorithm
2.1 Kalman Filter Algorithm
2.2 Extended Kalman Filter Algorithm
3. Realization Of Kalman Filtering Algorithm
4. SOC Algorithm Test
5. Concluding Remarks
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보