Extended Kalman Filter-Based State of Charge and State of Power Estimation Algorithm for Unmanned Aerial Vehicle Li-Po Battery Packs

Sunghun Jung, Heon Jeong

Open source

DOI: 10.3390/en10081237
Published: 2017-08-21
Container: Energies
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/en10081237,
  title = {Extended Kalman Filter-Based State of Charge and State of Power Estimation Algorithm for Unmanned Aerial Vehicle Li-Po Battery Packs},
  author = {Sunghun Jung and Heon Jeong},
  year = {2017},
  journal = {Energies},
  doi = {10.3390/en10081237},
  url = {https://doi.org/10.3390/en10081237}
}

RIS

TY  - JOUR
TI  - Extended Kalman Filter-Based State of Charge and State of Power Estimation Algorithm for Unmanned Aerial Vehicle Li-Po Battery Packs
AU  - Sunghun Jung
AU  - Heon Jeong
PY  - 2017
JO  - Energies
DO  - 10.3390/en10081237
UR  - https://doi.org/10.3390/en10081237
ER  -

APA

Jung, S., & Jeong, H. (2017). Extended Kalman Filter-Based State of Charge and State of Power Estimation Algorithm for Unmanned Aerial Vehicle Li-Po Battery Packs. Energies. https://doi.org/10.3390/en10081237

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crossref · retrieved 2026-09-25T07:09:44.986Z