Towards fast embedded moving horizon state-of-charge estimation for lithium-ion batteries [paper]

Wan, Yiming, Songtao Du, Jiayu Yan, and Zhuo Wang.

"Towards fast embedded moving horizon state-of-charge estimation for lithium-ion batteries."

Journal of Energy Storage 78 (2024): 110024.

Keywords

• State-of-charge estimation
• Moving horizon estimation
• Real-time computation
• Lithium-ion battery

Steps to run

• Open Matlab or Octave.
• Set ./matlabcode or ./octavecode as the current working directory.
• Run the main_ekf.m to implement the joint EKF.
• Run the main_optimalMHE.m to implement the optimal jMHE.
• Run the main_fastMHE.m to implement the fast jMHE.
• Run the main_fasterMHE.m to implement the fast jMHE with ETR.

Citation

If you find our work useful in your research or publications, please consider citing:

@article{wan2024towards,
  title={Towards fast embedded moving horizon state-of-charge estimation for lithium-ion batteries},
  author={Wan, Yiming and Du, Songtao and Yan, Jiayu and Wang, Zhuo},
  journal={Journal of Energy Storage},
  volume={78},
  pages={110024},
  year={2024},
  publisher={Elsevier}
}