Lithium battery capacity estimation method based on PCA and GA-BP neural network
DOI:
CSTR:
Author:
Affiliation:

School of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, Henan 471003

Clc Number:

TM912

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Aiming at the problem that the capacity estimation method of lithium-ion battery for vehicle is not high precision, a method of residual capacity estimation of lithium-ion battery based on BP neural network optimized by genetic algorithm is proposed in this paper. First, after collating NASA's lithium-ion battery data set, the peak value of battery capacity increment curve under different health conditions was obtained. Secondly, the health factor was analyzed by principal component analysis to reduce its dimension, and the connection weight of BP neural network was optimized by genetic algorithm to predict the capacity of lithium ion battery. Finally, the model was validated on different NASA batteries. The results show that the proposed method can accurately estimate the capacity of four kinds of lithium ion batteries under different training amounts, and the square mean error of the estimation is less than 2%, and the proposed method has higher prediction accuracy than the prediction results without genetic algorithm optimization.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: May 16,2024
  • Published:
Article QR Code