Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10006646,
  title    = {Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method},
  author    = {Cheng Zhang and  James Marco and  Walid Allafi and  Truong Q. Dinh and  W. D. Widanage},
  country   = {United Kingdom},
  institution={University of Warwick},
  abstract  = {Equivalent circuit models (ECMs) are widely used in
battery management systems in electric vehicles and other battery
energy storage systems. The battery dynamics and the model
parameters vary under different working conditions, such as different
temperature and state of charge (SOC) levels, and therefore online
parameter identification can improve the modelling accuracy. This
paper presents a way of online ECM parameter identification using a
continuous time (CT) estimation method. The CT estimation method
has several advantages over discrete time (DT) estimation methods
for ECM parameter identification due to the widely separated battery
dynamic modes and fast sampling. The presented method can be used
for online SOC estimation. Test data are collected using a lithium ion
cell, and the experimental results show that the presented CT method
achieves better modelling accuracy compared with the conventional
DT recursive least square method. The effectiveness of the presented
method for online SOC estimation is also verified on test data.},
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {11},
  number    = {3},
  year      = {2017},
  pages     = {277 - 282},
  ee        = {http://waset.org/publications/10006646},
  url       = {http://waset.org/Publications?p=123},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 123, 2017},
}