Open AccessComparison of Li‐ion battery equivalent circuit modelling using impedance analyzer and Bayesian networks
Author(s) -
Khan Khalid,
Jafari Mehdi,
Gauchia Lucia
Publication year - 2018
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
ISSN - 2042-9746
DOI - 10.1049/iet-est.2017.0087
Subject(s) - battery (electricity) , equivalent circuit , matlab , spectrum analyzer , frequency domain , electrical impedance , time domain , voltage , electronic engineering , electrical network , network topology , engineering , computer science , electrical engineering , power (physics) , physics , quantum mechanics , computer vision , operating system
An energy storage system simulation requires a battery model capable of precisely predicting the dynamic behaviour and I – V characteristics. An equivalent circuit model (ECM) of a battery generates an electric circuit able to replicate complicated battery characteristics. Combination of time domain and frequency domain tests can be utilised to parameterise ECM components properly. The goal of this study is to discuss two systematic approaches to decide the ECM parameters, which can be replicated on any battery technology. Time and frequency domain testing are carried out on a commercial electric bicycle Li‐ion battery composed of Samsung ICR18650–22P. Then, impedance analyzer approach and Bayesian network method are applied to estimate the ECM circuit elements with different circuit topologies. The models were developed in MATLAB/Simulink environment. A highly dynamic drive cycle based on the E‐bike was utilised to validate the ECMs through hardware‐in‐loop testing.