TY - JOUR
T1 - Online reduced complexity parameter estimation technique for equivalent circuit model of lithium-ion battery
AU - Saleem, Komal
AU - Mehran, Kamyar
AU - Ali, Zunaib
PY - 2020/8/1
Y1 - 2020/8/1
N2 - For control-oriented battery management applications in electric vehicles, Equivalent Circuit Model (ECM) of battery packs offer acceptable modelling accuracy and simple mathematical equations for including the cell parameters. However, in real-time applications, circuit parameters continuously changes by varying operating conditions and state of the battery and thus, require an online parameter estimator. The estimator must update the battery parameters with less computational complexity suitable for real-time processing. This paper presents a novel Online Reduced Complexity (ORC) technique for the online parameter estimation of the ECM. The proposed technique provides significantly less complexity (hence estimation time) compared to the existing technique, but without compromising the accuracy. We use Trust Region Optimization (TRO) based Least Square (LS) method as an updating algorithm in the proposed technique and validate our results experimentally using Nissan Leaf (pouch) cells and with the help of standard vehicular testing cycles, i.e. the Dynamic Driving Cycle (DDC), and the New European Driving Cycle (NEDC).
AB - For control-oriented battery management applications in electric vehicles, Equivalent Circuit Model (ECM) of battery packs offer acceptable modelling accuracy and simple mathematical equations for including the cell parameters. However, in real-time applications, circuit parameters continuously changes by varying operating conditions and state of the battery and thus, require an online parameter estimator. The estimator must update the battery parameters with less computational complexity suitable for real-time processing. This paper presents a novel Online Reduced Complexity (ORC) technique for the online parameter estimation of the ECM. The proposed technique provides significantly less complexity (hence estimation time) compared to the existing technique, but without compromising the accuracy. We use Trust Region Optimization (TRO) based Least Square (LS) method as an updating algorithm in the proposed technique and validate our results experimentally using Nissan Leaf (pouch) cells and with the help of standard vehicular testing cycles, i.e. the Dynamic Driving Cycle (DDC), and the New European Driving Cycle (NEDC).
KW - Equivalent circuit model
KW - Lithium-ion battery, Battery management system
KW - Parameter estimation
KW - Driving cycles
KW - Nissan leaf pouch cell
U2 - 10.1016/j.epsr.2020.106356
DO - 10.1016/j.epsr.2020.106356
M3 - Article
VL - 185
SP - 1
EP - 11
JO - Electric Power Systems Research
JF - Electric Power Systems Research
SN - 0378-7796
M1 - 106356
ER -