Parameter Estimation of Single Particle Model Using COMSOL Multiphysics ® and MATLAB ® Optimization Toolbox B. Rajabloo 1 , M. Désilets 1 , Y. Choquette 2 2 Institut de recherche d’Hydro-Québec, Varennes, QC, CANADA 1 Département de génie chimique et de génie biotechnologique, Université de Sherbrooke, QC, CANADA
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Parameter Estimation of Single Particle Model
Using COMSOL Multiphysics® and MATLAB®
Optimization Toolbox
B. Rajabloo1, M. Désilets1, Y. Choquette2
2Institut de recherche d’Hydro-Québec,
Varennes, QC, CANADA
1Département de génie chimique et
de génie biotechnologique,
Université de Sherbrooke, QC, CANADA
R solution
Parameter Estimation of Single Particle Model Using COMSOL
Multiphysics® and MATLAB® Optimization Toolbox
Conclusion
Parameter Estimation
Single Particle Model
October
2015
Parameter Estimation of Single Particle Model Using COMSOL
Multiphysics® and MATLAB® Optimization Toolbox
Single Particle Model
October
2015
4
SPM
Uniform current distribution
Ignore variation of electrolyte
concentration and potential
Assume a lumped solution resistance
Reasonable when:
Low applied current density Thin electrodes Highly conductive electrodes
Positive points:
High speed solution
AgingPackParameter
estimation
Inverse
method
Dynamic
optimization
Single Particle Model
Dao, T. S. et. al., J. Power Sources 198, 329-337 (2012)
5
SPM
02sinh
i
ia
F
RT locneg
)(, negnegnegs SOCEeq
SIiloc
Local current density
Overpotential negative electrode
Potential negative electrode
r
Csr
rr
D
t
Cs 2
2
00
rr
Cs
F
i
r
CsD loc
Rr
Solid concentration
)( negSOCEeq
solutionappnegsposscell RiE ,,
Open circuit potential
(Butler – Volmer equation)
Adjustable
parameter
I: total current
S: total electroactive
surface area
Parameter Estimation of Single Particle Model Using COMSOL
Multiphysics® and MATLAB® Optimization Toolbox
Parameter Estimation
October
2015
7
Parameter estimation
It is not convenient to find all physical and chemical parameters
that are needed for the simulation of lithium-ion cells