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Energies 2016,9, 563
2. ExistingBatteryModels
Differentmodelingapproachesare foundin the literature. Themostprominentbatterymodeling
techniques are: Electrochemical, analytical, and circuit-basedmodels [8]. Electrochemicalmodels
employnon-lineardifferential equations tomodel thechemicalandelectricalbehaviorof thecell [4,9].
Detailedknowledgeof thebattery chemistry,material structure andotherphysical characteristics
are essential to achieve high accuracy and cover a large number of different operating points.
However, the producers of batteries will rarely reveal the full parameters set of their products.
Anothershortcomingofelectrochemicalmodels is thehighcomputationaleffort requiredtosolve the
non-linearpartialdifferentialequations [8]. Electrochemicalmodelsarebettersuitedforresearch in
battery’scomponents fabrication, likeelectrodesandelectrolyte [4,10]. Theanalyticalmodeling,onthe
otherhand, reduces the computational complexity for thebattery. However, thatwouldbeon the
expenseofcapturingthecircuitphysical featuresof thebattery, suchasopencircuitvoltage,output
voltage, internal resistance,andtransient response [8].
Lumped electrical circuit models offer low complexity combined with high accuracy and
robustness insimulatingbatteriesdynamics [11–13].Modelswithsingleordoubleresistor-capacitor
(RC) networks are the best candidates for simulating the batterymodule [12–14]. RCparameters
employedtomodel thebatterycharacteristic showadependencyontemperature, charge/discharge
ratesandtheSOC.Several techniqueshadbeendiscussedin literature [1,15–19] forSOCestimation.
Lam and Bauer [20] proposed a circuit model for the Li-ion battery with variable open circuit
voltages, resistances and capacitances. The equivalent circuit components were represented as
empirical functions of the current direction, the SOC, the battery temperature and the C-rate.
Tremblayetal. [5,21]proposedanimprovedversionShepherd’smodel [22]. Thismodelconsiders the
influenceofSOContheOCVbyconsideringthepolarizationvoltage in thedischarge-chargemodel.
Differentdynamicmodels forLi-ion, lead-acid,NiMHandNiCdbattery typedwerepresented in
Reference [5]. However, neither the temperature effect nor thevariationof the internal resistance
were considered. Sawet al. [23] investigated the thermalbehavior for aLiFePO4–graphitebattery
by coupling the empirical equations of the modified Shephard’s battery model with a lumped
thermalmodel for the battery cell. The temperature development of a complete vehicle battery
packunderdifferentdrivingcycleswassimulated in[23]. Tanetal. [24]have incorporatedthe thermal
losses to Shephard’smodel for Li-ion battery cells by adding temperature dependent correction
terms to themodel. Wijewardana et al. [1] proposed a generic electro-thermalmodel for Li-ion
batteries. Themodelconsiderspotential correctiontermsaccountingforelectrodefilmformationand
electrolyte electron transfer chemistry. In addition, the constant values in the empirical equations
that represent theequivalentcircuit componentsof thebatterywereadjusted. Theseequationswere
employedtomodel theelectrical components independenceofSOCandtemperature.Wijewardana
et al. consider theC-rate effect in the estimationof SOCbyemployinganextendedKalmanfilter
technique.Computational thermalmodelsandtemperaturedistributionestimationswereproposed
in References [25–28]. Additionally, finite element analysis models to estimate the temperature
distribution inthebatterywerepresentedinReferences [25,27–29]. Thiskindofsimulationrequires
knowledge of thermal properties of the battery cell materials, such as thermal capacity, density,
mechanicalconstructionandcoolingof thebattery. Foranaccurateparameterization intensiveand
precisemeasurementsarenecessary.
3.OverviewofSelectedDynamicBatteryModels
Theequivalentcircuitbatterymodelprovidesageneric,dynamicwayofmodelingLi-ionbatteries
withmoderatecomplexity. Themoderatemodelcomplexitysupports the integrationof themodel in
amultiphysicalsimulation,allowingtoanalyzedynamiceffectsoftheelectricdrivetrain. Threemodels
areselectedfromthe literatureas thebestcandidates forLi-ionbatterymodeling, since theyare the
most thoroughamongthereviewedmodels. Thesemodelsare:
128
Emerging Technologies for Electric and Hybrid Vehicles
- Title
- Emerging Technologies for Electric and Hybrid Vehicles
- Editor
- MDPI
- Location
- Basel
- Date
- 2017
- Language
- English
- License
- CC BY-NC-ND 4.0
- ISBN
- 978-3-03897-191-7
- Size
- 17.0 x 24.4 cm
- Pages
- 376
- Keywords
- electric vehicle, plug-in hybrid electric vehicle (PHEV), energy sources, energy management strategy, energy-storage system, charging technologies, control algorithms, battery, operating scenario, wireless power transfer (WPT)
- Category
- Technik