Lithium Ion Battery Models and Parameter Identification Techniques

Barcellona, Simone; Piegari, Luigi

doi:10.3390/en10122007

Cited by 111 publications

(55 citation statements)

References 153 publications

(178 reference statements)

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“…In addition, battery modelling is subject to uncertainties, as battery aging depends on a variety of parameters and different battery models exist with different accuracy (cf. [53,54]).…”

Section: Limitations Of the Studymentioning

confidence: 99%

LAEND: A Model for Multi-Objective Investment Optimisation of Residential Quarters Considering Costs and Environmental Impacts

et al. 2020

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Renewable energy systems are especially challenging both in terms of planning and operation. Energy system models that take into account not only the costs but also a wide range of environmental impacts support holistic planning. In this way, burden-shifting caused by greenhouse gas mitigation can be identified and minimised at an early stage. The Life cycle Assessment based ENergy Decision support tool LAEND combines a multi-criteria optimising tool for energy system modelling and an integrated environmental assessment for the analysis of decentral systems. By a single or multi-objective optimisation, considering costs, environmental impact indicators as well as weighted impact indicator sets, the model enables the determination of optimal investment planning and dispatch of the analysed energy system. The application of LAEND to an exemplary residential quarter shows the benefit of the model regarding the identification of conflicting goals and of a system that compensates for the different objectives. The observed shift of environmental impacts from the use phase to the production phase of the renewable electricity generators points further to the importance of the integration of the entire life cycle.Energies 2020, 13, 614 2 of 22 detailed consideration. On the community level, less technical, administrative and economic resources for sustainable energy projects are available which hinders a successful transition. Decision support at the community level, therefore gains importance [8].With regard to climate impacts, renewable energies are often considered carbon-free in general and to emit less or no emissions to the air in the use phase (besides the burning of biomass) [9]. But the utilisation of renewable energies like e.g., wind and photovoltaics, lead to new conflicts of goals only partly implicated by storage needs: use of resources, especially the exploitation of rare earth materials, toxicities, land use and the loss of biodiversity might increase [10][11][12][13]. Additionally, the environmental impacts shift from the use phase (key emission phase of fossil energies) to the manufacturing phase of the energy converters (key emission phase of renewable energies and storages) [14].Thus, decision support considering the environmental impact of decentral energy systems gains importance and needs to cope with additional requirements in terms of:

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“…In addition, battery modelling is subject to uncertainties, as battery aging depends on a variety of parameters and different battery models exist with different accuracy (cf. [53,54]).…”

Section: Limitations Of the Studymentioning

confidence: 99%

LAEND: A Model for Multi-Objective Investment Optimisation of Residential Quarters Considering Costs and Environmental Impacts

et al. 2020

View full text Add to dashboard Cite

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“…The electrochemical reactions and characteristics of the electrode and electrolyte can be identified by separating the frequency region of the EIS spectra [28][29][30][31][32]. Waag et al [28] used an equivalent circuit model that simply consists of ohmic resistance, charge transfer resistance, and double layer capacitance.…”

Section: Interfacial Resistance Due To Different C/pvdf Ratiosmentioning

confidence: 99%

The Effect of Active Material, Conductive Additives, and Binder in a Cathode Composite Electrode on Battery Performance

Lee¹

2019

Energies

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The current study investigated the effects of active material, conductive additives, and binder in a composite electrode on battery performance. In addition, the parameters related to cell performance as well as side reactions were integrated in an electrochemical model. In order to predict the cell performance, key parameters including manganese dissolution, electronic conductivity, and resistance were first measured through experiments. Experimental results determined that a higher ratio of polymer binder to conductive additives increased the interfacial resistance, and a higher ratio of conductive additives to polymer binder in the electrode resulted in an increase in dissolved transition metal ions from the LiMn2O4 composite electrode. By performing a degradation simulation with these parameters, battery capacity was predicted with various fractions of constituents in the composite electrode. The present study shows that by using this integrated prediction method, the optimal ratio of constituents for a particular cathode composite electrode can be specified that will maximize battery performance.

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“…The battery model can be divided into an electrochemical model [8], black box model and equivalent circuit model in terms of its different building mechanisms [9][10][11][12]. The electrochemical model is based on the analysis of chemical reactions inside the battery, and the partial differential equation is established to describe the electrodes and electrolyte dynamics [13,14]. It is suitable for optimum design and the safety analysis of the battery [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries

et al. 2020

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An accurate estimation of the state of charge for lithium battery depends on an accurate identification of the battery model parameters. In order to identify the polarization resistance and polarization capacitance in a Thevenin equivalent circuit model of lithium battery, the discharge and shelved states of a Thevenin circuit model were analyzed in this paper, together with the basic reasons for the difference in the resistance capacitance time constant and the accurate characterization of the resistance capacitance time constant in detail. The exact mathematical expression of the working characteristics of the circuit in two states were deduced thereafter. Moreover, based on the data of various working conditions, the parameters of the Thevenin circuit model through hybrid pulse power characterization experiment was identified, the simulation model was built, and a performance analysis was carried out. The experiments showed that the accuracy of the Thevenin circuit model can become 99.14% higher under dynamic test conditions and the new identification method that is based on the resistance capacitance time constant. This verifies that this method is highly accurate in the parameter identification of a lithium battery model.

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Lithium Ion Battery Models and Parameter Identification Techniques

Cited by 111 publications

References 153 publications

LAEND: A Model for Multi-Objective Investment Optimisation of Residential Quarters Considering Costs and Environmental Impacts

LAEND: A Model for Multi-Objective Investment Optimisation of Residential Quarters Considering Costs and Environmental Impacts

The Effect of Active Material, Conductive Additives, and Binder in a Cathode Composite Electrode on Battery Performance

An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries

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