scholarly journals Parametrisation and Use of a Predictive DFN Model for a High-Energy NCA/Gr-SiOx Battery

2021 ◽  
Author(s):  
Alana Aragon Zulke ◽  
Ivan Korotkin ◽  
Jamie M. Foster ◽  
Mangayarkarasi Nagarathinam ◽  
Harry Hoster ◽  
...  
Keyword(s):  
Predictive Power ◽  
Lithium Ion ◽  
High Energy ◽  
Model Parameters ◽  
Computational Tool ◽  
Lithium Ion Cell ◽  
Galvanostatic Discharge ◽  
A Cell ◽  
Electrochemical Model ◽  
Dfn Model

Abstract We demonstrate the predictive power of a parametrised Doyle-Fuller-Newman (DFN) model of a commercial cylindrical (21700) lithium-ion cell with NCA/Gr-SiOx chemistry. Model parameters result from the deconstruction of a fresh commercial cell to determine/confirm chemistry and microstructure, and also from electrochemical experiments with half-cells built from electrode samples. The simulations predict voltage proles for (i) galvanostatic discharge and (ii) drive-cycles. Predicted voltage responses deviate from measured ones by <1% throughout at least 95% of a full galvanostatic discharge, whilst the drive cycle discharge is matched to a 1-3% error throughout. All simulations are performed using the online computational tool DandeLiion, which rapidly solves the DFN model using only modest computational resource. The DFN results are used to quantify the irreversible energy losses occurring in the cell and deduce their location. In addition to demonstrating the predictive power of a properly validated DFN model, this work provides a novel simplifed parametrisation work that can be used to accurately calibrate an electrochemical model of a cell.

scholarly journals The operation and capacity fade modelling of the lithium-ion cell for electric vehicles

2019 ◽  
Vol 108 ◽  
pp. 01017
Author(s):  
Damian Burzyński ◽  
Leszek Kasprzyk
Keyword(s):  
Electric Vehicles ◽  
Lithium Ion ◽  
Model Parameters ◽  
Average Charge ◽  
Variable Load ◽  
Capacity Fade ◽  
Lithium Ion Cells ◽  
Lithium Ion Cell ◽  
Electrochemical Model ◽  
Nickel Manganese

The paper deals with the issues related to the operation and capacity fade modelling of lithium-ion cells. It includes the presentation of the electrochemical model of the cell in which the phenomenon of diffusion and transfer of charge on electrodes and in electrolyte was discussed. The circuit model of the cell designed for analysis of its behaviour in the conditions of the dynamically variable load was presented. The key aging processes which occur during the operation of the cells were characterised, and their impact on the wear of the cell was discussed. The model of the capacity fade of the lithium-nickel-manganese-cobalt cell was developed. The model parameters depends on the ambient temperature, the value of load current and the value of the average charge current. The results of the model were verified with the laboratory measurement.

scholarly journals Electrochemical Model-Based Investigation of Thick LiFePO4 Electrode Design Parameters

Modelling ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 259-287
Author(s):  
Robert Franke-Lang ◽  
Julia Kowal
Keyword(s):  
Lithium Ion Batteries ◽  
Porous Electrode ◽  
Lithium Ion ◽  
Size Composition ◽  
Design Parameters ◽  
Model Parameters ◽  
Electrode Structure ◽  
Transport Channel ◽  
Scale Particle ◽  
Electrochemical Model

The electrification of the powertrain requires enhanced performance of lithium-ion batteries, mainly in terms of energy and power density. They can be improved by optimising the positive electrode, i.e., by changing their size, composition or morphology. Thick electrodes increase the gravimetric energy density but generally have an inefficient performance. This work presents a 2D modelling approach for better understanding the design parameters of a thick LiFePO4 electrode based on the P2D model and discusses it with common literature values. With a superior macrostructure providing a vertical transport channel for lithium ions, a simple approach could be developed to find the best electrode structure in terms of macro- and microstructure for currents up to 4C. The thicker the electrode, the more important are the direct and valid transport paths within the entire porous electrode structure. On a smaller scale, particle size, binder content, porosity and tortuosity were identified as very impactful parameters, and they can all be attributed to the microstructure. Both in modelling and electrode optimisation of lithium-ion batteries, knowledge of the real microstructure is essential as the cross-validation of a cellular and lamellar freeze-casted electrode has shown. A procedure was presented that uses the parametric study when few model parameters are known.

A Temperature Dependent, Single Particle, Lithium Ion Cell Model Including Electrolyte Diffusion

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Tanvir R. Tanim ◽  
Christopher D. Rahn ◽  
Chao-Yang Wang
Keyword(s):  
Single Particle ◽  
Lithium Ion ◽  
Particle Model ◽  
Voltage Response ◽  
Model Parameters ◽  
Battery Management System ◽  
Temperature Dependent ◽  
Lithium Ion Cell ◽  
Pulse Charge ◽  
Wide Range

Low-order, explicit models of lithium ion cells are critical for real-time battery management system (BMS) applications. This paper presents a seventh-order, electrolyte enhanced single particle model (ESPM) with electrolyte diffusion and temperature dependent parameters (ESPM-T). The impedance transfer function coefficients are explicit in terms of the model parameters, simplifying the implementation of temperature dependence. The ESPM-T model is compared with a commercially available finite volume based model and results show accurate matching of pulse responses over a wide range of temperature (T) and C-rates (I). The voltage response to 30 s pulse charge–discharge current inputs is within 5% of the commercial code for 25 °C<T<50 °C at I≤12.5C and -10 °C<T<50°C at I≤1C for a graphite/nickel cobalt manganese (NCM) lithium ion cell.

scholarly journals Useful Energy Prediction Model of a Lithium-ion Cell Operating on Various Duty Cycles

2021 ◽  
Author(s):  
Damian Burzyński
Keyword(s):  
Prediction Model ◽  
Gaussian Process Regression ◽  
Lithium Ion ◽  
Model Parameters ◽  
Battery Management ◽  
Acceptable Error ◽  
Energy Prediction ◽  
Depth Of Discharge ◽  
Duty Cycles ◽  
Lithium Ion Cell

The paper deals with the subject of the prediction of useful energy during the cycling of a lithium-ion cell (LIC), using machine learning-based techniques. It was demonstrated that depending on the combination of cycling parameters, the useful energy (<i>RUE<sub>c</sub></i>) that can be transfered during a full cycle is variable, and also three different types of evolution of changes in <i>RUE<sub>c</sub></i> were identified. The paper presents a new non-parametric <i>RUE<sub>c</sub></i> prediction model based on Gaussian process regression. It was proven that the proposed methodology enables the <i>RUE<sub>c</sub></i> prediction for LICs discharged, above the depth of discharge, at a level of 70% with an acceptable error, which is confirmed for new load profiles. Furthermore, techniques associated with explainable artificial intelligence were applied, for the first time, to determine the significance of model input parameters – the variable importance method – and to determine the quantitative effect of individual model parameters (their reciprocal interaction) on <i>RUE<sub>c</sub></i> – the accumulated local effects model of the first and second order. Not only is the <i>RUE<sub>c</sub></i> prediction methodology presented in the paper characterised by high prediction accuracy when using small learning datasets, but it also shows high application potential in all kinds of battery management systems.

scholarly journals The Impact of the Vanadium Oxide Addition on the Physicochemical Performance Stability and Intercalation of Lithium Ions of the TiO2-rGO-electrode in Lithium Ion Batteries

Materials ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 1018 ◽  
Author(s):  
Beata Kurc ◽  
Marcin Wysokowski ◽  
Łukasz Rymaniak ◽  
Piotr Lijewski ◽  
Adam Piasecki ◽  
...  
Keyword(s):  
Vanadium Oxide ◽  
Lithium Ion ◽  
Lithium Ions ◽  
Oxide Addition ◽  
Lithium Ion Cell ◽  
Reduced Graphene ◽  
Partial Transfer ◽  
A Cell ◽  
New Type ◽  
The Impact

This work determines the effect of the addition of various amounts of vanadium oxide on the work of a cell built from a hybrid VxOy-TiO2-rGO system in a lithium-ion cell. Moreover, a new method based on solvothermal chemistry is proposed for the creation of a new type of composite material combining reduced graphene, vanadium oxide and crystalline anatase. The satisfactory electrochemical properties of VxOy-TiO2-rGO hybrids can be attributed to the perfect matching of the morphology and structure of VxOy-TiO2 and rGO. In addition, it is also responsible for the partial transfer of electrons from rGO to VxOy-TiO2, which increases the synergistic interaction of the VxOy-TiO2-rGO hybrid to the reversible storage of lithium. In addition a full cell was created LiFePO4/VxOy-TiO2-rGO. The cell showed good cyclability while providing a capacity of 120 mAh g−1.

scholarly journals A Comparison of Lithium-Ion Cell Performance across Three Different Cell Formats

Batteries ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 38
Author(s):  
Grace Bridgewater ◽  
Matthew J. Capener ◽  
James Brandon ◽  
Michael J. Lain ◽  
Mark Copley ◽  
...  
Keyword(s):  
Degradation Mechanism ◽  
Single Layer ◽  
Lithium Ion ◽  
Capacity Loss ◽  
Lithium Ion Cells ◽  
Lithium Ion Cell ◽  
A Cell ◽  
The Difference ◽  
Discharge Capacities

To investigate the influence of cell formats during a cell development programme, lithium-ion cells have been prepared in three different formats. Coin cells, single layer pouch cells, and stacked pouch cells gave a range of scales of almost three orders of magnitude. The cells used the same electrode coatings, electrolyte and separator. The performance of the different formats was compared in long term cycling tests and in measurements of resistance and discharge capacities at different rates. Some test results were common to all three formats. However, the stacked pouch cells had higher discharge capacities at higher rates. During cycling tests, there were indications of differences in the predominant degradation mechanism between the stacked cells and the other two cell formats. The stacked cells showed faster resistance increases, whereas the coin cells showed faster capacity loss. The difference in degradation mechanism can be linked to the different thermal and mechanical environments in the three cell formats. The correlation in the electrochemical performance between coin cells, single layer pouch cells, and stacked pouch cells shows that developments within a single cell format are likely to lead to improvements across all cell formats.

Application of MMAE to the Fault Detection of Lithium-Ion Battery

2014 ◽  
Vol 598 ◽  
pp. 342-346
Author(s):  
Zhao Liu ◽  
Anwar Sohel
Keyword(s):  
Fault Detection ◽  
Lithium Ion Battery ◽  
Adaptive Estimation ◽  
Lithium Ion ◽  
High Energy ◽  
High Energy Density ◽  
Model Parameters ◽  
Multiple Model ◽  
Environmental Friendliness ◽  
Multiple Faults

With the advantage of high energy density, long cycle life and environmental friendliness, Lithium-ion battery has become a promising power source for hybrid and electric vehicles, which are liable to two kinds of failure, overcharge and overdischarge. Because of the capability of detecting multiple faults, Multiple Model Adaptive Estimation (MMAE) method was applied to a model-based fault detection of a lithium-ion battery with a two-order linear electrical model. Parameters that represent normal-mode and faulty-mode of the battery were obtained by a series of experiments, and three Kalman filters were designed thereafter. Finally, simulation verified the performance of the MMAE algorithm on fault detection of these two kinds of fault and it is shown that this technique is able to discern these faults rapidly and accurately.

Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter

2010 ◽  
Vol 132 (6) ◽  
Author(s):  
Domenico Di Domenico ◽  
Anna Stefanopoulou ◽  
Giovanni Fiengo
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Lithium Ion ◽  
State Of Charge ◽  
Critical Surface ◽  
Solid Concentration ◽  
Order Model ◽  
Power Sources ◽  
Lithium Ion Cell ◽  
Electrochemical Model

This paper presents a numerical calculation of the evolution of the spatially resolved solid concentration in the two electrodes of a lithium-ion cell. The microscopic solid concentration is driven by the macroscopic Butler–Volmer current density distribution, which is consequently driven by the applied current through the boundary conditions. The resulting, mostly causal, implementation of the algebraic differential equations that describe the battery electrochemical principles, even after assuming fixed electrolyte concentration, is of high order and complexity and is denoted as the full order model. The full order model is compared with the results in the works of Smith and Wang (2006, “Solid-State Diffusion Limitations on Pulse Operation of a Lithium-Ion Cell for Hybrid Electric Vehicles,” J. Power Sources, 161, pp. 628–639) and Wang et al. (2007 “Control oriented 1D Electrochemical Model of Lithium Ion Battery,” Energy Convers. Manage., 48, pp. 2565–2578) and creates our baseline model, which will be further simplified for charge estimation. We then propose a low order extended Kalman filter for the estimation of the average-electrode charge similarly to the single-particle charge estimation in the work of White and Santhanagopalan (2006, “Online Estimation of the State of Charge of a Lithium Ion Cell,” J. Power Sources, 161, pp. 1346–1355) with the following two substantial enhancements. First, we estimate the average-electrode, or single-particle, solid-electrolyte surface concentration, called critical surface charge in addition to the more traditional bulk concentration called state of charge. Moreover, we avoid the weakly observable conditions associated with estimating both electrode concentrations by recognizing that the measured cell voltage depends on the difference, and not the absolute value, of the two electrode open circuit voltages. The estimation results of the reduced, single, averaged electrode model are compared with the full order model simulation.

scholarly journals A review of lithium ion batteries electrochemical models for electric vehicles

2020 ◽  
Vol 185 ◽  
pp. 04001
Author(s):  
Jiaping Zhou ◽  
Bo Xing ◽  
Chunyang Wang
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Iterative Solution ◽  
Research Progress ◽  
Electrochemical Reactions ◽  
Model Parameters ◽  
Mechanism Analysis ◽  
Simulation Research ◽  
Computational Speed ◽  
Electrochemical Model

The electrochemical model can reflect the electrochemical reactions inside the lithium ion battery, and the model parameters have practical physical significance. Therefore, it is commonly used in the simulation research of the life prediction and the cell decay mechanism analysis of the lithium ion battery. This paper mainly introduces three commonly used electrochemistry models: P2D model, SP model and extended SP model. The origin and research progress of three kinds of electrochemical models are described. The characteristics of the three models are analyzed and compared. P2D model can describe the battery reactions comprehensively, but the iterative solution is complicated. The SP model simplifies some electrochemical reactions and improves the computational speed of the model, but the accuracy is decreased. In order to solve the shortcoming of SP model, the electrochemical reaction omitted from SP model is introduced again, and the approximate solution is solved by mathematical method, so as to realize the balance between precision and computational complexity of the model. Based on the above analysis and the application scenarios of lithium ion battery, the further development of the lithium ion battery electrochemical model is prospected.

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