Li-ion Battery Cells Research Articles

4D Bragg Edge Tomography of Directional Ice Templated Graphite Electrodes.

Bragg edge tomography was carried out on novel, ultra-thick, directional ice templated graphite electrodes for Li-ion battery cells to visualise the distribution of graphite and stable lithiation phases, namely LiC12 and LiC6. The four-dimensional Bragg edge, wavelength-resolved neutron tomography technique allowed the investigation of the crystallographic lithiation states and comparison with the electrode state of charge. The tomographic imaging technique provided insight into the crystallographic changes during de-/lithiation over the electrode thickness by mapping the attenuation curves and Bragg edge parameters with a spatial resolution of approximately 300 µm. This feasibility study was performed on the IMAT beamline at the ISIS pulsed neutron spallation source, UK, and was the first time the 4D Bragg edge tomography method was applied to Li-ion battery electrodes. The utility of the technique was further enhanced by correlation with corresponding X-ray tomography data obtained at the Diamond Light Source, UK.

In-situ investigations of the inhomogeneous strain on the steel case of 18650 silicon/graphite lithium-ion cells

The silicon-graphite composite electrode is the main focus of the high energy and high power density 18650 Li-ion battery cells, while the large volume expansion of the composite electrode may induce the steel case of the cell to deform largely, even rupture. The mechanical reliability of the steel case is very important to the safety and durability of the battery cell. In the paper, the hoop strain of the steel case is in-situ monitored during 18650 Li-ion battery cell operation. At the early cycle stage, the hoop strain of the steel case is induced by the thermal expansion. After a long-term cycle (cycled number > 300 times), inhomogeneous strain distribution, even negative strain, is found on the steel case. Based on the CT images and non-concentric numerical model, it is found that the gap between the jelly roll and steel case is the root of the different hoop strain on the steel case during the cycle. It is suggested that the gap (the diameter ratio of the jelly roll to steel case) need be focused in the engineering design for the cylindrical Li-ion battery cell with next-generation silicon composite electrode.

Multiple-imputation-particle-filtering for Uncertainty Characterization in Battery State-of-Charge Estimation Problems with Missing Measurement Data: Performance Analysis and Impact on Prognostic Algorithms

The implementation of particle-filtering-based algorithms for state estimation purposes often has to deal with the problem of missing observations. An efficient design requires an appropriate methodology for real-time uncertainty characterization within the estimation process, incorporating knowledge from other available sources of information. This article analyzes this problem and presents preliminary results for a multiple imputation strategy that improves the performance of particle-filtering-based state-of-charge (SOC) estimators forlithium-ion (Li-Ion) battery cells. The proposed uncertainty characterization scheme is tested, and validated, in a case study where the state-space model requires both voltage anddischarge current measurements to estimate the SOC. A sudden disconnection of the battery voltage sensor is assumed to cause significant loss of data. Results show that the multipleimputation particle filter allows reasonable characterization of uncertainty bounds for state estimates, even when the voltage sensor disconnection continues. Furthermore, if voltage measurements are once more available, the uncertainty bounds adjust to levels that are comparable to the case where data were not lost. As state estimates are used as initial conditions for battery End-of-Discharge (EoD) prognosis modules, we also studied how these multiple-imputation algorithms impact on the quality of EoD estimates.

Monoclinic α-Na2FePO4F with Strong Antisite Disorder and Enhanced Na+ Diffusion.

A new monoclinic α-polymorph of the Na2FePO4F fluoride-phosphate has been directly synthesized via a hydrothermal method for application in metal-ion batteries. The crystal structure of the as-prepared α-Na2FePO4F studied with powder X-ray and neutron diffraction (P21/c, a = 13.6753(10) Å, b = 5.2503(2) Å, c = 13.7202(8) Å, β = 120.230(4)°) demonstrates strong antisite disorder between the Na and Fe atoms. As revealed with DFT-based calculations, α-Na2FePO4F has low migration barriers for Na+ along the main pathway parallel to the b axis, and an additional diffusion bypass allowing the Na+ cations to go around the Na/Fe antisite defects. These results corroborate with the extremely high experimental Na-ion diffusion coefficient of (1-5)·10-11 cm2·s-1, which is 2 orders of magnitude higher than that for the orthorhombic β-polymorph ((5-10)·10-13 cm2·s-1). Being tested as a cathode material in Na- and Li-ion battery cells, monoclinic α-Na2FePO4F exhibits a reversible specific capacity of 90 and 80 mAh g-1, respectively.

PERFORMANCE STUDY OF LiBOB/LiTFSI ELECTROLYTE SALT IN THE ALL-SOLID-STATE LITHIUM-ION BATTERY

PERFORMANCE STUDY OF LiBOB/LiTFSI ELECTROLYTE SALT IN THE ALL-SOLIDSTATE LITHIUM-ION BATTERY. Solid polymer electrolyte is developed mainly to provide safer lithiumion battery upon high temperature operation. In this research, we employ LiBOB and LiTFSI electrolyte salt in various concentration to replace commercially used LiPF6 salt. Solution cast method was performed to produce polymer electrolyte membrane. PVdF-HFP was chosen as polymer matrix due to high dielectric constant, and compatibility to wide array of electrode materials as well as electrolyte salts. Higher amount of electrolyte salts contributes to thicker membrane and hence higher current output of the lithium-ion battery half-cells. SEM, FT-IR spectroscopy, and cyclic voltammetry measurement was conducted to evaluate li-ion battery cell performance. Between the two electrolyte salts used in this experiment, LiTFSI salt exhibited better performance compared to LiBOB.

Gas evolution in commercial Li-ion battery cells measured by on-line mass spectrometry – Effects of C-rate and cell voltage

Gas evolution in lithium ion batteries (LIB) caused by degradation of the battery cell components, is not only detrimental to cell performance, it is also a major safety risk. Understanding the connection between cell usage and gas evolution at different states of health of the battery is of utmost importance for the improvement of cell components as well as user protocols for LIBs. In this work, an electrochemical mass spectrometric in-operando cell house, capable of hosting a cylindrical 18650 cell, was developed and used to study the gas evolution at increasing cycle C-rates (from C/20 to 4C) between 2.6 V and 4.2 V and during stepwise increased/decreased cell voltages ranging from 2.2 V to 4.4 V. The cell under study was a commercial 1.5 Ah NMC-LMO/Graphite cell, pierced inside an Ar-filled glove box and mounted to the gas-tight cell house before being connected to the On-Line Electrochemical Mass Spectrometer (OEMS). The results show that the large capacity fade observed at high C-rate is associated to major evolution of ethylene gas. The voltage step experiments revealed that CO2 is the main gas evolving at high voltages (>4.15 V) and H2 at low (<2.8 V). Despite significant gas evolution at these extreme voltages, the cell capacity remained stable.

Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS)

Thanks to their electrochemical structure, batteries are the elements that can store electrical energy and spend on a load when the electrical energy they store is needed. Today, with the widespread use of electrically powered mobile devices, rechargeable batteries have become widespread and battery technologies have developed. With the idea that the latest technology systems and electric vehicles will become widespread in the future, the studies on batteries are increasing day by day. In this study, charge state estimation of Li-ion battery cell used to provide power in many applications was realized by using adaptive neural fuzzy inference system (ANFIS). A Li-ion battery was discharged using variable electrical loads with a battery discharge circuit modeled on MATLAB Simulink and current, voltage, temperature and current power parameters of the battery were selected as input variables. Battery parameters and charge status data obtained from discharge tests using different electrical loads on MATLAB Simulink were used as training and test parameters of neural network. Using the MATLAB ANFIS toolbox, the system was trained with 80% of the battery parameters obtained in the battery discharge experiments and with 20% as testing data, the success performance was interpreted by applying the adaptive neural fuzzy inference system.

A Collaborative Gaussian Process Regression Model for Transfer Learning of Capacity Trends Between Li-Ion Battery Cells

A novel method is proposed for forecasting the capacity of lithium-ion battery cells. The method uses a Gaussian Process Regression model, a machine learning framework. Besides the high prediction accuracy and robustness the proposed method possesses, the method offers other advantages, namely, it provides uncertainty information, and it has the capability to cross-correlate capacity trends between different battery cells. These two merits make the proposed method a very reliable and practical solution for applications that use battery cell packs with a large number of interconnected battery cells. The proposed method is derived, verified, and compared to benchmark methods on three experimental lithium-ion battery cell datasets. The results show the effectiveness of the proposed method.

Real-Time Estimation of Model Parameters and State-of-Charge of Li-Ion Batteries in Electric Vehicles Using a New Mixed Estimation Model

A precise estimation of the state of charge (SoC) of the lithium-ion battery is crucial for reducing range-anxiety and improving the performance of the electric vehicle (EV) battery management system. An accurate estimation of the SoC, however, has remained elusive due to the complex and nonlinear behavior of the battery. In this article, a new mixed estimation model (MEM) for the battery parameters and the SoC estimation is proposed, where the route is specified before the travel. The new MEM uses a combination of a battery power-based method (BPBM), a combined model, and a partial adaptive forgetting factor recursive least-square (PAFF-RLS) SoC calibration algorithm to make use of the best characteristics of each model to determine a better and more accurate SoC estimation. The partial adaptive forgetting factors solves the issue of the different rate changes in the battery parameters and reduces the complexity of the algorithm compared to the fully adaptive recursive models. The BPBM allows various traveling factors to be included in the model, such as the environmental conditions, the effect of auxiliary loads, and the traffic congestion. To verify the validity of the PAFF-RLS algorithm, two laboratory tests using real-time driving cycles have been conducted on a 2012 Nissan Leaf 31.1 Ah Manganese-oxide Li-ion battery cell. The effectiveness of the MEM model has been demonstrated by driving the Nissan Leaf along two selected routes in Australia. The results demonstrate the great accuracy of the proposed method for the SoC estimation, when compared with those from the previous models.

Application-oriented modeling and optimization of tailored Li-ion batteries using the concept of Diffusion Limited C-rate

To increase the user acceptance and to push electric mobility towards mass suitability, the energy and power density of Li-ion batteries for electric vehicles are among the most crucial features to be improved. The two major approaches to increase the energy density are the development of improved active materials and favorable cell designs. However, the identification of an optimal cell design is a sophisticated challenge due to the large number of interdependent factors influencing the different performance parameters. In the present study, a straightforward model based on the concept of diffusion-limited C-rate is proposed to optimize the energy density of Li-ion battery cells with specified rate performance. The model is introduced and the underlying assumptions are verified by comprehensive experimental investigations. The model is used to identify optimal design parameters of anode and cathode regarding maximum volumetric and gravimetric energy for specified rate performance. A sensitivity analysis is carried out to quantify optimization potentials of cell components and their properties. The results are discussed regarding promising improvement strategies and the practical limits of Li-ion batteries.

Operando investigation of the solid electrolyte interphase mechanical and transport properties formed from vinylene carbonate and fluoroethylene carbonate

The electrolyte additives vinylene carbonate (VC) and fluoroethylene carbonate (FEC) are well known for increasing the lifetime of a Li-ion battery cell by supporting the formation of an effective solid electrolyte interphase (SEI) at the anode. In this study combined simultaneous electrochemical impedance spectroscopy (EIS) and operando electrochemical quartz crystal microbalance with dissipation monitoring (EQCM-D) are employed together with in situ gas analysis (OEMS) to study the influence of VC and FEC on the passivation process and the interphase properties at carbon-based anodes. In small quantities both additives reduce the initial interphase mass loading by 30–50%, but only VC also effectively prevents continuous side reactions and improves anode passivation significantly. VC and FEC are both reduced at potentials above 1 V vs. Li+/Li in the first cycle and change the SEI composition which causes an increase of the SEI shear storage modulus by over one order of magnitude in both cases. As a consequence, the ion diffusion coefficient and conductivity in the interphase is also significantly affected. While small quantities of VC in the initial electrolyte increase the SEI conductivity, FEC decomposition products hinder charge transport through the SEI and thus increase overall anode impedance significantly.

Dual Frequency Hierarchical Modular Multilayer Battery Balancer Architecture

This article presents a dual frequency hierarchical modular multilayer balancer (MMB) architecture capable of performing electrochemical impedance spectroscopy (EIS) and self-heating for battery systems. The MMB comprises two layers of balancing circuits: a cell-level balancer operates at a few MHz with miniaturized size; and a string-level balancer operates at a few hundred kHz to achieve high efficiency and rapid balancing. By reusing the balancer circuitry, the cell-level balancer can perform EIS, and the string-level balancer can perform battery self-heating. The key contributions of this article include: first, the circuit topology and multi-input–multi-output (MIMO) power flow control of the dual frequency hierarchical balancer; second, a miniaturized common-mode (CM) Class-D based 4-port cell-level balancer for wide bandwidth EIS; and third, a high efficiency multiactive-bridge (MAB) based 12-port string-level balancer for self-heating. A MMB prototype with a 12-port 200 kHz string-level balancer and four 4-port 13.56 MHz cell-level balancers is built and tested with a battery string comprising sixteen Li-ion battery cells. The MMB is capable of performing EIS up to 100 kHz and self-heating across a wide frequency range (100 Hz–18 kHz). The 100-W 12-port string-level balancer achieves 93% peak efficiency. The 30-W 4-port cell-level balancer achieves 74% peak efficiency. Experimental results validated the performance and functionality of the MMB system.

Low-Complexity Fast Charging Strategies Based on Explicit Reference Governors for Li-Ion Battery Cells

This article proposes and compares a new family of low-complexity control schemes for the fast charge of lithium-ion (Li-ion) battery cells accounting for degradation constraints. These schemes are based on a two-level architecture, where a low-level linear quadratic regulator (LQR) ensures stability and fast tracking of the applied reference, while an outer control layer, based on an explicit reference governor (ERG), enforces constraints satisfaction by manipulating the applied reference of the lower level. The ERG is based on the construction of a suitable Lyapunov level set contained inside of linear constraints. The main challenge to build a performing ERG for the fast charge of Li-ion batteries is how to choose a convenient Lyapunov function for nonconvex constraints arising from the electrochemical model of the battery. This article proposes and compares four different approaches to obtain performing Lyapunov functions for a concave constraint evaluating the impact on the charging time of a Li-ion battery and on the required computational time. Experimental validations on commercial lithium-cobalt oxide (LCO) battery cells (Turnigy nano-tech 160 mAh) show a tradeoff between the four methods computational time and the charging time.

Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications

Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.

Elimination of Fluorination: The Influence of Fluorine-Free Electrolytes on the Performance of LiNi1/3Mn1/3Co1/3O2/Silicon-Graphite Li-Ion Battery Cells.

In the quest for environmentally friendly and safe batteries, moving from fluorinated electrolytes that are toxic and release corrosive compounds, such as HF, is a necessary step. Here, the effects of electrolyte fluorination are investigated for full cells combining silicon–graphite composite electrodes with LiNi1/3Mn1/3Co1/3O2 (NMC111) cathodes, a viable cell chemistry for a range of potential battery applications, by means of electrochemical testing and postmortem surface analysis. A fluorine-free electrolyte based on lithium bis(oxalato)borate (LiBOB) and vinylene carbonate (VC) is able to provide higher discharge capacity (147 mAh gNMC–1) and longer cycle life at C/10 (84.4% capacity retention after 200 cycles) than a cell with a highly fluorinated electrolyte containing LiPF6, fluoroethylene carbonate (FEC) and VC. The cell with the fluorine-free electrolyte is able to form a stable solid electrolyte interphase (SEI) layer, has low overpotential, and shows a slow increase in cell resistance that leads to improved electrochemical performance. Although the power capability is limiting the performance of the fluorine-free electrolyte due to higher interfacial resistance, it is still able to provide long cycle life at C/2 and outperforms the highly fluorinated electrolyte at 40 °C. X-ray photoelectron spectroscopy (XPS) results showed a F-rich SEI with the highly fluorinated electrolyte, while the fluorine-free electrolyte formed an O-rich SEI. Although their composition is different, the electrochemical results show that both the highly fluorinated and fluorine-free electrolytes are able to stabilize the silicon-based anode and support stable cycling in full cells. While these results demonstrate the possibility to use a nonfluorinated electrolyte in high-energy-density full cells, they also address new challenges toward environmentally friendly and nontoxic electrolytes.

Broadband Impedance Measurement of Lithium-Ion Battery in the Presence of Nonlinear Distortions

The impedance of a Lithium-ion (Li-ion) battery has been shown to be a valuable tool in evaluating the battery characteristics such as the state-of-charge (SOC) and state-of-health (SOH). Recent studies have shown impedance-measurement methods based on broadband pseudo-random sequences (PRS) and Fourier techniques. The methods can be efficiently applied in real-time applications where the conventional electrochemical-impedance spectroscopy (EIS) is not well suited to measure the impedance. The techniques based on the PRS are, however, strongly affected by the battery nonlinearities. This paper presents the use of a direct-synthesis ternary (DST) signal to minimize the effect caused by the nonlinearities. In such a signal, the second- and third-order harmonics are suppressed from the signal energy spectrum. As a result, the effect of the second- and third-order nonlinearities are suppressed from the impedance measurements. The impedance measurements are carried out for a nickel manganese cobalt Li-ion battery cell. The performance of the method is compared to the conventional EIS, as well as to other PRS signals which are more prone to battery nonlinearities. The Kronig–Kramers (K–K) transformation test is used to validate the uniqueness of the measured impedance spectra. It is shown that the measurement method based on the DST produces highly accurate impedance measurements under nonlinear distortions of the battery. The method shows a good K–K test behavior indicating that the measured impedance complies well to a linearized equivalent circuit model that can be used for the SOC and SOH estimation of the battery. Due to the good performance, low measurement time, and simplicity of the DST, the method is well suited for practical battery applications.

Interactions and Transport in Highly Concentrated LiTFSI-based Electrolytes.

To elucidate what properties control and practically limit ion transport in highly concentrated electrolytes (HCEs), the viscosity, ionic conductivity, ionicity, and transport numbers were studied for nine model electrolytes and connected to the rate capability in Li-ion battery (LIB) cells. The electrolytes employed the LiTFSI salt in three molar ratio concentrations; 1 : 2, 1 : 4, and 1 : 16 (LiTFSI:X) vs. solvents (X) with different permittivities; tert-butyl methyl ether (MTBE), tetrahydrofuran (THF) and propylene carbonate (PC). While the low polarity MTBE creates liquid electrolytes, ion-pairing limits the ionic conductivity despite extremely low viscosities. For the less concentrated 1 : 16 LiTFSI:MTBE and 1 : 16 LiTFSI:THF electrolytes the ionic diffusivities decrease with increased temperature, a sign of aggregation, but still their ionic conductivities and LIB performance increase. In general, the low ionic conductivity and high viscosity both limit the use of HCEs in LIBs, and no compensating mechanism seems to be present.

Sensitive magnetometry reveals inhomogeneities in charge storage and weak transient internal currents in Li-ion cells

The ever-increasing demand for high-capacity rechargeable batteries highlights the need for sensitive and accurate diagnostic technology for determining the state of a cell, for identifying and localizing defects, and for sensing capacity loss mechanisms. Here, we leverage atomic magnetometry to map the weak induced magnetic fields around Li-ion battery cells in a magnetically shielded environment. The ability to rapidly measure cells nondestructively allows testing even commercial cells in their actual operating conditions, as a function of state of charge. These measurements provide maps of the magnetic susceptibility of the cell, which follow trends characteristic for the battery materials under study upon discharge. In particular, hot spots of charge storage are identified. In addition, the measurements reveal the capability to measure transient internal current effects, at a level of μA, which are shown to be dependent upon the state of charge. These effects highlight noncontact battery characterization opportunities. The diagnostic power of this technique could be used for the assessment of cells in research, quality control, or during operation, and could help uncover details of charge storage and failure processes in cells.

Propensity to self-heating ignition of open-circuit pouch lithium-ion battery pile on a hot boundary

The fire safety issue of Lithium-ion (Li-ion) batteries is an important obstacle for its market growth and applications. Although the open-circuit condition (e.g. storage, transport and disposal) accounts for the major part of battery lifespan, little research has investigated its self-ignition hazard during non-operating periods. In this work, we experimentally study the self-heating behavior of piled pouch Li-ion battery cells through the classical hot-plate experiments. Results show that the self-ignition of battery pile occurs under a hot plate temperature ranging from 199 °C to 265 °C, depending on the number of cells and environmental cooling. Thermal runaway always first occurs to the cell next to the hot plate and then propagates to upper cells. This critical temperature is increased by 20 °C under a good environmental cooling condition whereas it is reduced by 40 °C as the state of charge increases from 30% to 80%. Moreover, the critical plate temperature for self-ignition increases slightly with the height of battery pile, which is opposite to both hot-plate experiments of hydrocarbon materials and the oven experiments of battery. Therefore, the classical self-ignition theory may not be applicable for Li-ion batteries next to a hot boundary. This research reveals new self-ignition phenomena and helps understand the fire safety of Li-ion batteries in storage and transport.

Comparing Different Thermal Runway Triggers for Automotive Lithium-Ion Batteries

It is of crucial importance to guarantee safety of enhanced Lithium-ion batteries (LIB) in electric vehicles and consumer electronic products. Failure cases of LIB causing high temperatures and undesirable chemical reactions which can result in exothermic reactions and following thermal runaway (TR) have to be avoided reliably. For certain potential failure cases of batteries, toxic (CO, HF...) and flammable gases (CO, CH4, C2H4...)1,2 and breathable particles are ejected.In order to understand the LIB failing behavior and to prevent failures and their consequences, different LIB safety tests, also named abuse tests, have been developed. Popular examples are: Thermal runway triggered by overtemperature, overcharge, over-discharge, external and internal short circuit, hot spots, crush or the presence of foreign objects, like nail penetration3. The tests are carried out and documented in literature on single cell, module or even battery pack level.This scientific contribution shows the setup and the results of different TR triggers on single cells in a custom-made thermal runaway reactor at VIRTUAL VEHICLE. The cell type is a state-of-the-art automotive pouch cell. Chosen triggers focus on for example:• overtemperature• overcharge• nail penetrationAfter the new or aged cell is positioned inside the thermal runway reactor and the measurement equipment is fixed, the reactor is closed and flushed with nitrogen. Each cell is cycled to 100% SOC. If the setup is prepared, different triggers are tested for the single cell. The overtemperature experiment is designed to increase the cell surface temperature with ~ 2°C/min and the overcharge experiment is conducted with 1 C.The results of differently triggered TR are compared in three main categories: Temperature behavior of the cell, amount of produced vent gas and vent gas composition.Inside the reactor, the temperature behavior of the cell is recorded with thermocouple measurements on both sides of the cell surface, the cell tabs, close to the venting positions of the cell and inside the TR reactor. With pressure sensors inside the reactor, the pressure increase due to gas generation is recorded. With the ideal gas law, the amount of produced not condensed vent gas can be calculated. The vent gas composition is measured with Fourier Transform Infrared (FTIR) spectrometer and gas chromatograph in parallel.In the presentation the high impact of overcharge experiments on produced gas amount and the increased toxicity of the gas components will be shown. With increasing energy density of current state-of-the-art nickel manganese cobalt oxide (NMC) LIBs’ significantly higher impact of failing batteries can be observed in temperature behavior, gas production and gas toxicity. To conclude the presentation an estimated trend of the main categories - maximum reached cell surface temperature, amount of produced vent gas and amount toxic compounds in the vent gas - will be given.1. Golubkov, A. W. et al. Thermal runaway of commercial 18650 Li-ion batteries with LFP and NCA cathodes – impact of state of charge and overcharge. RSC Adv. 5, (2015).2. Ribière, P. et al. Investigation on the fire-induced hazards of Li-ion battery cells by fire calorimetry. Energy Environ. Sci. 5, 5271–5280 (2012).3. Coman, P. T., Rayman, S. & White, R. E. A lumped model of venting during thermal runaway in a cylindrical Lithium Cobalt Oxide lithium-ion cell. J. Power Sources 307, 56–62 (2016).