Differential Voltage Research Articles

Ageing and Post-Mortem Study of LNMO-Based Lithium Ion Battery Pouch Cells

Lithium ion batteries are nowadays widely employed in a variety of applications from consumer electronics to electric vehicles. Due to the rising demand for batteries, more affordable and sustainable batteries are needed that exhibit at the same time high energy densities, high power capabilities, long cycle life, and increased safety. One concept to meet these requirements is to develop cobalt-free cathode materials of which the high-voltage spinel LNMO (LiNi0.5Mn1.5O4) is a promising material due to its high energy density and high operating voltage of 4.7 V. However, the high operating voltage has also its drawbacks. Commonly used carbonate-based electrolytes oxidize at high voltages, leading to the continuous formation of a cathode-electrolyte interface (CEI). Additionally, LNMO is prone to transition metal dissolution which not only leads to a reduced stability of the cathode active material but due to migration and deposition of the transition metals on the anode surface also to an altered solid electrolyte interface (SEI) formation and significant impedance rise of the anode.1 Both ageing mechanisms provoke increased lithium loss and high resistances and thus a poor cycling performance.2, 3 In the Horizon 2020 LC-BAT5 project HYDRA, LNMO-based prototype pouch cells are developed and built. Herein, we want to present the results from the comprehensive analysis of their performance and cycling behavior. The influence of upper cut-off voltage, charge and discharge current rate as well as temperature on the degradation are thoroughly investigated by electrochemical methods such as differential voltage analysis and impedance spectroscopy. After cycling, selected cells are opened under argon atmosphere followed by electrochemical characterization as well as physical analysis such as SEM-EDX and XPS in order to get further insights into the underlying ageing mechanisms. We thereby reveal the main degradation mechanisms as a function of the cycling conditions and derive solutions on how to increase the cycle life.1. C. Zhan, T. Wu, J. Lu and K. Amine, Energy Environ. Sci.,11 (2), 243-257 (2018).2. J. Ma, P. Hu, G. Cui and L. Chen, Chem. Mater.,28 (11), 3578-3606 (2016).3. W. Li, Y.-G. Cho, W. Yao, Y. Li, A. Cronk, R. Shimizu, M. A. Schroeder, Y. Fu, F. Zou, V. Battaglia, A. Manthiram, M. Zhang and Y. S. Meng, J. Power Sources,473, (2020).Pseudo-OCV (a) and differential voltage analysis curves (b) of LNMO-graphite pouch cell cycled with 0.3C CCCV charge and 0.1C discharge at 25°C Figure 1

Novel, in situ, electrochemical methodology for determining lead-acid battery positive active material decay during life cycle testing

Understanding the thermodynamic and kinetic aspects of lead-acid battery structural and electrochemical changes during cycling through in-situ techniques is of the utmost importance for increasing the performance and life of these batteries in real-world applications. Here, we describe the application of Incremental Capacity Analysis and Differential Voltage techniques, which are used frequently in the field of lithium-ion batteries, to lead-acid battery chemistries for the first time. These analyses permit structural data to be retrieved from simple electrical tests that infers directly the state of health of the positive active material. We present evidence from full-scale 12 V batteries to demonstrate the techniques and prove their utility to the space. Evaluation of capacity and cycle life testing supports a new theory of Positive Active Material utilization, the Single-Entity/Dual Behaviour-Hypothesis, which is described within our work.

Influence of state of charge window on the degradation of Tesla lithium-ion battery cells

The Tesla Model 3 is currently one of the most popular electric vehicle (EV) and was the best selling EV in 2020. In this article, performance and degradation of 21700 cylindrical cells, taken from a new vehicle, were studied by cycling within 10% State of charge (SOC) windows. Cells tested in either very high and very low SOC windows show faster degradation than at moderate SOC. In particular, the shortest service life was for cells cycled below 25% SOC. The ageing mechanisms of the cells cycled in these most extreme windows have been monitored by non-destructive electrochemical methods including analyses of differential voltage, incremental capacity, and voltage hysteresis. The combination of loss of lithium inventory (LLI) accelerated in early cycling by SiOx utilization, paired with loss of active material (LAM) of SiOx are responsible for the most rapid ageing, which is observed in the cells cycled in the 5%–15% SOC window. Calendar ageing, however, is not accelerated by storage at low SOC. The results from this study offer an understanding of the distinct, SOC-dependent ageing patterns observed in the cells. This understanding of the ageing mechanisms in different cycling and storage conditions can be used to recommend improved customer usage patterns and substantially extend the lifetime of lithium-ion batteries in operation.

A Low-Power 30MHz ,6th Order Band-pass Differential Gm-C Filter on Chip Using Floating Current Source

A 30MHz center frequency, 6th order Butterworth and elliptic band-pass filter using a leap-frog Gm-C structure in this work. A continuous time differential voltage mode Gm-C biquad and its adjoin voltage - mode version are described, employing FCS (Floating Current Source) circuits as building blocks. The improved current source structure is simple and includes fewer transistors. This provides an effective use of the chip area and brings simplicity to the design of circuits. The proposed filter structure does not contain the resistor which is very important for integration. All capacitors in proposed filter are grounded which reduces the parasitic effects. The proposed filter has been successfully implemented by TSMC 0.18μm CMOS process. Simulation results are given to confirm the theoretical analysis.

Analysis and Simulation Test of Electromagnetic Disturbance Mode Conversion in Secondary Circuit of Substation

Under ideal conditions, the electromagnetic interference experienced by the secondary circuit is manifested as a common mode. However, due to circuit imbalance, common mode disturbance is converted into differential mode disturbance, thereby presenting a danger to the normal functioning of secondary equipment. The investigation measured the distribution ratio of common mode voltages and differential mode voltages at the ports of secondary equipment during switching operations. A computational circuit model of the secondary circuit was established by using multi-conductor transmission line theory. The mechanisms and influencing factors of transformation from common mode to differential mode were analyzed, and a simulation test was carried out in a substation to explore the conversion law under impedance imbalance. The results showed that the differential mode voltage of the secondary equipment port was greater than the common mode voltage when the circuit breaker was in operation. Common-differential mode conversion in the secondary loop was predominantly caused by an imbalance in circuit structure and extraneous parameters. Differential mode disturbance generated by switch field side imbalance had a greater impact than that generated by protection chamber side imbalance. As the degree of imbalance increased, the differential mode voltage also increased.

Lithium-Ion Cells in Automotive Applications: Tesla 4680 Cylindrical Cell Teardown and Characterization

Battery research depends upon up-to-date information on the cell characteristics found in current electric vehicles, which is exacerbated by the deployment of novel formats and architectures. This necessitates open access to cell characterization data. Therefore, this study examines the architecture and performance of first-generation Tesla 4680 cells in detail, both by electrical characterization and thermal investigations at cell-level and by disassembling one cell down to the material level including a three-electrode analysis. The cell teardown reveals the complex cell architecture with electrode disks of hexagonal symmetry as well as an electrode winding consisting of a double-sided and homogeneously coated cathode and anode, two separators and no mandrel. A solvent-free anode fabrication and coating process can be derived. Energy-dispersive X-ray spectroscopy as well as differential voltage, incremental capacity and three-electrode analysis confirm a NMC811 cathode and a pure graphite anode without silicon. On cell-level, energy densities of 622.4 Wh/L and 232.5 Wh/kg were determined while characteristic state-of-charge dependencies regarding resistance and impedance behavior are revealed using hybrid pulse power characterization and electrochemical impedance spectroscopy. A comparatively high surface temperature of ∼70 °C is observed when charging at 2C without active cooling. All measurement data of this characterization study are provided as open source.

Differential Reactor Voltage Based Fault Detection and Classification for Smart DC Microgrid

The primary challenges in the implementation of differential protection techniques are Time Synchronization Error (TSE) due to communication delay and low sensitivity towards High Resistance Faults (HRFs). In this paper, a new technique utilizing the difference in voltage measured across the external reactors connected at opposite ends of the cable is proposed for fault detection and classification of HRFs in islanded and grid connected mode of operation of DC microgrid. Further, to overcome the challenges associated with TSE, which causes differential schemes to mal-operate, the proposed technique determines reactor voltage polarity at opposite ends of the cable to distinguish between internal and external faults. The proposed technique is tested for different types of internal faults and system transients such as external faults, load switching, generation uncertainties etc. to demonstrate sensitivity and accuracy of the proposed technique. Finally, a comparative analysis of the proposed technique is performed with the schemes reported in the literature, which confirms the fast fault detection, high sensitivity for internal HRFs, selectivity and stability of the proposed technique for different operating conditions.

Development of diagnostic instrumentations for fuel cells based on consumer electronics

The decarbonization process is pushing the energy sector into a transition towards clean energy vectors. In the hard-to-abate sectors, such as heavy-duty transport and industry, hydrogen can act as an energy carrier and a sector coupler. Key devices for hydrogen exploitation are fuel cells. Diagnostic is a crucial element for safety and efficiency during operation. This work regards the development process – from the conception to the validation and use – of an acquisition system made of consumer electronic components. By measuring differential voltage at high frequency, it enables to perform Electrochemical Impedance Spectroscopy (EIS). The system consists of an Arduino board running a self-developed circuit composed of an operational amplifier, an analog-to-digital converter, and a buffer memory. The system is designed to be expanded with multiple synchronized modules to monitor several cells at once. The module can be applied to a single cell or a group of cells (e.g., a stack) by tuning the operational amplifier. A dedicated software has also been developed, involving assembly language to achieve the required speed performance. The circuit has been validated using a function generator to apply sinusoids with frequencies between 100 Hz and 10 kHz and amplitudes of 10-500 mV (reflecting the EIS requirements on a single cell). An oscilloscope is used to double-check the generated signal. The results proved that the system features errors below 3% on amplitude and below 0.3% on frequency. Finally, the developed system has been tested against a commercial device performing EIS measurements. The obtained impedance values generally differ by less than 3% in the range of interest, while a few specific frequencies are affected by external disturbances.

A new data-driven diagnostic technique for in-situ capacity prediction of lithium-ion batteries

Lithium-ion battery (LIB) charging behavior is of equal importance as discharging with abundant information for the battery management system to determine the state of charge (SOC), state of health (SOH), and state of safety (SOS). However, to the best of the authors' knowledge, little work can be found regarding the fast and accurate prediction of the charging behaviors of LIBs. To fill in this gap, in this work, a data-driven diagnostic technique, long short-term memory in situ capacity prediction (LSTM-ICP), is proposed to predict battery capacity through short-term voltage measurements under constant current charging. Unlike the technique in the previous work, LSTM-ICP does not rely on the interpretation of voltage-time data as incremental capacity (IC) or differential voltage (DV) curves. Thus, the need for differentiating voltage-time data (amplifying the process of measuring noise) and the voltage measurement range including the peak of the IC/DV curve can be ignored and thus significantly shorten the prediction process. The optimization method of the mini-batch gradient descent may reduce the computational complexity and also enhance the randomness of prediction. Results highlight the performance of the proposed diagnostic technique, LSTM-ICP is applied to two datasets, which are composed of four and eight cells. In each case, the evaluation results of different performance indicators in a certain voltage range show that the prediction model has good accuracy and effectiveness.

Influence of atmospheric pressure on the aging mechanism of LiCoO2/graphite cells

With the application of lithium-ion battery (LIB) in the field of electric aircraft, the aging behavior and mechanism of LIB under low-pressure environment have become an important topic. In this paper, the aging characteristics of LiCoO2/graphite cells under low pressure are investigated. The results show that the decrease of pressure leads to the degradation of cell capacity. With the pressure decreases from 96 kPa to 30 kPa, the capacity loss rate of the cell increases from 0.5 % to 17.4 %. Coulomb efficiency and differential voltage analysis indicate that low pressure accelerates the loss of lithium inventory. The X-ray computed tomography shows that the cell cycled under low pressure exhibits more significant deformation. The disassembly photos demonstrate that the side reactions of the cell are more obvious under low pressure. The scanning electron microscopy and elemental analysis results confirm that the thickness of solid electrolyte interface film increases with the decrease of pressure. These phenomena indicate that the intensification of battery deformation and internal side reactions under low pressure leads to a decrease in the electrochemical kinetics and long-term cycling ability of the battery.

OptoDyCE-plate as an affordable high throughput imager for all optical cardiac electrophysiology

We present a simple low-cost system for comprehensive functional characterization of cardiac function under spontaneous and paced conditions, in standard 96 and 384-well plates. This full-plate actuator/imager, OptoDyCE-plate, uses optogenetic stimulation and optical readouts of voltage and calcium (parallel recordings from up to 100 wells in 384-well plates are demonstrated). The system is validated with syncytia of human induced pluripotent stem cell derived cardiomyocytes, iPSC-CMs, grown as monolayers, or in quasi-3D isotropic and anisotropic constructs using electrospun matrices, in 96 and 384-well format. Genetic modifications, e.g. interference CRISPR (CRISPRi), and nine compounds of acute and chronic action were tested, including five histone deacetylase inhibitors (HDACis). Their effects on voltage and calcium were compared across growth conditions and pacing rates. We also demonstrated optogenetic point pacing via cell spheroids to study conduction in 96-well format, as well as temporal multiplexing to register voltage and calcium simultaneously on a single camera. Opto-DyCE-plate showed excellent performance even in the small samples in 384-well plates. Anisotropic structured constructs may provide some benefits in drug testing, although drug responses were consistent across tested configurations. Differential voltage vs. calcium responses were seen for some drugs, especially for non-traditional modulators of cardiac function, e.g. HDACi, and pacing rate was a powerful modulator of drug response, highlighting the need for comprehensive multiparametric assessment, as offered by OptoDyCE-plate. Increasing throughput and speed and reducing cost of screening can help stratify potential compounds early in the drug development process and accelerate the development of safer drugs.

Mixing Behavior and Electrical Conductivity of Diisopropyl Amine-Water Surfactantless Emulsions: Implications for the Electrokinetic Purification of Water

The water pollutant diisopropylamine (DIPA) creates surfactantless emulsions in water. DIPA droplets bear a negative electrostatic charge, as demonstrated by electrophoretic measurements. Sodium salts (NaCl and Na2SO4) decrease their charge, leading to droplet coalescence and separation into bulk layers, depending on the salt and DIPA percentages. Attenuated total reflectance – Fourier transform infrared spectroscopy (ATR-FTIR) show that the DIPA concentration in the water rich phase is below 10wt% DIPA when adding 2wt% Na2SO4 (relative to the mixture) to mixtures of 20wt%, 40wt% and 50wt% DIPA (relative to water). The same occurs when adding 2% NaCl to mixtures of 30wt%, 50wt% and 70wt% DIPA (relative to water). DIPA-water mixtures are electrically conductive and can be separated by subjecting them to an electric field (electrokinetic separation). Without salts, the concentration of DIPA in 30wt% DIPA could be reduced by ≈20wt% after 60mins treatment using a differential voltage = 12V. NaCl (0.25wt% relative to water) improved efficiency. After 15mins, the percent decrease in DIPA was ≈50wt%. Electrokinetic treatment targets exclusively contaminants dispersed in water. DIPA sorbs onto clay, alumina and iron oxide minerals, whereas it does not sorb onto gypsum and limestone. Therefore, the in situ electrokinetic separation of DIPA can be most successfully applied in aquifers where the dominant minerals are gypsum and limestone.

State of Health Assessment of Spent Lithium–Ion Batteries Based on Voltage Integral during the Constant Current Charge

Lithium–ion batteries (LIBs) are used in many personal electronic devices (PED) and energy-demanding applications such as electric vehicles. After their first use, rather than dispose of them for recycling, some may still have reasonable capacity and can be used in secondary applications. The current test methods to assess them are either slow, complex or expensive. The voltage integral during the constant current (CC) charge of the same model of LIBs strongly correlates with the state of health (SOH) and is faster than a full capacity check. Compared to the filtering requirement in the incremental capacity (IC) and differential voltage (DV) or the complex analysis in the electrochemical impedance spectrum (EIS), the voltage integral offers a simple integration method, just like the simple capacity Coulomb’s counter that is installed in many BMS for estimating the SOC of LIBs. By obtaining the voltage integral of a relatively new cell and an old cell of the same model with known SOH at a given ambient temperature and CC charge, the SOH of other similar cells can be easily estimated by finding their voltage integrals.

Modified Decoupled Sense Amplifier with Improved Sensing Speed for Low-Voltage Differential SRAM

A modified decoupled sense amplifier (MDSA) and modified decoupled sense amplifier with NMOS foot-switch is proposed for improved sensing in differential SRAM for low-voltage operation at the 22-nm technology node. The MDSA and MDSANF both offer notable improvements to read delay over conventional voltage and current sense amplifiers. At an operating voltage of 0.8 V, the MDSA exhibited a reduced delay of 28.6%, 41.79%, 37.74%, and 30.94% compared to modified clamped sense amplifier (MCSA), double tail sense amplifier (DTSA), modified hybrid sense amplifier (MHSA), and conventional latch-type sense amplifier (LSA), respectively. Similarly, the MDSANF demonstrated a delay reduction of 26.13%, 39.78%, 35.58%, and 28.55% over MCSA, DTSA, MHSA, and LSA, respectively. To validate the performance, the MDSA and MDSANF are evaluated using the variation in delay and power consumption across various supply voltages, process corners, input differential bit line voltage (ΔV BL ), bit line capacitance (C BL ), and the sizing of decoupling transistors. Monte Carlo simulations were conducted to analyse the impact of voltage threshold variations on transistor mismatch which leads to an increased occurrence of read failures and a decline in SRAM yield. The performance analysis of various voltage and current sense amplifiers is presented along with MDSA and MDSANF. Area consideration for selection of sensing scheme is important and as such layout of MDSA and MDSANF was performed conforming to the design rules and estimated area for MDSA is 0.297 μm 2 whereas MDSANF occupies 0.5192 μm 2 .

Wire bond contact defect identification in battery modules of electric vehicles using pulses and differential voltage analysis

Automotive battery packs for electromobility applications consist of a large number of interconnected battery cells. Different cell-to-busbar joining techniques are utilized, with cylindrical cells frequently being contacted using wire bonding. Failure of individual connections can occur due to strong vibrations during operation and improper stress, making detection by the battery management system a necessity. This study investigates the identification of an electrical wire bond failure in a state-of-the-art electric vehicle module of a Lucid Air with 10 series-connected and 30 parallel-connected cells (10s30p). Four individual cells were characterized extensively in order to generate a simulation model taking into account parameter scatter. The failure case under investigation was simulatively incorporated in one parallel circuit and subsequently replicated in experimental validation measurements at the module level. The results show that this defect can be detected using pulses of C/3 or higher currents at various states of charge. An even more robust detection is achieved using differential voltage analysis of constant current C/20 discharge voltage trajectories. This defect identification method does not require any additional measurement sensors beyond the voltage taps and sensors provided by the manufacturer – with one voltage sensor per parallel circuit – and can therefore be implemented during electric vehicle usage, e.g. at dedicated service checks. A discussion on the applicability and scalability as well as the limitations of the method is provided. All measurement data of the state-of-the-art Lucid battery system is available as open source alongside the article.

Investigation of the Influence of Silicon Oxide Content on Electrolyte Degradation, Gas Evolution, and Thickness Change in Silicon Oxide/Graphite Composite Anodes for Li-Ion Cells Using Operando Techniques

This research paper investigates the influence of varying silicon oxide (SiOx) content on the performance and aging of lithium-ion cells. In-depth investigations encompass charge and discharge curves, thickness changes, electrolyte degradation, gas evolution, and chemical analysis of cells with different silicon oxide proportions in the anode and their associated cathodes. The results show that a higher silicon oxide content in the anode increases the voltage hysteresis between charge and discharge. Moreover, the first-cycle efficiencies decrease with a higher silicon oxide content, attributed to irreversible LixSiy formation and the subsequent loss of active lithium from the cathode during formation. The anodes experience higher thickness changes with increased silicon oxide content, and peaks in differential voltage curves can be correlated with specific anode active materials and their thickness change. A gas analysis reveals conductive salt and electrolyte intermediates as well as silicon-containing gaseous fragments, indicating continuous electrolyte decomposition and silicon oxide aging, respectively. Additionally, a chemical analysis confirms increased silicon-derived products and electrolyte degradation on electrode surfaces. These findings underscore the importance of a holistic aging investigation and help understand the complex chemical changes in electrode materials for designing efficient and durable lithium-ion cells.

Data-Driven Models for Sub-Cycle Dynamic Response of Inverter-Based Resources Using WMU Measurements

Using real-world data from Waveform Measurement Units (WMUs), this paper proposes novel data-driven methods to model the dynamic response of inverter-based resource (IBR) to the high-frequency disturbances that occur in practice in power systems. WMUs are an emerging class of smart grid sensors. They can capture the fast sub-cycle dynamics in power systems, which are overlooked by phasor measurement units (PMUs). After extracting the differential voltage and current waveforms from the raw waveform data, we develop multiple methods that include data-driven model library construction and proper model selection. One class of methods is proposed in frequency domain, which is based on modal analysis. Another class of methods is proposed in time domain, which is based on regression analysis of time-series. Experimental results based on real-world WMU data demonstrate the of performance the proposed methods.

Comparative Testing of Li-Ion Battery Chemistries for Stationary Energy Storage

Li-ion batteries are the most widely deployed battery energy storage system (BESS) today but understanding the benefits and cost-effectiveness for a wide range of grid services needs to be fully validated to further expand the market. Hence, various Li-ion battery chemistries currently deployed must be evaluated and compared in terms of performance, lifecycle, economics, and safety under grid services using standardized testing protocols. In this work, commercially available cylindrical cells with four different chemistries from major Li-ion battery manufacturers are subjected to standardized tests developed by the U.S. Department of Energy Office of Electricity (DOE-OE) for frequency regulation, peak shaving, and electric vehicle drive cycles. The results of 15 months of continuous grid service tests on different chemistries are presented, analyzed, and compared in terms of capacity retention, resistance, open-circuit voltage (OCV), cyclic voltammetry (CV), incremental capacity (dQ/dV), differential voltage (dV/dQ), and AC impedance

Voltage Differential Analysis during Power Discharge Operation in Energy Storage Systems

Constant Power Discharge (CPD) is a lucrative operating mode for grid-tied ESS in many energy markets. The CPD mode corresponds to an increasing current drawn as the ESS discharges. The operation can be modeled with an aged anode and cathode open circuit potentials (OCPn/p+RRC) model that can let us identify electrode-level (eSOH) parameters and resistance growth even though we do not have slow discharge with Constant Current. This identification process from realistic ESS field data, namely constant power discharge, will enable continuous eSOH diagnostics and lead to real-time and operando quantification of loss of active material and loss of lithium inventory (LAM and LLI, respectively).In addition, the timing of when the cell groups' differential voltage peaks occur when the battery system is under constant power operations inform us about the imbalance among cell groups in a module of a battery system, as shown in the figure. Using the time separation among cell differential voltage peaks as a metric of cell imbalance can improve cell balancing algorithms that measure cell imbalance using maximum or minimum voltage, which can be directly affected by the power limits of the battery system.The efficacy of the proposed algorithms is evaluated for multi-cell modules consisting of NMC/graphite cells, operating as part of a large-scale grid-connected energy storage system. Ultimately, by enabling improved diagnostics of the state of health of individual cells in a battery system and improved cell balancing algorithms, this work will enhance the performance and safety of large-scale lithium-ion battery systems. Figure 1

Utilizing Bayesian Optimization to Facilitate Differential Voltage Analysis of Lithium Ion Batteries

Differential voltage analysis (DVA) is a non-destructive, in situ method for analyzing degradation in lithium ion (Li-ion) batteries, and can be used to identify major modes of performance degradation, such as loss of lithium inventory (LLI) and loss of active material (LAM). Using the cycling voltage derivative with respect to capacity of half cells and full cells, DVA can be used to estimate which mode is the main contributor to degradation. Analysis of the signature peaks in the half cell to the full cell can reveal the degradation mode of full cell. Shifts in the peak can indicate LLI, while intensification and narrowing of peaks can indicate LAM. Analyzing the peak changes after cycling allows quantitative determination of how much cell aging has occurred, and what mode is involved in the cell aging process. However, the process of analyzing peak changes manually is inefficient and time consuming. In this work, we utilize a Bayesian optimization approach to facilitate the process of fitting full cell DVA data with pristine half-cell data. The Bayesian optimization algorithm finds the best deformation of pristine half-cell data to fit full-cell data automatically and efficiently for multiple chemistries. The only manual procedures for each fitting are reading data files into the program and determining a coarse bound. The rest is automated and takes less than ten minutes for each fitting. The fitting accuracy is comparable to manual fitting and significantly less time consuming. This method facilitates battery aging analysis and can be generalized to different kinds of data sets as well.