Low Charge States Research Articles

The Operation Window of Lithium Iron Phosphate/Graphite Cells Affects their Lifetime

Lithium iron phosphate (LFP) battery cells are ubiquitous in electric vehicles and stationary energy storage because they are cheap and have a long lifetime. This work compares LFP/graphite pouch cells undergoing charge-discharge cycles over five state of charge (SOC) windows (0%–25%, 0%–60%, 0%–80%, 0%–100%, and 75%–100%). Cycling LFP cells across a lower average SOC results in less capacity fade than cycling across a higher average SOC, regardless of depth of discharge. The primary capacity fade mechanism is lithium inventory loss due to: lithiated graphite reactivity with electrolyte, which increases incrementally with SOC, and lithium alkoxide species causing iron dissolution and deposition on the negative electrode at high SOC which further accelerates lithium inventory loss. Our results show that even low voltage LFP systems (3.65 V) have a tradeoff between average SOC and lifetime. Operating LFP cells at lower average SOC can extend their lifetime substantially in both EV and grid storage applications.

Compositional Metrics of Fast and Slow Alfvénic Solar Wind Emerging from Coronal Holes and Their Boundaries

We seek to understand the composition and variability of fast solar wind (FSW) and slow Alfvénic solar wind emerging from coronal holes (CHs). We leverage an opportune conjunction between Solar Orbiter and Parker Solar Probe (PSP) during PSP Encounter 11 to include compositional diagnostics from the Solar Orbiter Heavy Ion Sensor as these variations provide crucial insights into the origin and nature of the solar wind. We use potential field source surface and magnetohydrodynamic models to connect the observed plasma at PSP and Solar Orbiter to its origin footpoint in the photosphere and compare these results with the in situ measurements. A very clear signature of a heliospheric current sheet crossing as evidenced by enhancements in low first ionization potential (FIP) elements, ion charge state ratios, proton density, low Alfvénicity, and polarity estimates validates the combination of modeling, data, and mapping. We identify two FSW streams emerging from small equatorial CHs with low ion charge state ratios, low FIP bias, high Alfvénicity, and low footpoint brightness, yet anomalously low alpha particle abundance for both streams. We identify high-Alfvénicity slow solar wind emerging from the overexpanded boundary of a CH having intermediate alpha abundance, high Alfvénicity, and dips in ion charge state ratios corresponding to CH boundaries. Through this comprehensive analysis, we highlight the power of multi-instrument conjunction studies in assessing the sources of the solar wind.

A grey-box model with neural ordinary differential equations for the slow voltage dynamics of lithium-ion batteries: Application to single-cell experiments

Lithium-ion batteries exhibit a complex, nonlinear and dynamic voltage behaviour. Modelling their slow dynamics is a challenge due to the multiple potential causes involved. We present here a neural equivalent circuit model for lithium-ion batteries including slow voltage dynamics. The model uses an equivalent circuit with voltage source, series resistor, and diffusion element. The series resistance is parameterized using neural networks. The diffusion element is based on a discretized form of Fickian diffusion, parameterized using a neural network and learnable parameters. It is flexible to represent not only Warburg behaviour, but also resistor-capacitor-type dynamics. Mathematically, the resulting model is given by a differential–algebraic equation system combining ordinary and neural differential equations. Therefore, the model combines concepts of both physical theory (white-box model) and artificial intelligence (black-box model) to a combined framework (grey-box model). We apply this approach to a lithium iron phosphate based lithium-ion battery cell. The experimental voltage behaviour during constant-current cycles as well as the dynamics during pulse tests are well reproduced by the model. Only at very high and very low states of charge the simulation significantly deviates from experiments, which might result from insufficient training data in these regions.

Ion Mobility-Mass Spectrometry and Collision-Induced Unfolding Rapidly Characterize the Structural Polydispersity and Stability of an Fc-Fusion Protein.

Fc-fusion proteins are an emerging class of protein therapeutics that combine the properties of biological ligands with the unique properties of the fragment crystallizable (Fc) domain of an immunoglobulin G (IgG). Due to their diverse higher-order structures (HOSs), Fc-fusion proteins remain challenging characterization targets within biopharmaceutical pipelines. While high-resolution biophysical tools are available for HOS characterization, they frequently demand extended time frames and substantial quantities of purified samples, rendering them impractical for swiftly screening candidate molecules. Herein, we describe the development of ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) workflows that aim to fill this technology gap, where we focus on probing the HOS of a model Fc-Interleukin-10 (Fc-IL-10) fusion protein engineered using flexible glycine-serine linkers. We evaluate the ability of these techniques to probe the flexibility of Fc-IL-10 in the absence of bulk solvent relative to other proteins of similar size, as well as localize structural changes of low charge state Fc-IL-10 ions to specific Fc and IL-10 unfolding events during CIU. We subsequently apply these tools to probe the local effects of glycine-serine linkers on the HOS and stability of IL-10 homodimer, which is the biologically active form of IL-10. Our data reveals that Fc-IL-10 produces significantly more structural transitions during CIU and broader IM profiles when compared to a wide range of model proteins, indicative of its exceptional structural dynamism. Furthermore, we use a combination of enzymatic approaches to annotate these intricate CIU data and localize specific transitions to the unfolding of domains within Fc-IL-10. Finally, we detect a strong positive, quadratic relationship between average linker mass and fusion protein stability, suggesting a cooperative influence between glycine-serine linkers and overall fusion protein stability. This is the first reported study on the use of IM-MS and CIU to characterize HOS of Fc-fusion proteins, illustrating the practical applicability of this approach.

Battery Monitoring and Protective System

Abstract: The growing demand for battery-powered devices and systems has led to an increased need for battery monitoring and protective systems. These systems play a critical role in ensuring the safe and reliable operation of battery-powered systems, such as electric vehicles, renewable energy systems, and mobile devices. This work emphasizes to monitor the state of charge (SOC) of the battery to ensure optimal performance and prevent premature failure. The battery is protected from damage due to overcharging, over-discharging, overheating, and short-circuiting. It also provides early warning of potential battery issues, such as low SOC or high temperature, so that corrective action can be taken to prevent damage. The charging and discharging of the battery is optimized to maximize its lifespan and efficiency. The proposed model facilitates remote monitoring and control of the battery using Arduino and BLYNK App accompanied by predictive maintenance and reduced downtime.

Charge/Discharge Simulation Models of LiFePO4 Cells in MATLAB/Simulink

Lithium (Li) cells find widespread applications, particularly in electric vehicles their dynamic characteristics are often represented through equivalent circuit models. In this study, two different second-order equivalent circuit models of LiFePO4 cells are modeled and simulated in MATLAB/Simulink. The first model exhibits capacity changes based on drawn current, while the second assumes constant capacity. The analysis of the simulations results focuses on key parameters such as State of Charge (SOC), Open Circuit Voltage (OCV), and terminal voltage (VT). Comparative evaluations between the first and second cell models utilize formulas derived from prior experimental cell studies. Specifically, a 0.0155% variance in SOC, a 0.00003% difference in OCV, and a 0.00003% distinction in VT were observed between the two models during discharge. A similar assessment during charging observed an error of 0.0447% in SOC, 0.00007% in OCV, and 0.00003% in VT. Furthermore, the discharge process in the first model demonstrates lower SOC, OCV, and VT values, contrasting with higher values during charging. Despite these variances, the study concludes that both models yield similar results, establishing them as viable references for equivalent circuit representations of Lithium cells.

Thermodynamic and kinetic degradation of LTO batteries: Impact of different SOC intervals and discharge voltages in electric train applications

Lithium-titanate-oxide (LTO) based lithium-ion batteries show promise for longer lifespan, higher power capability, and lower life cycle cost for energy storage and electric transportation applications than graphite-based counterparts. However, the degradation mechanisms of LTO-based cells in the high and low state-of-charge (SOC) intervals and different discharge cut-off voltages are not clearly investigated. In this study, the application-related lifetime performance of high-power Li4Ti5O12/LiCoO2 batteries is investigated at five independent SOC intervals with 20 % depth-of-discharge (DOD) and three discharge cut-off voltages. Our results show that degradation increases significantly when the batteries are cycled within lower SOC intervals or with lower cut-off voltages. Additionally, thermodynamic degradation is more significant when cycled at 20 % DOD, while kinetic degradation dominates at 100 % DOD. For thermodynamic degradation, the determining degradation mode is shown to be the loss of active material in the negative electrode, while the active material loss at the cathode has a greater impact on the equilibrium voltage curve. The kinetic degradation is mainly due to the slower charge transfer process and diffusion process at the cathode, which increases polarization impedance.

State of Charge Estimation for Lithium Battery Based on Fractional Order Square Root Cubature Kalman Filter and Adaptive Multi-innovation Unscented Kalman Filter

Accurate state of charge (SOC) estimation of batteries is of great significance for electric vehicles. A SOC estimation method based on a fractional order square root cubature Kalman filter (FOSRCKF) and an adaptive multi-innovation unscented Kalman filter (AMIUKF) is proposed. The battery is modelled using fractional order calculus theory and the model parameters are identified by adaptive genetic algorithm. The FOSRCKF estimates the battery SOC, while the AMIUKF online updates the internal resistance in the model, and there exchanges information between two filters. The experimental results under the Urban Dynamometer Driving Schedule (UDDS) and the US06 Highway Driving Schedule show that the proposed method has lower SOC estimation error and lower terminal prediction error compared with the traditional SRCKF method based on integer order models, which demonstrates the effectiveness, accuracy and robustness of the proposed method.

The gas production characteristics and catastrophic hazards evaluation of thermal runaway for LiNi0.5Co0.2Mn0.3O2 lithium-ion batteries under different SOCs

Lithium-ion batteries (LIBs) are widely used as electrochemical energy storage systems in electric vehicles due to their high energy density and long cycle life. However, fire accidents present a trend of frequent occurrence caused by thermal runaway (TR) of LIBs, so it is especially important to evaluate the catastrophic hazards of these LIBs. This study conducted the adiabatic TR test coupled gas production test, Gas Chromatography-Mass Spectrometry test, and explosion limit test on a commercial LIB with Ni0.5Co0.2Mn0.3 as the cathode material at different states of charge (SOCs). The results show that the TR temperature and the maximum temperature at low SOC are lower compared to that at a high SOC. The probability of LIBs TR at less than SOC = 50 % is small and also causing less harm. For the gas production characteristics, the lower the SOC of the battery, the lower the gas production volume. The peak and steady-state gas production increase with the increase of SOC. For the mixed gases generated during TR, the content of CO2 shows a trend of decreasing with the increasing of battery SOC, while that of H2 and CO increase with the increasing of SOC. For the explosion limit of the mixed gas, the lower explosion limit and upper explosion limit decrease and increase with the increasing of SOC, respectively. Finally, based on the seven parameters related to the TR gas production of LIBs and so on, the analytic hierarchy process method was used to establish a LIB TR disaster-causing hazard evaluation system. The evaluation system can quantitatively evaluate the thermal safety of a LIB. This is instructive for establishing a comprehensive quantitative evaluation method for battery safety in practical engineering applications.

Structural Insights into Linkage-Specific Ubiquitin Chains Using Ion Mobility Mass Spectrometry.

The structural characterization and differentiation of four types of oligoubiquitin conjugates [linear (Met1)-, Lys11-, Lys48-, Lys63-linked di-, tri-, and tetraubiquitin chains] using ion mobility mass spectrometry are reported. A comparison of collision cross sections for the same linkage of di-, tri-, and tetraubiquitin chains shows differences in conformational elongation for higher charge states due to the interplay of linkage-derived structure and Coulombic repulsion. For di- and triubiquitin chains, this elongation results in a single narrow feature representing an elongated conformation type for multiple higher charge state species. In contrast, higher charge state tetraubiquitin species do not form a single conformer type as readily. A comparison of different linkages in tetraubiquitin chains reveals greater similarity in conformation type at lower charge states; with increasing charge state, the four linkage types diverge in the relative proportions of elongated conformer types with Met1- ≥ Lys11- > Lys63- > Lys48-linkage. These differences in conformational trends could be discussed with respect to biological functions of linkage-specific polyubiquitinated proteins.

An Experimental Study on the Thermal Runaway Propagation of Cycling Aged Lithium-Ion Battery Modules

The primary concerns for individuals using lithium-ion batteries (LIBs) are aging and thermal runaway (TR). This paper focuses on the thermal runaway propagation (TRP) of cycling aged LIB modules. The impacts of state of charge (SOC), state of health, and cyclic aging temperature on TRP in LIB modules are investigated. The analysis includes parameters such as temperature, voltage, and mass of the modules during TRP. It was found that as SOC increases, the maximum increase in temperature and maximum temperature rate of the modules increased, as did the total mass loss and smoke emissions. The average heat transfer between adjacent cells was higher for the lower SOC. Cycle aging reduces the thermal stability of LIBs, leading to a lower maximum temperature and maximum temperature rate, as well as a larger mass loss compared with fresh battery modules. Regarding aging temperature, low-temperature aging reduces the total duration of TRP compared with room temperature, but it increases the maximum temperature rate and causes greater mass loss. Aging also increases the average heat transfer between adjacent cells.

Revealing the Nanoscopic Corrosive Degradation Mechanism of Nickel-Rich Layered Oxide Cathodes at Low State-of-Charge Levels: Corrosion Cracking and Pitting.

Ni-rich layered oxides have received significant attention as promising cathode materials for Li-ion batteries due to their high reversible capacity. However, intergranular and intragranular cracks form at high state-of-charge (SOC) levels exceeding 4.2 V (vs. Li/Li+), representing a prominent failure mechanism of Ni-rich layered oxides. The nanoscale crack formation at high SOC levels is attributed to a significant volume change resulting from a phase transition between the H2 and H3 phases. Herein, in contrast to the electrochemical crack formation at high SOC levels, another mechanism of chemical crack and pit formation on a nanoscale is directly evidenced in fully lithiated Ni-rich layered oxides (low SOC levels). This mechanism is associated with intergranular stress corrosion cracking, driven by chemical corrosion at elevated temperatures. The nanoscopic chemical corrosion behavior of Ni-rich layered oxides during aging at elevated temperatures is investigated using high-resolution transmission electron microscopy, revealing that microcracks can develop through two distinct mechanisms: electrochemical cycling and chemical corrosion. Notably, chemical corrosion cracks can occur even in a fully discharged state (low SOC levels), whereas electrochemical cracks are observed only at high SOC levels. This finding provides a comprehensive understanding of the complex failure mechanisms of Ni-rich layered oxides and provides an opportunity to improve their electrochemical performance.

Plug‐In Hybrid Electric Vehicle Energy Management with Clutch Engagement Control via Continuous‐Discrete Reinforcement Learning

Energy management strategy (EMS) is a key technology for plug‐in hybrid electric vehicles (PHEVs). The energy management of certain series–parallel PHEVs involves the control of continuous variables, such as engine torque, and discrete variables, such as clutch engagement/disengagement. Herein, a control‐oriented model is established for a series–parallel plug‐in hybrid system with clutch engagement control from the perspective of mixed‐integer programming. Subsequently, an EMS based on continuous‐discrete reinforcement learning (CDRL), which enables simultaneous output of continuous and discrete variables, is designed. During training, state‐of‐charge (SOC) randomization is introduced to ensure that the hybrid system exhibits optimal energy‐saving performance in both high and low SOC. Finally, the effectiveness of the proposed CDRL strategy is verified by comparing EMS based on charge‐depleting charge‐sustaining (CD‐CS) with rule‐based clutch engagement control and dynamic programming (DP). In the simulation results, it is shown that, under a high SOC, the CDRL strategy proposed in this article can improve energy efficiency by 8.3% compared to CD‐CS, and the energy consumption is just 6.6% higher than the global optimum based on DP, while under a low SOC, the numbers are 4.1% and 3.9%, respectively.

Enhancing SOC estimation accuracy via incremental learning techniques for second-life batteries

The available options for retired batteries include recycling or finding a secondary application. Repurposing the batteries for applications like stationary systems or low-speed vehicles may present a viable alternative. However, Second-Life Batteries (SLB) entail unique challenges since a battery pack comprises cells with diverse resistance and capacity characteristics. It makes the operation of BMS less efficient as the battery undergoes degradation. In light of these challenges, this study introduces an application of Incremental Learning in conjunction with a Random Forest model employing twenty estimators to predict a battery’s state of charge (SOC) at various levels of state of health. The proposed model was trained using the first three cycles and applied in real time during subsequent discharges. After each discharge cycle, the model underwent further training to refine its understanding of the underlying problem. Compared to other models, the implementation is more straightforward because the model learns with the data and does not require cell rest, actual capacity, or a battery model, such as known models in the literature. To validate the model, it has been applied for sixty discharge cycles for first-life batteries (Exp1), stationary (Exp2), and dynamic SLB systems (Exp3). The results demonstrated a consistently low RMSE SOC variation of less than 2% for Exp1 and Exp2 and less than 4% for Exp3, validating the use of it for first-life batteries and SLB with constant and dynamic loads.

Developing Preventative Strategies to Mitigate Thermal Runaway in NMC532-Graphite Cylindrical Cells Using Forensic Simulations

The ubiquitous deployment of Li-ion batteries (LIBs) in more demanding applications has reinforced the need to understand the root causes of thermal runaway. Herein, we perform a forensic simulation of a real-case failure scenario, using localised heating of Li(Ni0.5Mn0.3Co0.2)O2 versus graphite 18650 cylindrical cells. This study determined the localised temperatures that would lead to venting and thermal runaway of these cells, as well as correlating the gases produced as a function of the degradation pathway. Catastrophic failure, involving melting (with internal cell temperatures exceeding 1085 °C), deformation and ejection of the cell componentry, was induced by locally applying 200 °C and 250 °C to a fully charged cell. Conversely, catastrophic failure was not observed when the same temperatures were applied to the cells at a lower state of charge (SOC). This work highlights the importance of SOC, chemistry and heat in driving the thermal failure mode of Ni-rich LIB cells, allowing for a better understanding of battery safety and the associated design improvements.

Battery degradation: Impact on economic dispatch

AbstractBatteries are crucial to manage the rising share of intermittent energy sources and variability in demand. Most technoeconomic models in the literature oversimplify battery degradation representation. Accounting properly for battery degradation allows for better cost tradeoffs and optimal battery usage, especially in dynamic settings. We propose a highly accurate and scalable formulation for battery degradation that considers the combined impact of cycle depth (CD) and state of charge on calendar and cycle aging. This includes a novel way to track charge‐discharge cycles. We test the consequences of battery degradation in a stylized price arbitrage model on battery operation and solution times. When ignoring battery degradation, ex post calculations reveal hidden degradation costs that exceed revenues and hence turn seemingly profitable trades into losing trades. Considering battery degradation leads to smaller CDs and lower average states of charge. Overall, we show that a much‐improved representation of battery degradation is possible at modest computational cost, allowing better decisions and higher profits.

MiRNA and DNA analysis by negative ion electron transfer dissociation and infrared multiple-photon dissociation mass spectrometry

BackgroundThe use of simple and hybrid fragmentation techniques for the identification of molecules in tandem mass spectrometry provides different and complementary information on the structure of molecules. Nevertheless, these techniques have not been as widely explored for oligonucleotides as for peptides or proteins. The analysis of microRNAs (miRNAs) warrants special attention, given their regulatory role and their relationship with several diseases. The application of different fragmentation techniques will be very interesting for their identification. ResultsFour synthetic miRNAs and a DNA sequence were fragmented in an ESI-FT-ICR mass spectrometer using both simple and hybrid fragmentation techniques: CID, nETD followed by CID, IRMPD, and, for the first time, nETD in combination with IRMPD. The main fragmentation channel was base loss. The use of nETD-IRMPD resulted in d/z, a/w, and c/y ions at higher intensities. Moreover, nETD-IRMPD provided high sequence coverage and low internal fragmentation. Native MS analysis revealed that only miR159 and the DNA sequence formed stable dimers under physiological ionic strength. The use of organic co-solvents or additives resulted in a lower sequence coverage due to lesser overall ionization efficiency. NoveltyThis work demonstrates that the combination of nETD and IRMPD for miRNA fragmentation constitutes a suitable alternative to common fragmentation methods. This strategy resulted in efficient fragmentation of [miRNA]5- using low irradiation times and fewer internal fragments while ensuring a high sequence coverage. Moreover, given that such low charge states predominate upon spraying in physiological-like conditions, native MS can be applied for obtaining structural information at the same time.

Novel battery power capability assessment for improved eVTOL aircraft landing

A key aspect in the deployment of electric vertical take-off and landing (eVTOL) aircraft is the safety and performance capabilities of the batteries used. A component of the safety requirements is the need for reserve energy, which would only be utilised in case of emergencies. In the literature, it has been observed that the lower bound of the reserve region of battery energy should be limited to avoid the area where a precipitous drop in voltage would occur. Here, a method for defining the lower bound is proposed. This seeks to extend the amount of time the aircraft can cruise before landing can no longer be completed. A novel power capability testing procedure is used to measure the lowest state-of-charge (SoC) at which a constant power pulse can be completed. This differs from existing power capability tests that perform pulses at predetermined SoC points. The goal of the proposed method is to replicate the conditions of landing to understand the power capability performance at low SoC. The test is performed for a variety of environmental conditions and use cases, which includes temperature and power pulses, as well as two sets of differently aged cells. For the defined test conditions, the lowest SoC values for the calendar aged cells ranges from 6% to 14% SoC, whereas the range for cycle aged cells is 8% to 27% SoC. The outcome of this test is a characteristic map which correlates temperature, pulse power and pulse duration to the lowest SoC the pulse can be completed. The characteristic map indicates the lowest SoC value allowed for the battery before landing needs to be performed. The accuracy of the characteristic map is compared to a battery equivalent circuit model, parametrised from the test data. The defined approaches are experimentally validated based on a set of previously unmeasured experimental conditions. Overall, the characteristic map provides good accuracy compared to measured values, with both map and model methods having an average maximum absolute percentage error of at most 7.5%. Additionally, the test results show that if the worst case landing scenario is used as the lower bound of the reserve region, the useable SoC range for nominal flight would be greatly affected if cell degradation is not considered.

Novel Active Battery Balancing Methodologies for Lithium Batteries: An Experimental Comparative Analysis

Inconsistency in the battery pack parameters results in an uneven state of charge (SoC). The active battery balancing method is an approach to equalize the SoC of the battery cells in a battery pack. In active balancing method, the battery having the highest SoC is made to equalize with the battery having the lowest SoC through the electronic circuits. However, it needs more cost and complex control circuits. To overcome this shortcoming, simple switching circuit‐based dynamic battery balancing techniques and row interconnected techniques are proposed. The proposed techniques are compared and analyzed with various conventional techniques. The experiments are conducted with 4.4 V, 6 Ah, 0.5 C lithium ferro‐phosphate battery cell and the battery pack consists of four cells. In the proposed techniques, the interconnections among the battery cells are altered using a switching matrix circuit. From the results, it is observed that the balanced row interconnected series–parallel dynamics and balanced row interconnected series–parallel have delivered superior performance under all the balancing conditions. Overall, the proposed technique enhances the battery storage capacity by 23.3% during the unbalanced SoC condition. The row interconnected series–parallel dynamics have achieved the average SoC of 96.14% under different balancing conditions.

Influence of state of charge inconsistency on electrical performance and thermal runaway characteristics in 2 serials 1 parallel lithium‐ion battery pack

AbstractLithium‐ion batteries (LIBs) are connected in series during use. State of charge (SOC) difference between two batteries will exist after charging/discharging owing to the capacity or resistance difference between them. This is also seen as SOC inconsistency. SOC inconsistency may cause battery electrical abuse. In this manuscript, a battery testing system, scanning electron microscope, heat furnace, and so on were employed to investigate the influence of SOC inconsistency on electrical performance and thermal runaway (TR) characteristics in 2 serials 1 parallel (2S1P) LIB pack after cycling. The results indicated that the cell with higher SOC in an inconsistent 2S1P pack was overcharged to 4.63 V during first charging, and the cell with lower SOC was over‐discharged to 1.90 V during first discharging. The cell with higher SOC became both overcharged and over‐discharged gradually with cycles. The cell with lower SOC became neither overcharged nor over‐discharged gradually. The electrical performance and TR characteristics of the cell with higher SOC became worse, while that of the cell with lower SOC did not change obviously. The state of health for cells with higher SOC decreased from 100% to 58% after 80 cycles. The time interval between current interrupt device activation and onset temperature of TR for cells with higher SOC was reduced by 183 s, and the maximum surface temperature increased by 34°C.