Battery Performance Degradation Research Articles

Advanced Electrode Materials for Low‐Temperature Na Storage

AbstractSodium‐ion batteries have drawn worldwide attention as ideal candidates for the upcoming generation of large‐scale electrical energy storage devices due to the low cost and abundance of sodium. Due to its unique electrochemical and chemical properties, sodium‐ion batteries hold the promise of breaking geographical and environmental constraints, achieving efficient sodium storage under low‐temperature conditions. However, low‐temperature sodium‐ion batteries, especially for their electrode materials, still face numerous challenges, such as the sluggish electrochemical reaction kinetics, poor material stability, significant volume changes leading to the pulverization of materials and the rapid degradation of battery performance. Here, it is focused on the modification methods for electrode materials, the research progress on cathode and anode materials of low‐temperature sodium‐ion batteries is summarized systematically and the other components of the electrodes are discussed briefly, and the shortcomings of the current research and possible future research directions are discussed thoroughly.

Chromium Oxide Nanoparticles Anchored in Hydrogel-Derived Three-Dimensional N-Doped Porous Carbon Anode Materials as Lithium-Ion Batteries.

Transition metal oxides (TMOs) have been identified as the most promising anode materials for lithium-ion batteries (LIBs). However, these materials tend to undergo volumetric expansion during battery operation, which disrupts their internal structure and ultimately leads to a degradation of battery performance. Cr2O3/N-doped porous carbon (Cr2O3@NC) composites were successfully synthesized through high-temperature calcination using Cr2O3-containing hydrogels as precursors. The results show that the carbon material not only improves the electron transfer ability of Cr2O3 but also effectively prevents its agglomeration. The Cr2O3@CN composite as a novel anode material for LIBs exhibits a reversible capacity of 936 mAh g-1 after 200 cycles at a current density of 1 A g-1, showcasing excellent cycling and structural stability during cycling. Scanning electron microscopy analysis reveals that the Cr2O3@NC composite remains structurally intact throughout cycling. The innovative approach proposed in this study provides a new direction for the advancement of electrode materials for energy storage technologies.

Prediction of Lithium-Ion Battery Health Using GRU-BPP

Accurate prediction of lithium-ion batteries’ (LIBs) state-of-health (SOH) is crucial for the safety and maintenance of LIB-powered systems. This study addresses the variability in degradation trajectories by applying gated recurrent unit (GRU) networks alongside principal component analysis (PCA), Granger causality, and K-means clustering to analyze the relationships between operating conditions—such as temperature and load profiles—and battery performance degradation. This paper uses a publicly accessible dataset derived by aging three prismatic LIB cells under a realistic forklift operation profile. First, we identify the features that are relevant to driving variance, then we employ the winning algorithm of K-means clustering for the classification of operational states. Granger causality later investigates the inter-group relationships. Our GRU-BPP model achieves an RMSE value of 0.167 and an MAE of 0.129 for the reference performance testing (RPT) dataset and an RMSE of 0.032 with an MAE of 0.025 for the aging dataset, thus outperformed benchmark methods such as GRU, LME, and XGBoost. These results further enhance the predictiveness and robustness of this approach and yield a holistic solution to the conventional challenges in battery management and their remaining useful life (RUL) predictions.

Evolution of aging mechanisms and performance degradation of lithium-ion battery from moderate to severe capacity loss scenarios

The aging mechanisms of Nickel-Manganese-Cobalt-Oxide (NMC)/Graphite lithium-ion batteries are divided into stages from the beginning-of-life (BOL) to the end-of-life (EOL) of the battery. The corresponding changes in the battery performance across these stages have been analyzed, and a digital twin model is established to quantify the primary parameters that influence these aging mechanisms. Post-mortem analysis is applied to validate the results. This paper compares the aging mechanisms from BOL to EOL using two charging protocols: a multi-step fast charge protocol and a common constant-current fast charge protocol that applies the average current of multi-step currents. Notably, a transition from a linear to a non-linear degradation trend in capacity fade is observed, beginning from a 10% capacity reduction to EOL. From BOL to 10% degradation, the resistance of solid electrolyte interphase (SEI) grows steadily. The graphite anode’s crack depth exhibits a significant increase, accompanied by an evident collapse of cathode materials in all the test cases following a 10% degradation until EOL. This phenomenon can be attributed to one primary reason—the expansion of the corresponding simulated resistance of charge transfer (Rct). Post-mortem analysis revealed the change in morphology, structure, and composition of various degradation conditions. This analysis proved that the primary driver of the linear aging stage is the SEI growth. Furthermore, it is evident that the transition to a non-linear aging degradation is dominated by electrode defects resulting from continuous mechanical stress during long-term aging.

Advanced data-driven techniques in AI for predicting lithium-ion battery remaining useful life: A comprehensive review

As artificial intelligence (AI) technology evolves, data-driven approaches are gaining attention in predicting lithium-ion battery's remaining useful life (RUL). Indeed, accurate RUL prediction is challenging, primarily because of the complex nature of the work and dynamic shifts in model parameters. To address these challenges, this article comprehensively explores five significant publicly accessible lithium-ion battery datasets, encompassing diverse usage conditions and battery types, offering researchers a rich repository of experimental data. In particular, we not only provide detailed information and access addresses for each dataset, but also present, for the first time, four innovative methods for battery aging health factor extraction. These methods, based on advanced AI techniques, are able to effectively identify and quantify key indicators of battery performance degradation, thereby enhancing the precision and dependability of RUL prediction. Additionally, the article identifies major challenges faced by current predictive techniques, including data quality, model generalization capabilities, and computational cost, highlighting the need for research focused on dataset diversity, multiple algorithm fusion, and hybrid physical-data-driven models to enhance prediction accuracy. We believe that this review will help researchers gain a comprehensive understanding of RUL estimation methods and promote the development of AI in battery.

Low‐temperature performance of Na‐ion batteries

AbstractSodium‐ion batteries (NIBs) have become an ideal alternative to lithium‐ion batteries in the field of electrochemical energy storage due to their abundant raw materials and cost‐effectiveness. With the progress of human society, the requirements for energy storage systems in extreme environments, such as deep‐sea exploration, aerospace missions, and tunnel operations, have become more stringent. The comprehensive performance of NIBs at low temperatures (LTs) has also become an important consideration. Under LT conditions, challenges such as increased viscosity of electrolyte, abnormal growth of solid electrolyte interface, and poor contact between collector and electrode materials emerge. The aforementioned issues hinder the diffusion kinetics of sodium ions (Na+) at the electrode/electrolyte interface and cause rapid degradation of battery performance. Consequently, the optimization of electrolyte composition and cathode/anode materials becomes an effective approach to improve LT performance. This review discusses the conduction behavior and limiting factors of Na+ in both solid electrodes and liquid electrolytes at LT. Furthermore, it systematically reviews the recent research progress of LT NIBs from three aspects: cathode materials, anode materials, and electrolyte components. This review aims to provide a valuable reference for developing high‐performance LT NIBs.

Dynamic Coupling of Internal Strain Field and Lithium Pathway within Individual Battery Particles in Solid State Batteries

In all-solid-state batteries (ASSBs), (electro)chemo-mechanical aspects such as uneven interfaces, cathode-electrolyte interphase formation, delamination, fracture, defects, etc., are the major factors in capacity fade but remain largely unknown.Nonhomogeneous transfer of lithium ions can cause significant variations in strain and stress within battery electrodes, leading to degradation in battery performance. In all-solid-state batteries (ASSBs), the lithium pathway and the associated strain/stress field become more intricate due to the (electro)chemo-mechanical reaction at the electrode-electrolyte interfaces. The dynamic volume change in active particles are heavily influencing by strength of the solid electrolyte and interfacial conformality. This can continually alter the lithium pathway and the internal stress field, leading to recurrent redefinitions of (electro)chemo-mechanical environment.Here, we have developed an operando coherent X-ray imaging platform and associated analysis methodologies. This technology can track the nanoscale transport of lithium and the strain evolution of individual electrode particles in ASSBs. With this platform, we gained a comprehensive electrochemical and mechanical understanding of the cycling properties of single electrode particles in ASSBs.

Evaluating the Performance of an All-Aqueous Copper Trab through 200 Hours of Discharge Cycling

Thermally regenerative ammonia batteries (TRABs) have the potential to serve as a viable solution for energy storage and electricity generation by harnessing low-grade heat. A TRAB discharge closely resembles that of a conventional flow battery, where electrochemical reactions are used to produce electrical power and aqueous electrolytes are stored in external tanks. However, the key distinction of a TRAB from a conventional flow battery lies in the recharging process, where thermal energy is used to separate ammonia from the negolyte, referred to as thermal recharging. During thermal recharging, the exhausted negolyte is converted into a fresh posolyte through the thermal separation of ammonia that was dissolved into the solution. This separated ammonia is subsequently added into the depleted posolyte, turning it into a fresh negolyte thereby completing the recharging process. Although there are many types of TRABs, the all-aqueous copper TRAB (Cuaq-TRAB) has produced some of the largest power densities and energy storage densities observed from a TRAB discharge. Building on these recent successes with Cuaq-TRABs, our investigation seeks to assess the performance of the Cuaq-TRAB during prolonged operation. Previous investigations with TRABs have typically lasted 0.5-7 hours, with the longest lasting 20 hours, which does not provide sufficient data to demonstrate the stability of the technology as thousands of hours of operation will be required. To address this gap, we operated an Cuaq-TRAB for 200 hours with a constant discharge current density of 10 mA cm-2 to examine battery performance and material degradation over time. Throughout the 200-hour test period, we measured an average power density of 7.2 mW cm⁻², which increased by 0.01% during the test. Additionally, the average energy density was 2.7 Wh L⁻¹, with a degradation of only 0.03% over the 200-hour timeframe. These results are the first to provide valuable information about the stability of the Cuaq-TRAB system during extended operation.

Interfacial Phase Separation Governs the Chemomechanics of Polymer Electrolytes in High-Voltage, Solid-State Lithium Batteries

Polymer electrolytes hold great promise for safe and high-energy solid-state batteries. Multiphase polymer electrolytes, consisting of mobile and rigid phases, exhibit fast ion conduction and desired mechanical properties. However, fundamental challenges exist in understanding and regulating intricate chemomechanical interactions at the electrode-electrolyte interface, especially when using a high-voltage layered cathode. Here, we report that depletion of the mobile conductive phase at the interface contributes to battery performance degradation. Molecular ionic composite electrolytes, composed of a rigid-rod ionic polymer with small mobile cations and anions, serve as a multiphase platform to investigate the evolution of conductive domains at the interface. Synchrotron chemical and structural analyses enable the direct visualization of concentration polarization and spatially resolve the interfacial chemical states over a statistically significant field of view for buried interfaces. We discover that concentration and chemical heterogeneities prevail at electrode-electrolyte interfaces, leading to interfacial chemomechanical degradation. We further demonstrate an interphase tailoring strategy based on electrolyte additives to mitigate such interfacial heterogeneity and improve battery stability. While polymer electrolytes have been considered “deformable” for conformal interfaces, our work shows the hidden roles of interfacial chemomechanics in polymer electrolytes and provides an effective mitigation approach.

Battery Performance Evaluation through Decision Tree

This study addresses the pervasive concern surrounding battery performance degradation in electronic devices. While some attribute this decline to device aging, a significant portion of the population lacks awareness of the precise factors contributing to diminished battery efficiency. Consequently, the research investigates the factors related to battery performance, aiming to identify the determinants of reduced efficiency. Decision trees are used to meticulously analyze the intricate relationships between variables and discern the factors that respondents perceive as causative of diminished battery performance. This algorithm is chosen since, in predicting high-capacity lithium-ion battery performance, the decision tree outperforms other algorithms in machine learning in accuracy. The study elucidates diverse user preferences, with 55.38% favoring Android and 44.62% expressing a preference for iOS, indicating disparate perceptions of battery health: 61.54% consider their batteries as "Good," while 38.46% acknowledge a decline. The decision tree analysis of 195 participants underscores the pronounced impact of prolonged usage on battery health, revealing that 95% maintain good battery performance. In contrast, 27.69% of Android users face reduced battery performance, emphasizing the need for targeted user education and Android manufacturers to prioritize device longevity. The ultimate objective is to give readers a comprehensive understanding of the dynamics of battery performance in the context of device aging and its contributing factors and give some input to manufacturers and service providers.

Double-layer optimal scheduling method for solar photovoltaic thermal system based on event-triggered MPC considering battery performance degradation

Solar photovoltaic thermal system (SPTS) can fully tap solar energy resources to realize thermal and electric supply for users simultaneously, but the volatility and uncertainty of renewable energy and load cause the imbalance of energy supply. This paper proposes a multi-time scale optimal scheduling method for SPTS based on event-triggered model predictive control (ET-MPC) considering battery performance deterioration. Firstly, SPTS is divided into day-ahead and day-in optimization layers from different time scales. Day-ahead scheduling takes the minimization economic cost as the optimization function to obtain pre-scheduling plan, and day-in scheduling adapts rolling optimization scheme based on model predictive control (MPC) to reduce power fluctuations and achieve optimal scheduling adjustment. Moreover, the battery performance decay parameter is introduced into the MPC model and embedded into the optimization problem to prolong the cyclic life deterioration, and an event-triggered mechanism is introduced into MPC to improve the computational efficiency and reduce the communication frequency. Finally, the results show that the proposed double-layer scheduling method improves 4.15 %, 66 % and 13.39 % respectively regarding cost, power fluctuation and battery maintenance, and improve the calculation efficiency of 48.89 % compared with standard MPC method, which indicates that the proposed method has good economy, stability and execution efficiency.

Performance degradation and sealing failure analysis of pouch lithium-ion batteries under multi-storage conditions

Due to its numerous advantages, lithium-ion batteries have been widely used in various fields. However, as the application scenarios expand, batteries often encounter adverse environments such as high temperature and high humidity during storage and usage. Faced with such conditions, batteries not only experience performance degradation but also the risk of leakage, posing a serious threat to battery safety. In order to investigate the influencing factors of battery performance degradation and the failure modes of battery leakage under harsh conditions, we conducted a study using a commercial LiCoO2/graphite pouch cell as the experimental object. We focused on studying the capacity degradation mechanism and sealing failure modes during the storage process under high temperature-low humidity and high temperature-high humidity conditions. The results revealed that compared to the cell under normal temperature-low humidity conditions, the remaining capacity and recovery capacity of the cell under high temperature-low humidity and high temperature-high humidity conditions has shown a certain degree of attenuation. Subsequently, we investigated the underlying mechanisms behind the performance degradation through a series of characterizations. Additionally, regarding the issue of leakage, we analyzed the outer sealing materials of the cell to identify potential pathways for external moisture ingress, aiming to provide references and support for enhancing battery safety in harsh environments.

Optimal charging for lithium-ion batteries to avoid lithium plating based on ultrasound-assisted diagnosis and model predictive control

Lithium plating in lithium-ion batteries for electric vehicles, occurring due to low-temperature or high-rate charging, is a significant factor impacting safety and service life. To address this issue, a novel adaptive charging approach is proposed, combining ultrasound-assisted diagnosis and model predictive control (MPC). In the method, a discrete state-space electrochemical model is used to describe the dynamic characteristics of the battery, and a model predictive controller (MPC) is utilized to optimize the charging current to avoid lithium plating. Considering that factors such as battery performance degradation and variable working temperature affect the battery model's judgment of lithium plating, an ultrasound-assisted diagnosis method is used to determine the critical point of lithium plating. The effectiveness of the method is validated through low-temperature charging and cycle aging experiments. The results indicate that without complex model parameter calibration in different temperatures, the new charging method not only has a higher charging speed than constant current charging, but also can effectively suppress the occurrence of lithium plating on the negative electrode of the battery. The method is expected to be applied in electrochemical energy storage systems to enhance safety and service life.

To Enhance the Performance of LiNi0.5Co0.2Mn0.3O2 Aqueous Electrodes by the Coating Process.

The Li+/H+ cation exchange reactions occur when the cathode is exposed to water and can cause the degradation of battery performance, posing a significant challenge in the preparation of cathode aqueous electrodes. In this study, kh570 [3-(trimethoxysilyl)propyl methacrylate] is used to coat and modify the surface of LiNi0.5Co0.2Mn0.3O2 cathode particles. During the coating process, kh570 undergoes hydrolysis to generate silanol groups, which are subsequently bonded onto the surface of cathode particles and undergo self-polymerization through condensation reactions. As a result, a coating layer forms on the surface of the cathode. This change alters the surface properties of the cathode particles from hydrophilic to hydrophobic, thereby increasing their resistance to water. The coating layers reduce direct contact with water and minimizes internal particle microcracks formation in aqueous electrode processing. After the preparation of aqueous electrodes, the modified cathode exhibits lower transfer resistance and lower polarization, improving both the current rate performance and the cycling performance of the battery.

Toward the High-Voltage Stability of Layered Oxide Cathodes for Sodium-Ion Batteries: Challenges, Progress, and Perspectives.

Sodium-ion batteries (SIBs) have garnered significant attention as ideal candidates for large-scale energy storage due to their notable advantages in terms of resource availability and cost-effectiveness. However, there remains a substantial energy density gap between SIBs and commercially available lithium-ion batteries (LIBs), posing challenges to meeting the requirements of practical applications. The fabrication of high-energy cathodes has emerged as an efficient approach to enhancing the energy density of SIBs, which commonly requires cathodes operating in high-voltage regions. Layered oxide cathodes (LOCs), with low cost, facile synthesis, and high theoretical specific capacity, have emerged as one of the most promising candidates for commercial applications. However, LOCs encounter significant challenges when operated in high-voltage regions such as irreversible phase transitions, migration and dissolution of metal cations, loss of reactive oxygen, and the occurrence of serious interfacial parasitic reactions. These issues ultimately result in severe degradation in battery performance. This review aims to shed light on the key challenges and failure mechanisms encountered by LOCs when operated in high-voltage regions. Additionally, the corresponding strategies for improving the high-voltage stability of LOCs are comprehensively summarized. By providing fundamental insights and valuable perspectives, this review aims to contribute to the advancement of high-energy SIBs.

Electrochemical 3-D morphology based degradation quantification framework for lithium-ion battery under low temperature

In high-latitude areas, lithium-ion batteries for electric vehicles frequently operate under low-temperature conditions. However, lithium-ion battery suffers from complex energy loss and performance degradation under low temperature. In order to quantify the degradation mode of the battery, this paper proposes a framework with electrochemical theory and electrode 3-D morphology. The proposed framework mainly includes two parts: Firstly, the degradation modes (DMs) of the battery are extracted from incremental capacity (IC), differential voltage (DV) techniques and electrochemical impedance spectroscopy (EIS). Secondly, the 3-dimension (3-D) morphological calculation method is proposed to analyze the degradation situation of the battery electrodes. Then, the battery aging and performance testing system under low temperature is established to verify the effectiveness of the proposed framework from the perspective of surface morphology. In order to validate the effectiveness of the proposed framework, an experimental bench for battery low-temperature aging and performance testing is constructed. The experimental results demonstrate that: (1) Battery capacity is greatly reduced at low temperatures, and loss of lithium inventory (LLI) is greater at low temperatures (−5 °C and −10 °C) than at 25 °C under the same state of health (SOH). (2) By analyzing 3-D morphology, the low temperature can lead to a significant change in the surface roughness parameters of the anode electrode. The low temperature aggravates the reduction of anode gap area. It is found that the microscopic mesomorphic changes are closely related to the aging of the battery. (3) The anode graphite (002) peak position is shifted to a low angle of 2.2° under low temperature. Scanning electron microscope (SEM) images shows the graphite anode is covered by a lithium-rich SEI at low temperature. (4) Post-test calculations of the consistency of the relevant covariates revealed that the electrochemical and morphological covariates are highly linearly correlated, respectively. Hence, the effectiveness of the proposed framework is verified and a novel perspective is provided to reveal the battery performance degradation under low temperatures, which can help guarantee safe operation through battery management system.

Performance benchmarks for open source porous electrode theory models

The electrochemical response characteristics of existing and emerging porous electrode theory (PET) models was benchmarked to establish a common basis to assess their physical reaches, limitations, and accuracy. Three open source PET models: dualfoil, MPET, and LIONSIMBA were compared to simulate the discharge of a LiMn2O4-graphite cell against experimental data. For C-rates below 2C, the simulated discharge voltage curves matched the experimental data within 4% deviation for dualfoil, MPET, and LIONSIMBA, while for C-rates above 3C, dualfoil and MPET show smaller deviations, within 5%, against experiments. The electrochemical profiles of all three codes exhibit significant qualitative differences, despite showing the same macroscopic voltage response, leading the user to different conclusions regarding the battery performance and possible degradation mechanisms of the analyzed system.

Assessment of hydrogen and Lithium-ion batteries in rooftop solar PV systems

Hydrogen batteries are currently gaining attention as a promising clean energy storage technology. However, limited knowledge is available at present on the technical and financial performance of Hydrogen batteries in rooftop solar PV (RSP) systems. This study models the operation of a commercial Hydrogen battery in RSP system, using Time of Use and Solar Feed-In tariffs, and compares the performance with a commercial Lithium-ion (Li-Ion) battery under solar and arbitrage scheme. The model considers battery aging and performance degradation, with results suggesting that both hydrogen and Li-Ion batteries can reduce grid dependency and lower electricity costs by minimizing grid imports. However, the Li-Ion battery outperforms the hydrogen battery in better capacity utilisation due to lower roundtrip energy losses. The Li-Ion battery generates higher net income, achieving a payback period 9 years earlier in the arbitrage scheme and 1 year in the solar scheme, compared to the Hydrogen battery. However, the Hydrogen battery demonstrates a longer lifespan, enduring 18 % fewer charge-discharge cycles than Li-Ion battery. This makes the Hydrogen battery suitable for remote applications requiring extended duration of energy storage. The methodology developed in this study provides a valuable framework for evaluating the potential adoption of Hydrogen and Li-Ion batteries globally.

Enhancing low-temperature electrolyte performance through intermittent discharge for improved LiODFB additive film formation

The challenge of improving low-temperature performance in lithium-ion batteries (LIBs) is attributed to the formation of an unstable solid electrolyte interphase (SEI) film. Lithium difluoro(oxalate)borate (LiODFB) has demonstrated potential in enhancing capacity retention and reducing impedance at low temperatures by establishing a high ion conductivity and stable SEI layer. Previous research indicates that the BOF2− anion, a soluble product of film formation additive of LiODFB hinder salt decomposition by aggregating on the electrode surface. This study presents a strategy to intensify the film formation process of LiODFB additives by introducing an optimal standing time during intermittent discharge processes. Three specific stages of soluble product diffusion are discussed. Diffusion starts from the outer layer of adsorption composed of soluble substances, gradually extends to the inner layer of adsorption, and finally establishes a new connection with the electrode. A brief standing time proves insufficient for inner adsorption layer diffusion, while excessively extended standing time fails to accelerate LiODFB decomposition. A standing time of 2300 s is selected to promote a stable SEI layer. This strategy elevates the capacity retention rate of cells at –20 °C from 66.59 % to 84.44 %. The study offers a method to address battery performance degradation in low-temperature conditions.

Controllable organic/inorganic composite film enables improved long-term and high-temperature storage performance of lithium primary battery

Though lithium primary battery has been widely used, high temperature and long-term storage still possibly cause its failure because of the active lithium anode, which continuously reacts with electrolyte, forms an unstable solid electrolyte interface and leads to the degradation of battery performance. In this work, a novel organic-inorganic composite protecting film composed of well-dispersed inorganic lithium nitride (Li3N) among poly (propylene carbonate) (PPC) organic matrix is controllably fabricated on the Li anode by spin coating, to enhance interfacial compatibility and stability. The composite film exhibits superior ionic conductivity of 3.57 × 10−4 S cm−1, and the Li-CFx battery with composite film delivers an excellent specific discharge capacity of 940 mAh g−1 at 0.1 C, and excellent rate capacity of 492 mAh g−1 even at 8 C. After storage at room temperature and 55 °C for 60 days, the battery can still release high specific capacities of 867 and 536 mAh g−1. With the assistance of composite film, a stable Li3N/LiF-rich SEI is formed on the Li anode and LiF-rich CEI is generated on the CFx cathode, ensuring long-term and high-temperature storage stability of Li-CFx battery. This study demonstrates a facile organic/inorganic composite film protecting strategy to achieve high-performance lithium battery.