Battery Performance Research Articles

Power converters analyzed in energy storage systems to enhance the performance of the smart grid application

This paper implements and compares the existing power supply converters for an energy storage system to determine the best suited for the smart grid application. A survey of different DC-DC converters is carried out to analyze the battery's overall performance. The main objective is to identify this application's most appropriate energy storage device. The advantages of this technology have high efficiency and reliability, which can connect various energy sources and reduce conduction losses in the power converters. Through the converter control, reference currents are imposed to charge the battery. The battery nominal voltage needs to change to see which type of converter is the most suitable and robust. Simulation results show that the operating ranges of boost-buck, buck-boost, and buck-boost converters with negative output voltage enhance the efficiency of battery and renewable energy sources and compared the DC converters to know the functional voltage for the energy storage system. The power converter's efficiency and control facility will allow us to link the energy storage system with the power grid. The overall installation is established using MATLAB/Simulink software.

Power Control of Hybrid Grid-Connected Renewable Energy System using Machine Learning

This article addresses the crucial challenge of maintaining a reliable power supply in integrated electric systems that combine solar power and energy storage. It focuses on optimizing key parameters for remote photovoltaic, wind, and battery energy storage within the grid, with a primary goal of sustaining 24-hour load demand. The study introduces a comprehensive approach that integrates fuel price dynamics and battery depletion costs into the optimization model for hybrid grids. This approach seeks a delicate balance between sustainable energy usage and cost-effectiveness. To achieve this balance, the research employs genetic algorithms, a robust computational technique. These algorithms play a vital role in calculating discharge-charge cycles and assessing battery health, addressing concerns about battery longevity and performance. Additionally, the study explores a machine learning framework, specifically nested learning, to further enhance the optimization process. Nested learning allows for the development of a sophisticated target function that considers various grid operation parameters and constraints. This machine learning approach enhances the system's ability to dynamically monitor power consumption and generation. Within this machine learning framework, the TD Lambda learning algorithm takes a prominent role in identifying the optimal function. This algorithm is well-known for its efficiency, particularly in non-Markovian scenarios. Its quick convergence enhances the overall performance of the hybrid grid, ensuring efficiency in changing conditions. The research also evaluates the impact of weight factors on various aspects, including battery charging status, algorithmic decisions, and their consequences on optimal energy pricing within the hybrid grid. This comprehensive assessment deepens the understanding of how these weight factors influence grid performance and economic viability.

Adaptive fault detection for lithium-ion battery combining physical model-based observer and BiLSTMNN learning approach

Lithium-ion batteries possess one of the best energy-weight ratios, while safety and reliability are critical issues for its continued operation. Due to extreme fast-charging, huge application sizes and variable usage environment, the risk of soft battery faults, including soft internal short circuit (SISC), is increased and may evolve into severe accidents. Therefore, accurate early detection of lithium ion battery fault is imperative to guarantee the battery performance. Motivated by this fact, we proposed a real time fault detection framework for battery soft faults. Based on the Equivalent Circuit Model (ECM) and coupling thermal model, Extended Kalman Filter (EKF) observer is used for reliable monitoring of battery voltage and surface temperature. Inspired by uncertainty interference during the observation process, we explore an observed-based learning approach that combine physical model-based observer and Bidirectional Long Short-Term Memory neural networks (BiLSTMNN) to empower the observer with the ability to learn the uncertainties, which is efficient in distinguishing soft faults information and uncertainties from residual. Furthermore, the memory characteristics of BiLSTMNN are considered to improve the robustness of the detection system, including comprehensive training data and optimized input features. Finally, through the comparative analysis and the robustness evaluation experiments including various driving cycles and internal short circuits (ISC) faults test verity the good performance of the proposed method.

Investigation of 1.5 kW secondary side power controlled method in a inductive wireless power transfer system

The contemporary and utilitarianism of the existing consumer world is advancing towards the better world technical benefits in the electrical world such as wired phase to wireless phase utilizing its volatile features. This paper addresses the battery performance in constant current (CC), constant voltage (CV) through inductive wireless power transfer (IWPT) systems. To analyze this workable mode, the researcher has proposed the series-series (S-S) compensation topology which is load independent current output. While charging the battery through wireless, the coil resistance is found to be affected by the battery's current and power. To figure out a practical solution, the researcher has introduced novel closed loop bi-directional switches with duty cycle control. The existing theoretical and simulated results have been analyzed with 1.5 kW, 120 mm air-gap and 85 kHz frequency. In this connection, the researcher has self-developed a prototype to better understand the theoretical perceptions of the proposed WPT system.

Mechanically and Electrically Stable Hybrid Aerogels as Free‐Standing Anodes for High‐Capacity Lithium‐Ion Battery

Molybdenum disulfide (MoS2) is a promising alternative to graphite anodes in battery materials. Therefore, it is critical to scrutinize their structural stability and charge storage capacity during battery operation. Herein, freestanding electrodes consisting of MoS2‐incorporated carbon nanotube aerogels are fabricated using a simple yet scalable hydrothermal method, as used in lithium‐ion batteries. The outer nitrogen‐doped graphitic carbon (NGr) layers support efficient charge transport, even under a substantial compressive environment, and improve the structural integrity, showing significant improvements in battery performance, such as a high rate capacity of 820 mAh g−1 at the current density of 5 A g−1 and 94% capacity retention after 170 cycles (1170 mAh g−1 at 1 A g−1 after 170 cycles), even in the absence of polymer binders and conductive additives. The resulting NGr/MoS2/single‐walled carbon nanotubes freestanding electrodes have great potential to increase the volumetric and gravimetric energy density of batteries.

Experimental study of heat pipes for battery cooling technology in EVs

Abstract The modern world is moving towards electric vehicles (EV) due to the increment in greenhouse gas (GHG) emissions, global warming, and the lack of fossil fuels. EVs can overcome these issues by using batteries instead of fuel. But increasing and maintaining the batteries is a major challenge in EVs because of the large heat emissions from the batteries. In order to overcome these issues and increase the performance of the batteries, a heat pipe (HP) is attached to the passive cooling system. This study aims to improve the performance of batteries and the thermal conductivity of HP with a combination of refrigerant and nanofluid (nanorefrigerant) as working fluids. Copper HP with R-134a or SWCNT is selected for this study. The thermal resistance and thermal conductivity of HP with R-134a and SWCNT were observed for several heat conditions. From the study, it was well observed that changing the working fluid inside the HP affects the thermal performance and the cooling capacity of batteries. Fixing an HP to a battery would decrease the battery’s temperature effectively. Furthermore, increasing the heat power in an evaporator section decreases the thermal resistance and enhances thermal conductivity with the shortest time limit because of Brownian motion.

Boosting potassium and sodium-ion storage performance by in-situ self-assembly of a Co-based π-d conjugated coordination polymer on graphene nanosheets

To obtain anode materials with good electrochemical performances in both potassium ion batteries (PIBs) and sodium-ion batteries (SIBs), a Co-based π-d conjugated coordination polymer (Co-HHTP) is in-situ assembled on graphene (G) nanosheets using a facile one-step solvothermal method. The resulting Co-HHTP/G composite shows improved electrochemical performances over pure Co-HHTP. After 300 cycles of using as an anode of PIBs/SIBs for the first time, the reversible specific capacity of the Co-HHTP/G composite is found to be 381/277 mAh g−1 at 100 mA g−1. After undergoing 500 cycles at 1000 mA g−1, the material's reversible specific capacities remain at 234/164 mAh g−1 for PIBs/SIBs. The improved performances of the Co-HHTP/G composite electrode are due to the incorporation of graphene. This incorporation not only reduces structural stacking and promotes active site utilization, but also increases electrical conductivity and structural stability. According to the ex-situ X-ray photoelectron spectrometer (XPS) spectra, the Co-HHTP/G's energy storage mechanism throughout the process of potassisation/depotassisation is found to be linked to the aromatic rings presented in the organic ligands.

Reconfiguring the Hydrogen Networks of Aqueous Electrolyte to Stabilize Iron Hexacyanoferrate for High-Voltage Decoupled Cell.

Prussian blue analogs (PBAs) as insertion-type cathodes have attracted significant attention in various aqueous batteries to accommodate metal or non-metal ions while suffering from serious dissolution and consequent inferior lifespan. Herein, we reveal that the dissolution of PBAs primarily originates from the locally elevated pH of electrolytes that are caused by proton co-insertion during discharge. To address this issue, a water-locking electrolyte (WLE) has been strategically implemented, which interrupts the generation and Grotthuss diffusion of protons by breaking the well-connected hydrogen bonding network in aqueous electrolytes. As a result, the WLE enables the iron hexacyanoferrate to endure over 1000 cycles at a 1C rate and supports a high-voltage decoupled cell with an average voltage of 1.95 V. These findings provide insights for mitigating dissolution problems in electrode materials, thereby enhancing the viability and performance of aqueous batteries.

Reconfiguring the Hydrogen Networks of Aqueous Electrolyte to Stabilize Iron Hexacyanoferrate for High‐Voltage Decoupled Cell

Prussian blue analogs (PBAs) as insertion‐type cathodes have attracted significant attention in various aqueous batteries to accommodate metal or non‐metal ions while suffering from serious dissolution and consequent inferior lifespan. Herein, we reveal that the dissolution of PBAs primarily originates from the locally elevated pH of electrolytes that are caused by proton co‐insertion during discharge. To address this issue, a water‐locking electrolyte (WLE) has been strategically implemented, which interrupts the generation and Grotthuss diffusion of protons by breaking the well‐connected hydrogen bonding network in aqueous electrolytes. As a result, the WLE enables the iron hexacyanoferrate to endure over 1000 cycles at a 1C rate and supports a high‐voltage decoupled cell with an average voltage of 1.95 V. These findings provide insights for mitigating dissolution problems in electrode materials, thereby enhancing the viability and performance of aqueous batteries.

Correction: Enhanced cycle performance of Li ion battery by graphene sheets covering with SnO@SnO2 anode materials

Correction: Enhanced cycle performance of Li ion battery by graphene sheets covering with SnO@SnO2 anode materials

The Li battery digital twin – Combining 4D modelling, electro-chemistry, neutron, and ion-beam techniques

Knowledge driven materials and component design is key for improving the performance of Li-ion batteries and solving the remaining hurdles for next-generation battery concepts like all-solid-state batteries. While the spatial and time dependent distribution of Li would help elucidating performance bottlenecks and degradation phenomena, only a few analysis techniques are available, due to the unique nature of Li, especially as Li+-ion. In fact, only two non-destructive techniques with good time resolution can combine spatial information with absolute quantification of Li, one being Neutron Depth Profiling (NDP), the other Ion-Beam-Analysis (IBA). While both exploit nuclear processes, the information gained is complementary. NDP provides high depth resolution, but only limited lateral resolution, whereas IBA has high lateral, but only limited depth resolution. In this study, we benchmark both techniques for the first time using a set of Li-battery test-samples and show the strengths and synergies of both techniques. The derived information regarding the depth dependent Li-concentration is then used to validate a microstructure resolved continuum model of charge, discharge, and relaxation behavior of the cells and electro-chemical analysis. This fundamental work demonstrates a new route to optimize Li batteries on material and component level by combining advanced characterization and digital twin modelling.

Weak Li-O bonds and small grains enable fast ion diffusion and electron transport for LiFePO4 cathode

The LiFePO4 material continue to suffer from poor rate performance. Nanosized LFP can improve rate performance; however, nanofabrication typically requires expensive organic matter and high-pressure-resistant equipment. The current widely used solid-phase sintering methods employ FePO4 as the precursor, but it is difficult to suppress grain growth. Here, we propose a W–Ti codoping strategy to suppress grain growth during sintering, thereby improving rate performance of Li-ion batteries. W and Ti doping shrinks grains during the sintering process and make the Li-O bond more ionized. Li0.36WO3 accumulates at grain boundaries, hindering grain boundary diffusion and inhibiting grain growth during sintering. The resulting material exhibits refined grains and suppressed polarization growth, resulting in improved rate performance while maintaining a specific capacity of 117 mAh g−1 at a rate of 10 C. After 1000 cycles at a rate of 1 C, 91.0 % of the initial capacity was retained. In summary, this research provides a method for large-scale production of LFP with excellent rate performance.

Continuum insight into the effects of electrode design parameters on the electrochemical performance of lithium-ion batteries

Lithium-ion batteries energy and power density strongly depend on the type of active material and the electrode design parameters. An in-depth understanding of the effect of battery design parameters on their electrochemical performance is experimentally expensive and hence requires the utilization of cheaper continuum scale models. Here, using a lithium-ion cell composed of LiFePO4 cathode, Li4Ti5O12 anode and a porous separator filled with a liquid electrolyte as an example, we demonstrate the use of an experimentally validated pseudo-two-dimensional (P2D) model in one-dimension to explore the effects of different cell design parameters on the discharge capacity at different current rates. The model is simulated in two-dimensional to instantly visualize the concentration distribution of Li ions in the electrode at high discharge current rates. The continuum model unravels that the solution phase diffusion limitation is the main factor inhibiting the performance of thick electrodes at high current rates and the Li4Ti5O12 anode is the limiting electrode. These findings using continuum models provide guidance for and accelerate the optimization of electrode architecture for enhancing the performance of lithium-ion batteries.

Achieving Dendrite-Free and By-Product-Free Aqueous Zn-Ion Battery Anode via Nicotinic Acid Electrolyte Additive with Molecule-Ion Conversion Mechanism.

The widespread adoption of aqueous Zn ion batteries is hindered by the instability of the Zn anode. Herein, an elegant strategy is proposed to enhance the stability of Zn anode by incorporating nicotinic acid (NA), an additive with a unique molecule-ion conversion mechanism, to optimize the anode/electrolyte interface and the typical ZnSO4 electrolyte system. Experimental characterization and theoretical calculations demonstrate that the NA additive preferentially replaces H2O in the original solvation shell and adsorbs onto the Zn anode surface upon conversion from molecule to ion in the electrolyte environment, thereby suppressing side reactions arising from activated H2O decomposition and stochastic growth of Zn dendrites. Simultaneously, such a molecule-to-ion conversion mechanism may induce preferential deposition of Zn along the (002) plane. Benefiting from it, the Zn||Zn symmetric battery cycles stably for 2500h at 1mAcm-2, 1mAhcm-2. More encouragingly, the Zn||AC full batteries and the Zn||AC full batteries using NA electrolyte and Zn||VO2 full batteries also exhibit excellent performance improvements. This work emphasizes the role of variation in the form of additives (especially weak acid-based additives) in fine-tuning the solvation structure and the anode/electrolyte interface, hopefully enhancing the performance of various aqueous metal batteries.

Reconfiguring the Electrolyte Network Structure with Bio‐Inspired Cryoprotective Additive for Low‐Temperature Aqueous Zinc Batteries

AbstractDespite promising performance at ambient temperature, the development of aqueous zinc batteries is jeopardized by the freeze of aqueous electrolytes and deteriorative electrode‐electrolyte interphase at low temperatures. Herein, inspired by the cryoprotective mechanism of extracellular polysaccharides in biological organisms, a quaternized galactomannan polysaccharide (q‐GPA) is proposed as a cryoprotective additive for improving low‐temperature performance of aqueous zinc batteries. Mechanistic studies revealed that a multi‐hydroxyl galactomannan backbone can substantially attenuate the activity of water molecules through the reconfiguration of the hydrogen bond network, which inhibits ice crystal formation at subzero temperatures and thus depress the freezing point of the electrolyte. Meanwhile, the quaternary ammonium groups tethered on the q‐GPA skeleton are intended to neutralize the interfacial electric field through electrostatic repulsion, thereby accelerating Zn2+ deposition kinetics and prohibiting zinc dendrite growth. Impressively, the q‐GPA–modified electrolyte enables an extended lifespan of over 1700 h in Zn||Zn symmetric battery at a high current density of 3 mA cm−2 and an ultralong cycle life of 5000 cycles with a capacity retention of 99.2% in the Zn||Na2V6O16·1.5H2O (NVO) full battery at −30 °C. This work provides unprecedented possibilities for optimizing the electrolyte formulation of low‐temperature aqueous batteries.

Modeling and Simulation of Single Flow Zinc–Nickel Redox Battery Coupled with Multi-Physics Fields

Metallic zinc (Zn) presents a compelling alternative to conventional electrochemical energy storage systems due to its environmentally friendly nature, abundant availability, high water compatibility, low toxicity, low electrochemical potential (−0.762 V vs. SHE), and cost-effectiveness. While considerable efforts have been devoted to enhancing the physical and chemical properties of zinc-ion battery materials to improve battery efficiency and longevity, research on multi-physics coupled modeling for a deeper understanding of battery performance remains relatively scarce. In this study, we established a comprehensive two-dimensional model for single-flow zinc–nickel redox batteries to investigate electrode reactions, current-potential behaviors, and concentration distributions, leveraging theories such as Nernst–Planck and Butler–Volmer. Additionally, we explored the distribution of the velocity field using the Brinkman theory in porous media and the Navier–Stokes equations in free-flow channels. The validated model, informed by experimental data, not only provides insights into the performance of the battery, but also offers valuable recommendations for advancing single-flow zinc–nickel battery technology. Our findings offer promising avenues for enhancing the design and performance of not only zinc–nickel flow batteries, but also applicable for other flow battery designs.

Hierarchical Co-doped hollow Ti3C2Tx tubes with built-in electron/ion transport network for high-performance lithium sulfur batteries

A crucial approach to enhancing the electrochemical performance of lithium-sulfur batteries (LSBs) is to develop a dependable sulfur host material possessing reasonable structure, high electrical conductivity, and exceptional adsorption/catalytic capabilities towards lithium polysulfides (LiPSs). Herein, Co-doped hollow Ti3C2Tx tubes with in-situ grown CNTs as a built-in electron/ion transport network (HTCTs/Co/CNTs) are prepared via electrospinning technique combined with the self-catalyzed growth strategy. The unique hierarchical porous structure of HTCTs/Co/CNTs not only increases the sulfur loading and alleviates the volume expansion, but also effectively suppresses the shuttling effect of LiPSs through the synergism between physical confinement and chemical adsorption. It is revealed that the combination of Ti3C2Tx MXene and metallic Co enhances the LiPSs absorbability and accelerates the catalytic conversion of sulfur species, thereby improving sulfur utilization and electrochemical reversibility. The corresponding cells with HTCTs/Co/CNTs/S cathode retain high capacities of 901.9 mAh g−1 after 100 cycles at 0.2 C and 725.9 mAh g−1 after 500 cycles at 1.0 C. More importantly, a high areal capacity of 4.83 mAh cm−2 is achieved under a high sulfur loading of 5.8 mg cm−2 and a low E/S ratio of 4.3 µL mg−1 after 50 cycles at 0.1 C.

Experimental study of the effect of different pulse charging patterns on lithium-ion battery charging

This study aims to experimentally investigate the impact of different pulse charging patterns on the charging time and performance of lithium-ion batteries at room temperature. Experimental results indicate that most pulse charging protocols have a positive impact on shortening the total charging time compared to the CC-CV charging method with the same input charge capacity. This effect is observed not only in LFP batteries but also in NMC batteries. Three pulse charging patterns are studied: constant current charge (C–C), charge rest (C–R), and charge discharge (C-D). The C-D mode results in the shortest charging time and the smallest cell internal resistance. Compared to the 1C CC-CV baseline, the pulse C-D mode reduces the charging time by approximately 6.8 %, decreases the average pulse internal resistance by about 17.5 %, and increases the remaining discharge capacity ratio by 3.76 % after 800 cycles. Additionally, a pseudo-2D physics model is used to study the internal effects on the battery using the pulse C-D mode. The results show that using the pulse charging method (C-D) results in a more even distribution of electrolyte salt concentration and electrode particle lithium concentration across the cell, thereby improving battery performance.

Improving the Rechargeable Li-CO2 Battery Performances by Tailoring Oxygen Defects on Li-Ni-Co-Mn Multi-Metal Oxide Catalysts Recycled from Spent Ternary Lithium-Ion Batteries.

Rechargeable Li-CO2 batteries are considered as a promising carbon-neutral energy storage technology owing to their ultra-high energy density and efficient CO2 capture capability. However, the sluggish CO2 reduction/evolution kinetics impedes their practical application, which leads to huge overpotentials and poor cyclability. Multi-element transit metal oxides (TMOs) are demonstrated as effective cathodic catalysts for Li-CO2 batteries. But there are no reports on the integration of defect engineering on multi-element TMOs. Herein, the oxygen vacancy-bearing Li-Ni-Co-Mn multi-oxide (Re-NCM-H3) catalyst with the α-NaFeO2-type structure is first fabricated by annealing the NiCoMn precursor that derived from spent ternary LiNi0.8Co0.1Mn0.1O2 cathode, in H2 at 300°C. As demonstrated by experimental results and theory calculations, the introduction of moderate oxygen vacancy has optimized electronic state near the Fermi level (Ef), eventually improving CO2 adsorption and charge transfer. Therefore, the Li-CO2 batteries with Re-NCM-H3 catalyst deliver a high capacity (11808.9 mAh g-1), a lower overpotential (1.54V), as well as excellent stability over 216 cycles at 100mA g-1 and 165 cycles at 400mA g-1. This study not only opens up a sustainable application of spent ternary cathode, but also validates the potential of multi-element TMO catalysts with oxygen defects for high-efficiency Li-CO2 batteries.

The Effect of Battery Configuration on Dendritic Growth: A Magnetic Resonance Microscopy Study on Symmetric Lithium Cells

The potential of metallic lithium to become the anode material for next-generation batteries is hampered by significant challenges, chief among which is dendrite growth during battery charging. These dendritic structures not only impair battery performance but also pose safety risks. Among the non-destructive analytical techniques in battery research, Magnetic Resonance Imaging (MRI) stands out as a promising tool. However, the direct imaging of lithium by 7Li MRI is limited by its low sensitivity and spatial resolution, making it a less effective way of imaging dendrite growth. Instead, a recently introduced indirect imaging approach which is based on 1H MRI of the electrolyte was used in this study. This method was used to sequentially 3D image and thus monitor the charging process of lithium metal symmetric cells in three different electrical circuits, namely those composed of a single cell, four cells in parallel, and four cells in series. The measured sequential images allowed for the measurement of dendrite growth in each cell using volumetric analysis. The growth results confirmed the theoretical prediction that the growth across cells is uneven in a parallel circuit, and even in a series circuit. The methods presented in this study can also be applied to analyze many other dendrite-related issues in batteries.