Battery Operation Research Articles

A novel linear programming-based predictive control method for building battery operations with reduced cost and enhanced computational efficiency

Battery energy storage systems can be readily integrated with buildings to enhance renewable energy self-consumptions while leveraging time-variant electricity tariffs for possible operation cost reductions. The extensive variability in building operating conditions presents significant challenges in developing universally applicable methods for optimal controls. To ensure reliable and robust controls, this study integrates predictive control with efficient linear programming to effectively fine-tune battery controls for real-time operations. An adaptive time aggregation scheme has been proposed to streamline the optimization process by accounting for unique changes in energy balances and tariffs. Comprehensive data experiments, based on measurements from 95 unique building operation scenarios, have been conducted to quantify the control performance given different optimization formulations, varying types and levels of prediction uncertainties in building energy demands and PV generations. The results validate the value of the method proposed, leading to 11.75% to 34.63% operation cost reductions on average, while reducing computation steps by 87.75% to 92.60% compared with conventional linear programming approaches. The insights obtained are useful for developing flexible building control strategies with improved computation efficiency and robustness, while providing extensible optimization frameworks for buildings with various energy patterns and storage systems.

State of Charge Prediction of Mine-Used LiFePO4 Battery Based on PSO-Catboost

The accurate prediction of battery state of charge (SOC) is one of the critical technologies for the safe operation of a power battery. Aiming at the problem of mine power battery SOC prediction, based on the comparative experiments and analysis of particle swarm optimization (PSO) and Categorical Boosting (Catboost) characteristics, the PSO-Catboost model is proposed to predict the SOC of a power lithium iron phosphate battery. Firstly, the classification model based on Catboost is constructed, and then the particle swarm algorithm is used to optimize the Catboost hyperparameters to build the optimal model. The experiment and comparison show that the optimized model’s prediction accuracy and average precision are superior to other comparative models. Compared with the Catboost model, the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values of the PSO-Catboost model decreased by 12.4% and 25.4% during charging and decreased by 5.5% and 12.2% during discharging. Finally, the Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models, both ensemble learning models, are selected and compared with PSO-Catboost after being optimized via PSO. The experimental results show that the proposed model has a better performance. In this paper, experiments show that the optimization model can select parameters more intelligently, reduce the error caused by artificial experience to adjust parameters, and have a better theoretical value and practical significance.

Sustainable Solid-State Sodium-Ion Batteries Featuring Ferroelectric Electrolytes

Solid-state batteries offer significant advantages but present several challenges. Given the complexity of these systems, it is good practice to begin the study with simpler models and progressively advance to more complex configurations, all while maintaining an understanding of the physical principles governing solid-state battery operation. The results presented in this work pertain to cells without traditional electrodes, thus providing a foundation for guiding the development of fully functional solid-state cells. The open circuit voltage (OCV) of the Cu/Na2.99Ba0.005ClO composite in a cellulose/Zn pouch cell achieves 1.10 V, reflecting the difference in the chemical potentials of the current collectors (CCs), Zn and Cu, serving as electrodes. After 120 days, while set to discharge, conversely to what was expected, a higher potential difference of 1.13 V was attained (capacity of 5.9 mAh·g−1electrolyte). By incorporating a layer of carbon felt, the OCV became 0.85 V; however, after 95 days, the potential difference increased to 1.20 V. Ab initio simulations were additionally performed on a Cu/Na3ClO/Zn heterojunction showing the formation of dipoles and the Na deposition on Zn which is demonstrated experimentally. The sodium plating on the negative CC (Zn) takes place as the cell is set to discharge at room temperature but is not observed at 40 °C.

Optimization of Thermal Non-Uniformity Challenges in Liquid-Cooled Lithium-Ion Battery Packs Using NSGA-II

Abstract Heat removal and thermal management are critical for the safe and efficient operation of lithium-ion batteries and packs. Effective removal of dynamically generated heat from cells presents a substantial challenge for thermal management optimization. This study introduces a novel liquid cooling thermal management method aimed at improving temperature uniformity in a battery pack. A complex nonlinear hybrid model is established through traditional full-factor design and back propagation neural network (BPNN) approximation. This model links input parameters such as the number of baffles, baffle angle, and inlet speed to output parameters including maximum temperature, temperature difference, and pressure drop. Global multiobjective optimization is carried out using the Nondominated Sorting Genetic Algorithm II to sidestep locally optimal solutions. Pareto optimal solutions are sorted using multiple criteria decision-making techniques. Through thermal management optimization, the maximum temperature rise of the battery relative to the initial temperature is controlled within 7.68 K, the temperature difference is controlled within 4.22 K (below the commonly required 5 K), and the pressure drop is only 83.92 Pa. Results presented in this work may help enhance the performance and efficiency of battery-based energy conversion and storage. The optimization technique used in this work helps maximize the benefit of an innovative battery thermal management technique.

Optimal battery management in PV + WT micro-grid using MSMA on fuzzy-PID controller: a real-time study

In modern energy systems, managing energy within a microgrid (MG) poses significant challenges due to the unpredictable nature of renewable energy sources. This article introduces a novel approach for optimal battery management in a photovoltaic–wind microgrid using a Modified Slime Mould Algorithm (MSMA) combined with a fuzzy-PID controller. The microgrid comprises a wind turbine (WT) generator, solar photovoltaic (PV) generator, and a battery energy storage system (BESS). The BESS plays a crucial role in meeting high power demand during outages, while the fuzzy-PID controller ensures accurate prediction of the battery’s state of charge (SOC). The proposed method’s performance is evaluated by comparing the MSMA-based fuzzy-PID controller with a PSO-based fuzzy-PID controller to establish its effectiveness. The optimal energy management of the BESS in the microgrid is achieved by fine-tuning the fuzzy-PID controller using the MSMA algorithm. Simulation results demonstrate that the battery management system (BMS) effectively optimizes charging and discharging based on renewable energy availability and load demand. The fuzzy-PID controller adjusts battery operation by minimizing the error between the desired and actual battery voltage. Performance validation has been conducted in RTS-lab using five distinct load scenarios—45 kW, 35 kW, 75 kW, 4.5 kW, and 12.5 kW, which confirming the effectiveness of the proposed control strategy for energy management.

Experimental study on creep characteristics of electrolyte-bearing salt rock under long-term triaxial cyclic loading

During the operation of the Salt Cavern Flow Battery (SCFB) system, the rock surrounding a salt cavern is subjected to erosion by the electrolyte. To study the creep characteristics of electrolyte-bearing salt rock under long-term triaxial cyclic loading in SCFB, a triaxial creep experiment with a cycle period of 1 day was conducted. The results indicated that, when not subjected to failure, the axial stress-strain curve of electrolyte-bearing sample undergoes only two phases of “sparse-dense”, entering dense phase approximately 4 cycles earlier than that of sample without electrolyte. Under the same stress conditions, the strain generated in electrolyte-bearing salt rock surpasses that of sample without electrolyte, demonstrating an initial rapid increase followed by a gradual stabilization trend. The stress-strain curve of electrolyte-bearing sample in a single cycle can be divided into six stages. The number of cycles has almost no effect on the axial strain in stages I, IV, V and VI, and the axial strain in stages IV and VI is basically 0. Additionally, the elastic deformation generated in stage I is basically recovered in stage V. The strain in stage II gradually decreases and disappears in the 4th cycle, which is 13 cycles earlier than that of the sample without electrolyte. The creep rate of electrolyte-bearing sample shows a trend of “gradual decrease—basically stabilization” as the number of cycles increases, and the creep experiment contains only the decay creep stage and steady creep stage. Irreversible deformation of electrolyte-bearing sample exhibits a gradual decrease followed by stabilization with increasing number of cycles. The research findings hold significant implications for the stability analysis of SCFB systems.

Tailoring superstructure units for improved oxygen redox activity in Li-rich layered oxide battery’s positive electrodes

The high-voltage oxygen redox activity of Li-rich layered oxides enables additional capacity beyond conventional transition metal (TM) redox contributions and drives the development of positive electrode active materials in secondary Li-based batteries. However, Li-rich layered oxides often face voltage decay during battery operation. In particular, although Li-rich positive electrode active materials with a high nickel content demonstrate improved voltage stability, they suffer from poor discharge capacity. Here, via physicochemical and electrochemical measurements, we investigate the correlation between oxygen redox activity and superstructure units in Li-rich layered oxides, specifically the fractions of LiMn6 and Ni4+-stabilized LiNiMn5 within the TM layer. We prove that an excess of LiNiMn5 hinders the extraction/insertion of lithium ions during Li metal coin cell charging/discharging, resulting in incomplete oxygen redox activity at a cell potential of about 3.3 V. We also demonstrate that lithium content adjustment could be a beneficial approach to tailor the superstructure units. Indeed, we report an improved oxygen redox reversibility for an optimized Li-rich layered oxide with fewer LiNiMn5 units.

Reconfiguring the Coordination Structure in Deep Eutectic Electrolytes for Enabling Stable Operation of Zinc-Ion Batteries.

Highly stable aqueous Zn-ion batteries are of great importance for commercial applications. The challenging issues of interfacial side reactions and rampant dendrite growth cause short circuit and premature failure of aqueous Zn-ion batteries. Herein, a hydrated deep eutectic electrolyte is formulated to tackle such problems, which adopts 1,3-propanediol as a cosolvent. 1,3-Propanediol molecules can enter into the Zn2+ solvation structure to from a lean-water electrolyte and drastically diminish the activity of water molecules through reinforcing the hydrogen bond network. Meanwhile, PDO molecules exclude the neighboring water to modulate the electric double layer configuration, thus impeding water-mediated side reactions and inducing an inorganic-rich interphase. Consequently, this hydrated deep eutectic electrolyte ensures long-term stability of Zn-Zn, Zn-Cu, and Zn-I2 cells. The favorable influence exerted by PDO molecules provides the guidance for constructing high-performance aqueous Zn-ion batteries.

High‐Safety Lithium Metal Batteries Enabled by Additive of Fire‐Extinguishing Microcapsules

ABSTRACTLithium metal battery (LMB) is regarded as one of the most promising high‐energy energy storage systems. However, the high reactivity of lithium metal and the formation of lithium dendrites during battery operation have caused safety concerns. Herein, we present the design and synthesis of fire‐extinguishing microcapsules to enhance LMB safety. The encapsulation strategy addressed perfluoro(2‐methyl‐3‐pentanone)'s volatility and storage challenges, yielding microcapsules with stable and uniform size distributions. The rapid release and effective fire‐extinguishing performance of the microcapsules upon exposure to high temperatures has been demonstrated. Integration of these microcapsules into LMBs showed no significant impact on electrochemical performance, maintaining high lithium‐ion conductivity, and stable cycling capacity. Notably, practical safety tests on pouch cells indicated that the presence of microcapsules effectively prevented ignition and improved thermal stability under mechanical damage and flame intrusion, underscoring their potential for significantly improved battery safety. These findings provide a robust strategy for mitigating fire hazards of high‐energy‐density battery systems without compromising their electrochemical performances.

On the Thermal Conductivity and Local Lattice Dynamical Properties of NASICON Solid Electrolytes.

The recent development of solid-state batteries brings them closer to commercialization and raises the need for heat management. The NASICON material class (Na1+xZr2PxSi3-xO12 with 0 ≤ x ≤ 3) is one of the most promising families of solid electrolytes for sodium solid-state batteries. While extensive research has been conducted to improve the ionic conductivity of this material class, knowledge of thermal conductivity is scarce. At the same time, the material's ability to dissipate heat is expected to play a pivotal role in determining efficiency and safety, both on a battery pack and local component level. Dissipation of heat, which was, for instance, generated during battery operation, is important to keep the battery at its optimal operating temperature and avoid accelerated degradation of battery materials at interfaces. In this study, the thermal conductivity of NaZr2P3O12 and Na4Zr2Si3O12 is investigated in a wide temperature range from 2 to 773 K accompanied by in-depth lattice dynamical characterizations to understand underlying mechanisms and the striking difference in their low-temperature thermal conductivity. Consistently low thermal conductivities are observed, which can be explained by the strong suppression of propagating phonon transport through the structural complexity and the intrinsic anharmonicity of NASICONs. The associated low-frequency sodium ion vibrations lead to the emergence of local random-walk heat transport contributions via so-called diffusons. In addition, the importance of lattice dynamics in the discussion of ionic transport as well as the relevance of bonding characteristics typical for mobile ions on thermal transport, is highlighted.

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.

Result-Adaptive PID Control Based Ant Colony Optimization Tuning for Battery Operation Control in Standalone PV System With Consumption Side Power Management

Result-Adaptive PID Control Based Ant Colony Optimization Tuning for Battery Operation Control in Standalone PV System With Consumption Side Power Management

"Anchoring Capture" Effect Mimicking Proline in Hardy Deep-Sea Fish to Stabilize the Zinc Anode with Lower Operating Temperature.

The low plating/stripping efficiency of zinc anodes, dendrite growth, and high freezing points of aqueous solutions hinder the practical application of aqueous zinc-ion batteries. This paper proposes a zwitterionic permeable network solid-state electrolyte based on the "anchor-capture" effect to address these problems by incorporating proline (Pro, a biological antifreeze agent) into the electrolyte. Extensive validation tests, Quantum Chemistry (QC) calculations, Molecular Dynamics (MD) Simulations, and ab initio molecular dynamics simulations consistently indicate that the amino groups in proline adsorb onto the Zn metal surface, stabilizing the zinc anode-electrolyte interface, suppressing side reactions from water decomposition, and homogenizing zinc-ion flux. This electrolyte demonstrates excellent reversibility in Zn-Mn2O3 cells and Zn-Zn half-cells, achieving a high coulombic efficiency of over 99.4% across 2000 cycles in Zn-Mn2O3 full cells, and delivering a discharge-specific capacity of 175.2 mAhg-1 at -35°C and 1 Ag-1. Additionally, an appropriate concentration of proline lowers the electrolyte's freezing point to -45°C through the network's solid-state effect, ensuring the stable operation of the solid-state battery at -35°C. This innovative concept of network solid-state electrolytes injects new vitality into the development of multifunctional solid-state electrolytes.

Evaluation of the effectiveness of a firing battery in self-defense and protection in the area of firing positions using constructive simulation

The paper describes the results of an experiment based on the use of constructive simulation in the MASA SWORD environment to verify the ability of an artillery firing battery to provide self-defense and protection in the firing position area and to perform the firing task when different types of adversary attack the firing position area. The objective of the experiment is to verify the ability of the artillery battery to survive within the Artillery Reserved Areas/Artillery Maneuver Areas (ARA/AMA) while performing combat tasks and the necessity of allocating additional resources (equipment, personnel, material) to protect and defend the firing position area and the artillery firing unit assets operating within it. The experiment results are the initial basis for follow-on simulations that will assess the impact on the ability to accomplish an artillery battery operation’s planned and unplanned joint fire support tasks.

Electrostatic Shielding Engineering for Stable Zn Metal Anodes

AbstractAqueous Zn‐ion batteries (AZIBs) are promising energy storage systems due to their low cost, excellent safety, and environmental friendliness. However, challenges like uncontrollable dendrite growth and side reactions during battery operation limit their commercialization. Addressing these issues requires regulating ion deposition behavior at the anode/electrolyte interface. The electrostatic shielding effect, which leverages the interplay between electric potential and ionic motion, provides a unique mechanism to inhibit zinc dendrites and side reactions effectively. Despite significant progress in understanding electrostatic shielding in AZIBs, a comprehensive summary of its effects is still lacking. This paper first reviews the primary challenges in AZIBs and then describes how the electrostatic shielding effect can optimize their performance. Existing strategies for achieving electrostatic shielding through anode structure optimization and electrolyte optimization‐are classified and analyzed. Finally, the review summarizes current electrostatic shielding strategies for stabilizing zinc anodes, identifies existing challenges, and discusses the future potential, and for this approach in AZIBs.

Enhanced Na-Ion Electrochemical Performance through Cu Doping-Mediated Sb2Se3 Phase Transformation into CuSbSe2 with Improved Kinetics.

This work investigates the influence of structural and electronic modification on the electrochemical performance of conversion and alloying materials. The CuSbSe2, a promising 2D layered conversion-and-alloying material is being investigated with references to parent pristine Sb2Se3 and a doped version of later Sn0.2Sb1.8Se3 for their sodium-ion battery performance. The CuSbSe2 with layered structure is well known to accommodate lattice distortions via inter-layer movement, potentially mitigating distortions brought about by the Alkali ion (Na in this case) insertion. In contrast, the parent conversion-cum-alloying material Sb2Se3 with its one-dimensional crystal structure leads to structural disintegration during battery operation. The Sn-doped analog, Sn0.2Sb1.8Se3, comparatively exhibits enhanced kinetics owing to the reduced long-range order. The 2D layered, CuSbSe2 despite exhibiting2D long-range order exhibits superior electrochemical performance owing to the favorable electronic and structural features. The CuSbSe2 exhibits a reversible capacity of 881 mAh g-1 compared to 516 mAh g-1 for Sn0.2Sb1.8Se3 and 429 mAh g-1 for Sb2Se3, with an improved Coulombic efficiency as well. The transient electrochemical investigations of Electrochemical Impedance Spectroscopy (EIS) and Galvanostatic intermittent titration techniques (GITT) reveal that better performance exhibited by CuSbSe2 may well be attributed to kinetics owing to enhanced diffusion coefficients in the intercalation and conversion regime.

Rational design of alginate-derived network binder for high-performance silicon-based anodes in Li-ion batteries

This study developed a novel alginate-derived network binder, SAH, to enhance the performance and stability of silicon-based anodes in lithium-ion batteries. Integrating acrylic acid and 2-hydroxyethyl acrylate with sodium alginate through a one-pot polymerization and in-situ cross-linking method, SAH effectively addresses the volumetric expansion challenges associated with silicon anodes. This innovative binder maintains the structural integrity of the silicon anode through its rigid acrylic acid component, while the flexible acrylic-2-hydroxyethyl ester serves as a dynamic buffer to enhance flexibility. Sodium alginate contributes its intrinsic beneficial properties and imparts a robust three-dimensional network structure through effective coupling, allowing the binder to accommodate silicon volume changes during battery operation. Consequently, lithium-ion batteries incorporating this binder exhibited improved stability and extended cycle life, achieving an impressive capacity retention rate of 87.3 % after 100 cycles at 0.5C. This study highlights the potential of biopolymeric materials in enhancing the functionality of silicon-based anodes, contributing to the ongoing development of high-performance energy storage technologies.

A hybrid physical modeling and AUKF approach for optimizing low-temperature charging of lithium-ion batteries

A common method for charging lithium-ion batteries at low temperatures involves preheating to mitigate low charging efficiency and safety risks from lithium dendrite growth. However, preheating alone is insufficient for rapid and safe charging. Optimization of low temperature charging requires consideration of the coupling relationship between heating and charging processes, while avoid lithium plating. Therefore, this study first constructs an electrochemical-thermal coupled model suitable for a broad temperature range to access the internal states of battery during low-temperature charging, ensuring lithium plating-free. Then, a hybrid physical modeling and AUKF method is proposed to accurately capture the changing state of charge (SOC) and state of temperature (SOT) during low-temperature charging, which is essential to improve the simulation accuracy of the model. After that, this study proposes a multi-stage heating-charging strategy which is controlled by hybrid physical modeling and AUKF approach to consider charging efficiency and safety. Optimization algorithm is used to obtain the optimal sequence of decisions for charging and heating under different phases to achieve the highest charging efficiency. Compared to One-stage heating-charging strategy, the proposed method offers superior charging efficiency, providing certain convenience for the operation of lithium-ion batteries in low temperature environment.

A Hybrid Electrochemical Multi-Particle Model for Li-ion Batteries

Physics-based models have proven to be effective tools for predicting the electrochemical behavior of Li-ion batteries. Among the various physics-based models, the Doyle-Fuller-Newman (DFN) model has emerged as the most widely employed. In response to certain limitations of the DFN model, the multiple particle-Doyle-Fuller-Newman (MP-DFN) model was introduced. The MP-DFN model utilizes multiple electrode particle sizes, addressing internal concentration heterogeneities and more realistically simulate diffusion processes in the electrodes. However, the model requires relatively high computational cost. This work introduces the Padé approximation for the MP-DFN model, resulting in the simplified MP-DFN model, leading to a faster simulation time. However, depending on battery design and operation conditions, this solution shows to have lower accuracy compared to the MP-DFN. To overcome these challenges, this study also introduces a hybrid MP-DFN model. This model uses a novel approach aimed at striking a balance between accuracy and computational speed. The hybrid MP-DFN model integrates both the finite difference method (FDM) and Padé approximation to effectively address the challenges posed by multiple particle sizes within the electrodes. The choice between FDM or the approximations for a specific particle in the electrode is determined by the scaled diffusion length.

In-situ detection of electrolyte defects in lithium-ion batteries using ultrasonic imaging and analysis of formation patterns

The urgent necessity for enhanced cycling performance in lithium batteries is paramount for electric vehicles to attain broader economic advantages. However, prolonged usage and cycling often lead to electrolyte de-wetting within the battery, posing a significant risk to battery safety and lifespan reduction. A thorough understanding of the mechanisms underlying electrolyte de-wetting is pivotal for the development of long-lasting batteries. This study employs an ultrasonic non-destructive testing method to investigate changes in the internal electrolyte during battery operation. Analysis of the results found that during to the relatively higher current density and temperature near the tabs, electrolyte de-wetting is more prone to occur in these areas, with defects being more severe at the positive electrode compared to the negative electrode. Finally, these issues are addressed to provide reasonable recommendations for future battery design and optimization.