Charge Rate Research Articles

Numerical computations on thermal performance of large-scale Ti-Mn-based metal hydride storage reactor via open source CFD software

Certain metals and metal alloys can absorb hydrogen through an exothermic chemical reaction, resulting in the formation of metal hydrides. To maintain a rapid charging rate, the produced heat must be extracted as rapidly as it is generated. This study was attempted to evaluate the heat transfer enhancement in a cylindrical hydrogen storage reactor equipped with a central tube for large-scale applications using a 3D transient model. Finite-volume simulations are carried out using the open-source software package OpenFOAM to systematically investigate the impacts of material thermophysical properties, cooling media, and heat exchanger design on the heat transfer behaviors and hydrogen storage rate. The reactor’s performance was evaluated in terms of temperature and total hydrogen mass history profiles, in addition to pressure drop. The findings indicated that the charging time was improved by roughly 86%, compared to the case without thermal enhancement to attain 90% hydrogen storage capacity. A diminished pressure drop was observed between the water-based Al2O3 nanofluid with 5 vol% concentration and pure water at lowered coolant flow velocities, hence enhancing pumping power efficiency. Moreover, the results demonstrated that the storage rate is markedly improved by enhancing the effective thermal conductivity of the hydride bed, increasing the heat exchange area, accelerating the coolant flow rate, and lowering its temperature. The outcomes highlighted the possibility of advancing the current metal hydride reactor for practical application.

Test particles in Kaluza-Klein models

Abstract Geodesics in general relativity describe the behaviour of test particles in a gravitational field. In 5D Kaluza-Klein, geodesics reproduce the Lorentz force motion of particles in an electromagnetic field. This paper studies geodesic motion on a higher-dimensional M4 × K with background metrics encoding general 4D gauge fields and Higgs-like scalars. It shows that the classical mass and charge of a test particle become variable quantities when the geodesic traverses regions of spacetime with massive gauge fields, such as the weak force field, or with non-constant Higgs scalars. This agrees with the physical fact that interactions mediated by massive bosons can change the mass and charge of particles. The variation rates of mass and charge along a geodesic are given by natural geometric formulae. In regions where mass is preserved, there are additional constants of motion, one for every abelian or simple summand in the Killing algebra of K. The last part of the paper discusses traditional difficulties of Kaluza-Klein models, such as the low q/m ratios in the 5D model. It suggests possible ways to circumvent them. It also remarks the naturalness of a model where elementary particles always travel at the speed of light in higher dimensions.

SOC and SOH Prediction of Lithium‐Ion Batteries Based on LSTM–AUKF Joint Algorithm

ABSTRACTLithium batteries are increasingly favored for energy storage due to their high energy density, long cycle life, and robust charge and discharge rates. However, safety concerns necessitate the implementation of a battery management system (BMS) to monitor battery status, maintain energy balance, and provide failure warnings to ensure safe operation. This paper proposes an efficient BMS for high‐voltage, high‐current lithium battery energy storage. The approach leverages a multihead‐attention‐enhanced long short‐term memory (LSTM) neural network combined with an adaptive unscented Kalman filter to accurately calculate the battery's state of charge (SOC) and state of health (SOH). To improve accuracy, various factors such as temperature and internal resistance were considered. The algorithm was validated through hardware and simulation experiments, with experimental data compared to estimation results to demonstrate its precision. The findings show strong convergence and tracking capabilities, with SOC estimation presenting a maximum error of 1.5% and SOH estimation a maximum error of under 0.4%. We expect that this approach will allow for a more refined evaluation of SOC and SOH in lithium‐ion batteries, potentially improving Li‐ion battery system management.

Application of ion modification for alteration of anode materials based on ZnO/CoZn nanostructures

During the conducted studies, it was established that the use of ion modification by irradiation with O+ and Ar+ ions makes it possible to elevate the degradation resistance of anode materials due to the effect of vacancy defect creation, the density of which varies with the irradiation fluence. At the same time, the analysis of changes in the band gap and the optical density value, expressing changes in structural distortions, revealed that ion irradiation leads to a rise in the stability of the preservation of electronic properties during long-term resource tests, which are inextricably linked with the degradation of ZnO/CoZn nanostructures due to oxidation processes as a result of lithiation. During assessment of changes in the parameters of the band gap and optical density of the samples after resource tests, it was found that the observed growth in these indicators is due to oxidation processes and partial amorphization due to the formation of oxide inclusions in the structure of nanowires, the presence of which is due to the interaction of nanostructures with the electrolyte over a long period of time during charging/discharging, which results in near-surface layer degradation due to the introduction of oxygen, and in the case of a long service life, to the formation of oxide inclusions that elevate the density of defects and vacancies in the structure. According to tests of synthesized ZnO/CoZn nanostructures as anode materials, it was found that the use of O+ and Ar+ ions not only leads to a growth in the degradation resistance of capacitive characteristics during long-term tests, but also to the stability maintenance of indicators with a reversible decrease in the charging rate at charging rate variation.

Experimental investigation on the performance of a borehole thermal energy storage system based on similarity and symmetry

Although Borehole Thermal Energy Storage (BTES) technology has achieved significant progress in feasibility and sustainable energy integration, high heat loss and long preheating periods still strongly restrict its charging and storage performance. This investigation designed and constructed a laboratory-scale BTES sandbox based on similarity and symmetry principles. Detailed monitoring of sand temperature data and boundary conditions validated the effectiveness of the symmetrically simplified similarity experiment. The data comprehensively reflected the change of underground temperature fields during the charging and seasonal storage phases. The reasons for the performance limitations of BTES are thereby analyzed. During the charging phase, the prototype BTES achieved its highest average charging rate of 220W within the first 21 days, and the temperature field stabilized after 192 days. In the storage phase, the exergy destruction losses of BTES primarily occurred at the junction between the core and peripheral zones, accounting for 56 % of the total losses. An effective method to enhance BTES performance is to reconfigure the borehole layout and operation, which improves the uniformity and continuity of the underground temperature field. The experimental measurement provides fundamental data for the integrated seasonal utilization of heating and cooling, which can be essential for innovative building energy systems.

Exploring the Impact of Battery Charge Reduction Rate and the Placement of Chargers on AGV Operation

This paper presents a simulation model to study the effect of the battery charging rate of Automated Guided Vehicles (AGVs) on the overall output of a toy car production environment. This paper uses Modular Petri Nets for modeling and the General Petri Net Simulator (GPenSIM) for model implementation on MATLAB and simulation. The main focus of this paper is to analyze the operational efficiency of AGVs under varying conditions, such as the impact of battery charge reduction rates and the strategic placement of Charging Stations within the production line. By employing Modular Petri Nets implemented with GPenSIM, this paper presents a detailed model that captures the dynamics (movements and interactions) of AGVs in a simulated manufacturing environment. The model is also extensible, as newer functionalities can be added to it as Petri Modules. This paper specifically focuses on two critical operational parameters: (a) the number of AGVs and their battery charge reduction rate; (b) the number of Charging Stations. In summary, the goal, aim, and novelty of this paper is to provide a simpler yet effective model to practitioners so that they can study and experiment without needing advanced mathematical skills.

Revealing how internal sensors in a smart battery impact the local graphite lithiation mechanism

Smart batteries, i.e., equipped with internal and external sensors, are emerging as promising solutions to enhance battery state of health and optimize operating conditions. However, for accurate correlations between the evolution of the cell parameters (e.g., temperature, strain) and physicochemical degradation mechanisms, it is crucial to know the reliability of sensors. To address this question, we perform a synchrotron operando X-ray diffraction experiment to investigate the local and global impact of the presence of internal sensors on a commercial prismatic Li-ion battery cell at various (dis)charge rates. We find that, while the overall electrochemical performance is unaffected, the sensors have a substantial impact on the local graphite lithiation kinetics, especially at high (dis)charge rates. These results show the importance of controlling local deformations induced by internal sensors and tailoring the dimensions of these sensors to obtain reliable battery performance indicators and optimize smart batteries.

Deep P‐C Interface Reconstruction for High‐Performance Potassium Storage

AbstractPotassium‐ion batteries (PIBs) capable of achieving full charge in minutes, or even in seconds, while maintaining high energy densities, are highly desirable for practical applications. However, significant challenges exist in developing electrodes that can sustain both high capacity and rapid charging rates. Conventional phosphorus‐carbon composites, limited by the intrinsic common carbon materials structure, often fail to prevent the edges reconstruction of black phosphorus (BP), thereby limiting its potential advantages as a high‐capacity, high‐rate anode. This study addresses these challenges by grafting BP onto a super‐porous carbon (SPC) framework to serve as an anode for potassium storage. The large number of open pores in SPC ensures the uniform distribution of BP nanoparticles in this carbon matrix, realizing the complete potassiation reactions and uniform volumetric strain dispersion. The abundant defects significantly promote the phosphorus‐carbon reconstruction between edge carbon atoms and edge phosphorus atoms, effectively inhibiting the P‐P edge reconstruction of BP to ensure open edges for rapid K+ diffusion. As a result, the composite exhibits excellent performance in potassium storage, demonstrating superior capacity, charging rates, and cycling durability. This research provides a new insight into enhancing BP‐base anodes, offering favorable guidance for the development of high‐performance materials.

Superionic conducting vacancy-rich β-Li3N electrolyte for stable cycling of all-solid-state lithium metal batteries.

The advancement of all-solid-state lithium metal batteries requires breakthroughs in solid-state electrolytes (SSEs) for the suppression of lithium dendrite growth at high current densities and high capacities (>3 mAh cm-2) and innovation of SSEs in terms of crystal structure, ionic conductivity and rigidness. Here we report a superionic conducting, highly lithium-compatible and air-stable vacancy-rich β-Li3N SSE. This vacancy-rich β-Li3N SSE shows a high ionic conductivity of 2.14 × 10-3 S cm-1 at 25 °C and surpasses almost all the reported nitride-based SSEs. A Li- and N-vacancy-mediated fast lithium-ion migration mechanism is unravelled regarding vacancy-triggered reduced activation energy and increased mobile lithium-ion population. All-solid-state lithium symmetric cells using vacancy-rich β-Li3N achieve breakthroughs in high critical current densities up to 45 mA cm-2 and high capacities up to 7.5 mAh cm-2, and ultra-stable lithium stripping and plating processes over 2,000 cycles. The high lithium compatibility mechanism of vacancy-rich β-Li3N is unveiled as intrinsic stability to lithium metal. In addition, β-Li3N possesses excellent air stability through the formation of protection surfaces. All-solid-state lithium metal batteries using the vacancy-rich β-Li3N as SSE interlayers and lithium cobalt oxide (LCO) and Ni-rich LiNi0.83Co0.11Mn0.06O2 (NCM83) cathodes exhibit excellent battery performance. Extremely stable cycling performance is demonstrated with high capacity retentions of 82.05% with 95.2 mAh g-1 over 5,000 cycles at 1.0 C for LCO and 92.5% with 153.6 mAh g-1 over 3,500 cycles at 1.0 C for NCM83. Utilizing the vacancy-rich β-Li3N SSE and NCM83 cathodes, the all-solid-state lithium metal batteries successfully accomplished mild rapid charge and discharge rates up to 5.0 C, retaining 60.47% of the capacity. Notably, these batteries exhibited a high areal capacity, registering approximately 5.0 mAh cm-2 for the compact pellet-type cells and around 2.2 mAh cm-2 for the all-solid-state lithium metal pouch cells.

The Impact of Microstructure Variation on Lithium-Ion Battery Charging Capability

As electrification of the automotive industry progresses, there is an increasing consumer desire to reduce charge times and increase power and energy density of electric vehicles1. However, fast charge rates induce large gradients across the electrochemical components of these battery electrodes and can lead to adverse impacts2 at the active material and electrode level. Particularly at high states of charge, local anode potentials can drop significantly below the equilibrium potential3, and due to the proximity of the graphite equilibrium potential4,5 to 0V vs metallic Li at high states of lithiation, a risk that the anode potential drops below 0.0 V vs lithium metal exists, which can drive lithium plating on the active material2, reducing the electrochemically active surface area, impacting performance and heat generation6, and impacting lithium salt concentration present in the electrolyte. By using electrochemical simulations, the onset of lithium plating can be predicted and used to set charging guidelines to reduce the risk of lithium plating. The pseudo-two-dimensional (P2D) model7–9 is a popular modeling method for capturing this behavior. With many effective media assumptions present translated to an average continuum impact, the P2D model can simulate rapid charge and capture a global equivalent onset of lithium plating for the anode. However, the P2D model lacks the ability to resolve any localized behaviors across the individual components due to local non-uniformities, as variation in the through plane direction only represents an average value across a slice of the full domain. Lopata10 developed a three-dimensional microstructure based (3DMS) modeling method, we employ here to simulate rapid charge events and capture what occurs locally across the electrochemical components while broadly agreeing with the established P2D’s model results. With the 3DMS model, we are able to better predict the onset of local lithium plating and can use this knowledge to design more conservative charging conditions to delay the onset of lithium plating and improve the performance of these electrochemical systems. In this work, several similar microstructures are evaluated to determine the variation of the lithium plating onset time during fast charge operation. A small normal distribution for particle sizes are explored to drive variation in performance and are compared to a uniform particle size structure. References T. R. Garrick, Y. Zeng, J. B. Siegel, and V. R. Subramanian, J. Electrochem. Soc., 170, 113502 (2023). U. Janakiraman, T. R. Garrick, and M. E. Fortier, J. Electrochem. Soc., 167, 160552 (2020). T. R. Garrick, J. Gao, X. Yang, and B. J. Koch, J. Electrochem. Soc., 168, 010530 (2021). T. R. Garrick et al., J. Electrochem. Soc., 170, 060548 (2023). A. Paul et al., J. Electrochem. Soc., 171, 023501 (2024). M. Song, Y. Hu, S.-Y. Choe, and T. R. Garrick, J. Electrochem. Soc., 167, 120503 (2020). S. T. Dix, J. S. Lowe, M. R. Avei, and T. R. Garrick, J. Electrochem. Soc., 170, 083503 (2023). T. F. Fuller, M. Doyle, and J. Newman, Journal of the electrochemical society, 141, 1 (1994). M. Doyle, T. F. Fuller, and J. Newman, Journal of the Electrochemical society, 140, 1526 (1993). J. S. Lopata et al., J. Electrochem. Soc., 170, 020530 (2023).

Mechanical shutdown of battery separators: Silicon anode failure

The pulverization of silicon (Si) anode materials is recognized as a major cause of their poor cycling performance, yet a mechanistic understanding of this degradation from a full cell perspective remains elusive. Here, we identify an overlooked contributor to Si anode failure: mechanical shutdown of separators. Through mechano-structural characterization of Si full cells, combined with digital-twin simulation, we demonstrate that the volume expansion of Si exerts localized compressive stress on commercial polyethylene separators, leading to pore collapse. This structural disruption impairs ion transport across the separator, exacerbating redox nonuniformity and Si pulverization. Compression simulation reveals that a Young’s modulus greater than 1 GPa is required for separators to withstand the volume expansion of Si. To fulfill this requirement, we design a high modulus separator, enabling a high-areal-capacity pouch-type Si full cell to retain 88% capacity after 400 cycles at a fast charge rate of 4.5 mA cm−2.

The Influence of Thermal Management Concepts on the Battery Behavior - Insights from a New Coupled Numerical Modelling Approach on the Battery Module Scale and Corresponding Experiments

Battery electric vehicles (BEVs) are the future mainstream drivetrain solution for the individual mobility sector. However, the fast charging capability of BEVs, which is seen as a key enabler for a broad customer acceptance and a convenient e-mobility is a remaining challenge in the development of battery systems. During fast charging, increased heat losses occur in the battery cells and the electrical connectors of a battery module. The battery thermal management then plays a crucial role to keep the battery temperature in the recommended range and to avoid accelerated degradation of the cells. Most of the conventional battery thermal management concepts in today’s BEVs are not efficient in managing the increased heat losses which leads to currently limited fast charging rates. Therefore, new thermal management solutions are being discussed and developed. A promising approach is the direct liquid cooling of batteries, also known as immersion cooling. With immersion cooling, the cells, cell tabs and electrical connectors are in contact with a dielectric fluid. Immersion cooling has the potential to increase the temperature homogeneity within and between the cells and to decrease or even prevent subsequent cell degradation. For the development of efficient thermal management systems for future BEVs and to use the full potential of concepts like immersion cooling, the influence of the thermal management on the battery cells must be understood and evaluated in detail. Considering that, a deep understanding of the interacting electrical, electrochemical, thermal and fluid dynamic phenomena occurring inside a battery module is required. Therefore, in this contribution, numerical simulations and corresponding experiments with battery modules in application-related setups are combined to study the effects of the thermal management on the battery behavior. The two fundamentally different concepts of immersion cooling and state-of-the-art bottom cooling are investigated as well as variations of each of those concepts. In the immersion cooled module, particular attention is paid to the fluid flow distribution and the effect different flow concepts on the thermal and electrochemical conditions in the cell. The numerical studies are based on a new coupled modelling approach (Fig. 1). Detailed thermal models of the 65 Ah automotive NMC/Si-Gr pouch cells are set up in a 3D CFD environment based on the analysis of the disassembly of the cell and the measurements of its thermophysical properties. Then, networks of electrochemical models of the cell are electrically and thermally coupled to the 3D models and the module components. This holistic approach allows for the investigation of e.g., the interaction of the cooling fluid flow with the current and temperature distribution and its effect on the local electrochemical cell behavior like the anode potential during fast charging. The corresponding experimental battery modules in a 3s2p configuration (Fig. 2) are explicitly designed and built for the validation of the numerical models. The cells and module components are equipped with extensive temperature measurements to capture thermal gradients within and between the cells. The modules are then installed and operated in separate climate chambers and connected to individual cooling circuits (Fig. 3) to ensure defined and equal boundary conditions as basis for the comparison of concepts and concept variations. The performance differences in various operating points including fast charging are demonstrated and analyzed. Furthermore, the variation of boundary conditions e.g., the volume flow rate or the fluid temperature allows for the analysis of relevant differences in the cooling concepts’ operating principles. The results from simulation and experiment illustrate the weak spots of the conventional concepts that are used in today’s BEVs. Furthermore, the numerical models reveal the critical local conditions inside the cells that are provoked by high loads in combination with inefficient thermal management concepts. Furthermore, the results show the benefits of immersion cooling over conventional concepts and its potential to increase the lifetime of battery systems by steering the battery temperature and temperature homogeneity with suitable fluid flow conditions. At the same time, the fast charging capability of BEVs can be increased significantly with immersion cooling. The good agreement of numerical and experimental results (Fig. 4) show that the presented modelling approach can be used as a tool for the design and the optimization of thermal management concepts. The application-related setup in this study ensures transferability of the findings from experiment and simulation to automotive applications and will help researchers and developers from industry and academia towards developing better thermal management solutions for BEVs. Figure 1

Demineralization of a Carbon Material Derived from Palm Kernel Shells as a Process for the Enhancement of the Electrochemical Performance of Lithium-Sulfur Cells.

Carbon materials derived from biomass have been widely used in Li-S batteries; however, the mineral matter present in the biomass could impact the properties of the carbons and affect the electrochemical performance. In this study, the removal of mineral matter from palm kernel shells is reported to identify the effect of minerals on the physicochemical properties of the derived activated carbon and correlate them to the electrochemical performance in Li-S batteries. The content of minerals such as silicon, iron, and potassium was decreased by acid washing. The textural and conductive properties of activated carbon were increased by the absence of minerals. Electrochemical results reveal that the demineralized sample used as a sulfur host can increase the capacity for high charge and discharge rates by 23%. Hence, the removal of mineral matter in the biomass is an important step to consider for the application of activated carbons as sulfur hosts in Li-S batteries.

Two-stage distributionally robust optimization operation of virtual power plant considering the virtual energy storage of electric vehicles

Virtual Power Plant (VPP) is a key to aggregate various distributed energy sources. With the vigorous rise of various distributed energy sources, the direct access of large-scale electric vehicle load will increase the complexity of VPP coordinated operation. Hence, this paper proposes a VPP optimization method for Electric Vehicle Virtual Energy Storage (EV-VES). Firstly, the travel characteristics of electric vehicles are analyzed, and EV-VES model is established to coordinate and manage the charge-discharge behavior of EV. Secondly, the “carbon charge rate” model of energy storage (ES) is introduced to establish the relationship between carbon emission and electricity price, and the VPP operation model considering the “carbon charge rate” of energy storage is established. Finally, the two-stage robust optimization operation model of VPP is constructed, Wasserstein distance is used to describe the confidence set of uncertain probability distribution of wind power generation and load, and the uncertainty of system source and load are described by the confidence set. The Column and Constraint Generation (C&CG) algorithm was used to determine the optimal operational benefit solution. The effectiveness of the proposed VPP optimal operation model was validated through case study.

Composite Solid-State Electrolyte with Vertical Ion Transport Channels for All-Solid-State Lithium Metal Batteries.

Composite solid electrolytes (CSEs) consisting of polymers and fast ionic conductors are considered a promising strategy for realizing safe rechargeable batteries with high energy density. However, randomly distributed fast ionic conductor fillers in the polymer matrix result in tortuous and discontinuous ion channels, which severely constrains the ion transport capacity and restricts its practical application. Here, CSEs with highly loaded vertical ion transport channels are fabricated by magnetically manipulating the alignment of Li0.35La0.55TiO3 nanowires. The construction of densely packed, vertically aligned ion transport channels can effectively enhance the ion transport capacity of the electrolyte, thereby significantly increasing ionic conductivity. At room temperature (RT), the presented CSE exhibits a remarkable ionic conductivity of up to 2.5 × 10-4 S cm-1. The assembled LiFePO4/Li cell delivers high capacities of 118 mAh g-1 at 5 C at 60°C and a RT capacity of 115 mAh g-1 can be achieved at a charging rate of 0.5 C. This work paves an encouraging avenue for further development of advanced CSEs that favor lithium metal batteries with high energy density and electrochemical performance.

An Instructive CO2 Adsorption Model for DAC: Wave Solutions and Optimal Processes.

We present and investigate a simple yet instructive model for the adsorption of CO2 from air in porous media as used in direct air capture (DAC) processes. Mathematical analysis and non-dimensionalization reveal that the sorbent is characterized by the sorption timescale and capacity, while the adsorption process is effectively wavelike. The systematic evaluation shows that the overall adsorption rate and the recommended charging duration depend only on the wave parameter that is found as the ratio of capacity and dimensionless air flow velocity. Specifically, smaller wave parameters yield a larger overall charging rate, while larger wave parameters reduce the work required to move air through the sorbent. Thus, optimal process conditions must compromise between a large overall adsorption rate and low work requirements.

Tailoring-Orientated Deposition of Li2S for Extreme Fast-Charging Lithium-Sulfur Batteries.

Precipitation/dissolution of insulating Li2S has long been recognized as the rate-determining step in lithium-sulfur (Li-S) batteries, which dramatically undermines sulfur utilization at elevated charging rates. Herein, we present an orientated Li2S deposition strategy to achieve extreme fast charging (XFC, ≤15 min) through synergistic control of porosity, electronic conductivity, and anchoring sites of electrode substrate. Via magnesiothermic reduction of a zeolitic imidazolate framework, a nitrogen-doped and hierarchical porous carbon with highly graphitic phase was developed. This design effectively reduces interfacial resistance and ensures efficient sequestration of polysulfides during deposition, leading to (110)-preferred growth of Li2S nanocrystalline between (002)-dominated graphitic layers. Our approach directs an alternative Li2S deposition pathway to the commonly reported lateral growth and 3D thickening growth mode, ameliorating the electrode passivation. Therefore, a Li-S cell capable of charging/discharging at 5C (12 min) while maintaining excellent cycling stability (82% capacity retention) for 1000 cycles is demonstrated. Even under high S loading (8.3 mg cm-2) and low electrolyte/sulfur ratio (3.8 mL mg-1), the sulfur cathode still delivers a high areal capacity of >7 mAh cm-2 for 80 cycles.

Developing an Innovative Seq2Seq Model to Predict the Remaining Useful Life of Low-Charged Battery Performance Using High-Speed Degradation Data

This study introduces a novel Sequence-to-Sequence (Seq2Seq) deep learning model for predicting lithium-ion batteries’ remaining useful life. We address the challenge of extrapolating battery performance from high-rate to low-rate charging conditions, a significant limitation in previous studies. Experiments were also conducted on commercial cells using charge rates from 1C to 3C. Comparative analysis of fully connected neural networks, convolutional neural networks, and long short-term memory networks revealed their limitations in extrapolating to untrained conditions. Our Seq2Seq model overcomes these limitations, predicting charging profiles and discharge capacity for untrained, low-rate conditions using only high-rate charging data. The Seq2Seq model demonstrated superior performance with low error and high curve-fitting accuracy for 1C and 1.2C untrained data. Unlike traditional models, it predicts complete charging profiles (voltage, current, temperature) for subsequent cycles, offering a comprehensive view of battery degradation. This method significantly reduces battery life testing time while maintaining high prediction accuracy. The findings have important implications for lithium-ion battery development, potentially accelerating advancements in electric vehicle technology and energy storage.

Simulation and Optimization of Automated Guided Vehicle Charging Strategy for U-Shaped Automated Container Terminal Based on Improved Proximal Policy Optimization

As the decarbonization strategies of automated container terminals (ACTs) continue to advance, electrically powered Battery-Automated Guided Vehicles (B-AGVs) are being widely adopted in ACTs. The U-shaped ACT, as a novel layout, faces higher AGV energy consumption due to its deep yard characteristics. A key issue is how to adopt charging strategies suited to varying conditions to reduce the operational capacity loss caused by charging. This paper proposes a simulation-based optimization method for AGV charging strategies in U-shaped ACTs based on an improved Proximal Policy Optimization (PPO) algorithm. Firstly, Gated Recurrent Unit (GRU) structures are incorporated into the PPO to capture temporal correlations in state information. To effectively limit policy update magnitudes in the PPO, we improve the clipping function. Secondly, a simulation model is established by mimicking the operational process of the U-shaped ACTs. Lastly, iterative training of the proposed method is conducted based on the simulation model. The experimental results indicate that the proposed method converges faster than standard PPO and Deep Q-network (DQN). When comparing the proposed method-based charging threshold with a fixed charging threshold strategy across six different scenarios with varying charging rates, the proposed charging strategy demonstrates better adaptability to terminal condition variations in two-thirds of the scenarios.

Impact of thickness and charge rate on the electrochemical performance of Si-based electrodes

Impact of thickness and charge rate on the electrochemical performance of Si-based electrodes