Search Results (31)

Energy shortage and environmental pollution have accelerated the adoption of lithium-ion batteries (LIBs) as efficient energy storage solutions. However, their performance and safety challenges under extreme temperatures highlight the urgent need for effective temperature control during charging and discharging, making a comprehensive understanding of electrochemical and thermal behaviors crucial. This paper develops a 3D electrochemical–thermal coupled model for 150 Ah lithium iron phosphate (LFP) batteries to investigate thermal behavior at varying charge–discharge rates. An integrated learning regression prediction system, incorporating a structured vector autoregression (SVAR) model, is subsequently proposed to analyze the interactions among multiple electrochemical and thermal variables. The temperature difference exceeds 5 °C at higher charging rates (1.3C, 1.5C), driven primarily by accelerated heat generation—especially reversible heat. Complex interactions exist between electrochemical and thermal parameters. When charging at 0.5C, voltage, current density, battery capacity, and the maximum temperature difference (MTD) are all significantly and positively correlated (p < 0.001). Under 1C discharge conditions, voltage exhibits a strong positive correlation with most thermal characteristic variables, and correlation coefficients across different operating conditions range from −0.9731 to 0.973. Finally, the proposed ensemble learning system exhibits excellent prediction accuracy, strong generalization, and robust trend analysis, with practical guiding value. Full article

The global rise of electric vehicles (EVs) is reshaping the automotive industry, driven by a 25% increase in EV sales in 2024 and mounting regulatory pressure from European countries aiming to phase out thermal and hybrid vehicle production. In this context, the development of advanced battery technologies has become a critical priority. However, progress in electrochemical storage systems remains limited due to persistent technological barriers such as gaps in data, inadequate modeling tools, and difficulties in system integration, such as thermal management and interface instability. Safety concerns like thermal runaway and the lack of long-term performance data also hinder large-scale adoption. This study presents an in-depth analysis of lithium–ion (Li–ion) batteries, with a particular focus on evaluating their charging and discharging behaviors. To facilitate this, a series of automated experiments was conducted using a custom-built test bench equipped with MATLAB (2024b) programming and dSPACE data acquisition cards, enabling precise current and voltage measurements. The acquired data were analyzed to derive mathematical models that capture the operational characteristics of Li–ion batteries. Furthermore, various state-of-charge (SoC) estimation techniques were investigated to enhance battery efficiency and improve range management in EVs. This paper contributes to the advancement of energy storage technologies and supports global ecological goals by proposing safer and more efficient solutions for the electric mobility sector. Full article

The escalating demand for efficient thermal management in lithium-ion batteries necessitates precise characterization of their thermal behavior under diverse operating conditions. This study develops a three-dimensional (3D) electrochemical–thermal coupling model grounded in porous electrode theory and energy conservation principles. The model solves multi-physics equations such as Fick’s law, Ohm’s law, and the Butler–Volmer equation, to resolve coupled electrochemical and thermal dynamics, with temperature-dependent parameters calibrated via the Arrhenius equation. Simulations under varying discharge rates reveal that high-rate discharges exacerbate internal heat accumulation. Low ambient temperatures amplify polarization effects. Forced convection cooling reduces surface temperatures but exacerbates core-to-surface thermal gradients. Structural optimization strategies demonstrate that enhancing through-thickness thermal conductivity reduces temperature differences. These findings underscore the necessity of balancing energy density and thermal management in lithium-ion battery design, proposing actionable insights such as preheating protocols for low-temperature operation, optimized cooling systems for high-rate scenarios, and material-level enhancements for improved thermal uniformity. Full article

Batteries are used as energy storage devices in various equipment. Today, research is focused on solid-state batteries (SSBs), replacing the liquid electrolyte with a solid separator. The solid separators provide electrolyte stability, no leakage, and provide mechanical strength to the battery. Separators are mostly manufactured by either traditional processes or 3D printing technologies. These processes involve making a slurry of plastic, active and conductive material and usually adding a plasticizer when making thin films or filaments for 3D printing. This study investigates the additive manufacturing of solid-state electrolytes (SSEs) by employing fused deposition modeling (FDM) with recyclable, bio-derived polylactic acid (PLA) filaments. Precise control of macro-porosity is achieved by systematically varying key process parameters, including raster orientation, infill percentage, and interlayer adhesion conditions, thereby enabling the formation of tunable, interconnected pore networks within the polymer matrix. Following 3D printing, these engineered porous frameworks are infiltrated with lithium hexafluorophosphate (LiPF₆), which functions as the active ionic conductor. A tailored thermal sintering protocol is then applied to promote solid-phase fusion of the embedded salt throughout the macro-porous PLA scaffold, resulting in a mechanically robust and ionically conductive composite separator. The electrochemical ionic conductivity and structural integrity of the sintered SSEs are characterized through electrochemical impedance spectroscopy (EIS) and standardized mechanical testing to assess their suitability for integration into advanced solid-state battery architectures. The solid-state separator achieved an average ionic conductivity of 2.529 × 10⁻⁵ S·cm⁻¹. The integrated FDM-sintering process enhances ion exchange at the electrode–electrolyte interface, minimizes material waste, and supports cost-efficient, fully recyclable component fabrication. Full article

Three new complexes of copper(II) and chromone-2-carboxylic acid, a ligand from the group of hydroxypyrones, were synthesised according to the principles of green chemistry. The complexes were characterised by FT–IR and NMR spectroscopy, thermal and electrochemical analysis, and their structures are proposed. The results show the formation of mononuclear (1) and dinuclear hydroxo-bridged dinuclear copper(II) complexes (2 and 3). The results of cyclic voltammetry show that the copper in all complexes is in the +2-oxidation state. The antiproliferative activity was determined by MTT assay on 2D cell models in vitro on seven cell lines. The activity spectrum of complexes 1–3 ranged from the highest to the lowest value in the tumour cell lines tested, in the following order: Hep G2 > NCI-H358 > HT-29 > KATO III > MDA-MB 231 > Caco-2. The most effective concentration was 10⁻⁵ mol dm⁻³, which suppressed the growth of Hep G2 cells as follows: 69.5% (1), 64.8% (2) and 64% (3). The calculated selectivity index clearly shows that Hep G2 is the most sensitive cell line to copper complexes (SI = 1.623 (1); 1.557 (2), 1.431 (3). Full article

This article develops an electromechanical-thermal model for semi-solid-state batteries using Software COMSOL Multi-physics. The battery’s three-dimensional structure is firstly simplified into a one-dimensional electrochemical model (P2D), which combines the solid heat transfer module and the solid mechanics module. The total power consumption of the battery, obtained from the P2D model, is used to calculate the battery temperature and the lithium concentration. Then, stress analysis of the anode active particles is conducted, and the battery temperature is fed back into both the electrochemical and mechanical models. To validate the model, constant current charge/discharge cycling experiments, as well as tests on the basic electrical parameters and temperature of the battery, are conducted. The electromechanical-thermal model developed in this study serves as an effective tool for simulating semi-solid-state lithium-ion batteries, which can predict the battery’s performance under various operating conditions. The simulation results from the numerical model are consistent with experimental data at low charge/discharge rates, while slightly larger discrepancies are observed at high charge/discharge rates, with the accuracy remaining over 90%. Further, the thermal expansion behavior of the batteries with silicon-carbon anodes during the charge-discharge process can be examined using the developed model. Full article

With the global rise in consumer electronics, electric vehicles, and renewable energy, the demand for lithium-ion batteries (LIBs) is expected to grow. LIBs present a significant challenge for state estimations due to their complex non-linear electrochemical behavior. Currently, commercial battery management systems (BMSs) commonly use easier-to-implement and faster equivalent circuit models (ECMs) than their counterpart continuum-scale physics-based models (PBMs). However, despite processing more mathematical and computational complexity, PBMs are attractive due to their higher accuracy, higher fidelity, and ease of integration with thermal and degradation models. Various reduced-order PBM battery models and their computationally efficient numerical schemes have been proposed in the literature. However, there is limited data on the performance and feasibility of these models in practical embedded and cloud systems using standard programming languages. This study compares the computational performance of a single particle model (SPM), an enhanced single particle model (ESPM), and a reduced-order pseudo-two-dimensional (ROM-P2D) model under various battery cycles on embedded and cloud systems using Python and C++. The results show that reduced-order solvers can achieve a 100-fold reduction in solution times compared to full-order models, while ESPM with electrolyte dynamics is about 1.5 times slower than SPM. Adding thermal models and Kalman filters increases solution times by approximately 20% and 100%, respectively. C++ provides at least a 10-fold speed increase over Python, varying by cycle steps. Although embedded systems take longer than cloud and personal computers, they can still run reduced-order models effectively in Python, making them suitable for embedded applications. Full article

Lithium ion (Li-ion) battery packs have become the most popular option for powering electric vehicles (EVs). However, they have certain drawbacks, such as high temperatures and potential safety concerns as a result of chemical reactions that occur during their charging and discharging processes. These can cause thermal runaway and sudden deterioration, and therefore, efficient thermal management systems are essential to boost battery life span and overall performance. An electrochemical-thermal (ECT) model for Li-ion batteries and a conjugate heat transfer model for three-dimensional (3D) fluid flow and heat transfer are developed using COMSOL Multiphysics^®. These are used within a novel computational fluid dynamics (CFD)-enabled multi-objective optimization approach, which is used to explore the effect of the mini-channel cold plates’ geometrical parameters on key performance metrics (battery maximum temperature ($T_{max}$), pressure drop ($∆P$), and temperature standard deviation ($T_{\sigma }$)). The performance of two machine learning (ML) surrogate methods, radial basis functions (RBFs) and Gaussian process (GP), is compared. The results indicate that the GP ML approach is the most effective. Global minima for the maximum temperature, temperature standard deviation, and pressure drop ($T_{max}$, $T_{\sigma }$, and $∆P$, respectively) are identified using single objective optimization. The third version of the generalized differential evaluation (GDE3) algorithm is then used along with the GP surrogate models to perform multi-objective design optimization (MODO). Pareto fronts are generated to demonstrate the potential trade-offs between $T_{max}$, $T_{\sigma }$, and $∆P$. The obtained optimization results show that the maximum temperature dropped from 36.38 to 35.98 °C, the pressure drop dramatically decreased from 782.82 to 487.16 Pa, and the temperature standard deviation decreased from 2.14 to 2.12 K; the corresponding optimum design parameters are the channel width of 8 mm and the horizontal spacing near the cold plate margin of 5 mm. Full article

The specificities of temperature-dependent electrochemical modelling strategies of 18650 Li-ion batteries were investigated in pseudo-2D, 2D and 3D domains using finite element analysis. Emphasis was placed on exploring the challenges associated with the geometric representation of the batteries in each domain, as well as analysing the performance of coupled thermal-electrochemical models. The results of the simulations were compared with real reference measurements, where temperature data were collected using temperature sensors and a thermal camera. It was highlighted that the spiral geometry provides the most realistic results in terms of the temperature distribution, as its layered structure allows for a detailed realisation of the radial heat transfer within the cell. On the other hand, the 3D-lumped thermal model is able to recover the temperature distribution in the axial direction of the cell and to reveal the influence of the cell cap and the cell wall on the thermal behaviour of the cell. The effect of cooling is an important factor that can be introduced in the models as a boundary condition by heat convection or heat flux. It has been shown that both regulated and unregulated (i.e., natural) cooling conditions can be achieved using an appropriate choice of the rate and type of cooling applied. Full article

Charge time has become one of the primary issues restricting the development of electric vehicles. To counter this problem, an adapted thermal management system needs to be designed in order to reduce the internal thermal gradient, by predicting the surface and internal temperature responses of the battery. In this work, a pseudo 3D model is developed to simulate battery cell performance and its internal states under various operational scenarios such as temperature and convection conditions as well as the applied current during charge and discharge. An original mesh of the JR is proposed where heat exchanges in the three directions (radial, orthoradial and axial) are considered. The model represents one of the solutions that enable increasing the lifespan of batteries while decreasing charging time. It offers the opportunity to optimize operating parameters to extend battery life. In this paper, attention was paid not only to the core and non-core components, but also to the experiments required to parametrize the thermal and electrochemical models (heat generation). Unlike existing approaches documented in the literature, the model developed in this work achieves an impressive balance between computational efficiency and result accuracy, making it a groundbreaking contribution in the field of electric vehicle technology. Full article

Recently, there has been growing recognition of the significance of energy and environmental challenges. Utilization of lithium-ion batteries in electric vehicles has shown considerable potential and benefits for tackling these issues. The effective management of battery temperature has become a crucial factor in the advancement and widespread adoption of lithium-ion batteries in electric vehicles. In this study, a thermo-coupled pseudo-two-dimensional (P2D) electrochemical model is employed to simulate the heat generation of the NCM811-21700 cylindrical battery cell at various discharge rates at an ambient temperature of 25 °C, and is validated by experimental data. The validation results demonstrate that the thermo-coupled P2D model can effectively predict the battery voltage curve during the discharge process with less than 4% errors. Although there is a slightly larger error in the temperature prediction during the battery 2C and 3C discharge processes, the maximum error approaches 10%, which is still generally within an acceptable range. In addition, the battery’s electrochemical and thermal characteristics during discharge are presented. The suggested thermo-coupled electrochemical model can be used for applications in the thermal management system of the NCM811-21700 battery. Full article

In this paper, a computational fluid dynamics (CFD) model to predict the transient temperature distributions of a prismatic lithium-ion polymer battery (LiPo) cooled by natural convection at various discharge cycles is developed. The thermal behavior of a lithium-ion (Li-ion) battery cell is important for its safety, performance and degradation, and it requires both measurement and modeling. However, most existing thermal models for Li-ion battery cells only account for steady-state temperature fields, while the exercise of a Li-ion battery cell is usually transitory. The Newman’s pseudo-2D approach was used to perform an electrochemical CFD analysis. This approach treats the porous electrode as a collection of equal-sized, isotropic, homogeneous spherical particles. This simplifies the electrode microstructure and assumes a smooth and uniform lithium insertion/extraction in the electrode. The model has been validated through variable discharge rate experimental tests in a controlled chamber. Additionally, infrared images of the battery cell during discharging are taken and the experimental numerical gradient temperature was compared. We have validated the CFD simulations by comparing the temperature, state of charge and voltage curves with experimental data. The model predictions match the experimental data very well. The difficulty in CFD battery simulations with an electrochemical approach lies in the setting of many physical parameters that are difficult to find. In this work, the parameters’ characteristics of the simulated battery are assumed and validated; these can be useful for modeling batteries of the same type. Consequently, the model developed in this work can be applied to predict the temperature distribution of the LiPo prismatic battery and can be used by the battery designers and by the designers of all systems that include batteries. Full article

Due to climate concerns, most countries are looking for alternative ways to generate energy in a clean, efficient, and environmentally friendly way. Currently, a practical and technically feasible solution can be obtained by integrating a gas turbine and a solid oxide fuel cell to form a hybrid system. Experimental studies of the thermophysical, electrochemical, and other internal processes in solid oxide fuel cells are an expensive procedure, so theoretical tools such as simulations are very important in the analysis and design of solid oxide fuel cell stack systems. In this work, a 3D model of a planar fuel cell was studied. Numerical modeling was carried out, taking into account the flow channel design, the movement of thermal air, and fuel flows. A calculation of the thermodynamic parameters of a solid oxide fuel cell with hydrocarbon fuel has been carried out. In conclusion, some constructive perspectives and recommendations for future research are offered. Full article

Lithium-ion battery cells exhibit a complex and nonlinear coupling of thermal, electrochemical, and mechanical behavior. In order to increase insight into these processes, we report the development of a pseudo-three-dimensional (P3D) thermo-electro-mechanical model of a commercial lithium-ion pouch cell with graphite negative electrode and lithium nickel cobalt aluminum oxide/lithium cobalt oxide blend positive electrode. Nonlinear molar volumes of the active materials as function of lithium stoichiometry are taken from literature and implemented into the open-source software Cantera for convenient coupling to battery simulation codes. The model is parameterized and validated using electrical, thermal and thickness measurements over a wide range of C-rates from 0.05 C to 10 C. The combined experimental and simulated analyses show that thickness change during cycling is dominated by intercalation-induced swelling of graphite, while swelling of the two blend components partially cancel each other. At C-rates above 2 C, electrochemistry-induced temperature increase significantly contributes to cell swelling due to thermal expansion. The thickness changes are nonlinearly distributed over the thickness of the electrode pair due to gradients in the local lithiation, which may accelerate local degradation. Remaining discrepancies between simulation and experiment at high C-rates might be attributed to lithium plating, which is not considered in the model at present. Full article

An increase in the size of large-format Li-ion batteries (LIBs) may lead to nonuniform temperature distribution, which degrades the performance and lifespan of the LIBs. To address this issue, we performed design optimization using a 3D electrochemical-thermal coupled model for 55 Ah LFP/graphite large-format pouch cells. To minimize temperature differences in Normal Tab (NT), Lateral Tab (LT), and Counter Tab (CT) types of LIBs, design optimization was performed on the width, height, and attachment position of each positive and negative Table The upper and lower limits of each design variable were set as constraints without exceeding the sum of the total area of the tabs of the initial NT type. Owing to the optimization of the NT, LT, and CT types, the temperature difference in the optimized CT type was 79.2% less than in the initial NT type. Additionally, the potential difference decreased by 37.1%, minimizing ohmic heat. Aging analysis of 2500 cycles was performed to analyze the improvement in the lifespan due to the uniform temperature distribution. Consequently, the capacity retention rate of the optimized CT type was 6.5% higher than that of the initial NT type. Thus, the temperature distribution and lifespan of LIBs were improved by design optimization. Full article