Transformer Oil Research Articles

Theoretical Calculation of Dissolved Gas in Transformer Oil Using the Gas Sensitive Properties of Sc- and Ti-Modified ZrS2.

To guarantee the secure functioning of the complete power system and minimize the risks associated with oil-filled transformers during their operation, it is greatly important to carry out gas sensing studies of dissolved gases in transformer research. Through the utilization of first-principles density functional theory calculations, the adsorption energy, electronic characteristics, and recuperation duration of ZrS2 modified with Sc and Ti were examined. The results show that compared to those of the initial ZrS2 material, the doping of TM atoms Sc and Ti significantly improved the adsorption properties of the material, and the adsorption of CO and C2H4 showed chemisorption. The adsorption capacity for gases decrease in the following order: C2H4 > CO > H2. The calculated recovery times indicate that Sc-ZrS2 and Ti-ZrS2 were ideal carbon monoxide sensing materials under the specific conditions. The results of this work can establish a fundamental rationale for the use of ZrS2 in sensing the conditions of oil-immersed transformers.

Evolution laws of charge mobility of transformer oil and pressboard material with temperature and electric field strength

Abstract Charge mobility, a pivotal parameter in the space charge analysis model for oil-pressboard insulation of converter transformer under DC electric fields, predominantly relies on theoretical or empirical data. The prevalent omission of empirical, measurement-based evaluations, combined with the neglect of temperature and electric field intensity effects, introduces uncertainties in the calculation of electric field and charge dynamics. Grounded on the principles of the electroacoustic pulse technique for space charge measurements, our investigation established a temperature-controlled platform to determine the charge-charge mobility in oil and pressboard insulation mediums. Utilizing diverse oil-pressboard insulation systems, this study identified the temporal patterns of both positive and negative charge mobilities and unravelled the mechanisms modulated by temperature and electric field intensity: 1) With increasing temperatures (from 20°C to 80°C) and intensifying electric field strengths (from 5kV/mm to 25kV/mm), the charge mobility within transformer oil and pressboard exhibits a rising trend. Notably, temperature variations exert the most significant influence, yielding amplifications up to 24.8 times. 2) The intrinsic properties of different transformer oils and oil-impregnated pressboards result in pronounced differences in their charge transport behaviours. Specifically, naphthenic-based oil demonstrates enhanced charge mobility relative to its paraffin-based counterpart. In contrast, transformer oils with higher kinematic viscosities exhibit diminished charge mobility compared to those with lower viscosities. 3) A linear relationship is observed between the oil absorption rate and electrical conductivity, aligning closely with the insulating pressboard's charge mobility. The evaluation of electric field and interface charge dynamics in oil-pressboard insulation under both DC and polarity-reversed conditions revealed that the electric field decay in naphthenic-based oil is more rapid than in paraffin-based oils. Moreover, both the magnitude and rate of interface charge accumulation in naphthenic-based oils exceed those in paraffin-based variants, further validating the accuracy of our charge mobility measurements and ensuing analysis.

Prediction of Dissolved Gas Content in Transformer Oil Using the Improved SVR Model

Prediction of Dissolved Gas Content in Transformer Oil Using the Improved SVR Model

15-GW repetitive pulsed power generator based on Midel 7131 and double-width pulse forming line

The Tesla-type pulsed power generator based on transformer oil is limited by volume and weight, which affects its suitability for mobile platforms. In this paper, a double-width pulse forming line (PFL) based on high-energy-density liquid medium Midel 7131 was designed, and a compact, high-repetitive pulsed power generator was developed. The structural and electrical parameters of the PFL with an outer diameter of 1000 mm were optimized to achieve the highest output power with a fixed load impedance of 60 Ω. This generator employed a double-width forming line, which has an output pulse width of four times of the electrical length of its external line, significantly increasing the output pulse width and making the system more compact. The generator could be finally enveloped with a size of 4 × 1.5 × 1.5 m3 and a weight of 4.7 tons. The experiment showed that the generator could operate reliably under the conditions of 15-GW peak power, 50-ns pulse width, 50-Hz repetition rate, and <1% voltage jitter. The X-band relatively backward wave oscillator driven by this generator yielded a favorable microwave, which demonstrated the high-power driving capability of the generator.

Suppression of Transformer Oil Surges Caused by External Short-Circuit Faults Using an SFCL

Suppression of Transformer Oil Surges Caused by External Short-Circuit Faults Using an SFCL

A study on the water content in distribution pole transformer using random forest model

This study proposes and validates an artificial intelligence (AI)-based method for estimating the water content in the insulating oil of distribution-level transformers. The methodology includes data augmentation using noise addition, outlier removal via Isolation Forest, and data normalization through square root transformation. A Random Forest (RF) model is developed to estimate water content based on the usage period of the transformer. Correlation analyses identified the usage period as the key variable affecting water content. The model demonstrated high estimation accuracy with an R-squared value of 0.83, closely aligning estimated values with measured data. This approach provides a practical solution for real-world applications, expanding the focus to distribution-level transformers and ensuring reliable estimations through validation with actual field data. Despite limitations due to a dataset comprising 100 samples of transformer usage and oil analysis data, the method shows promise for accurate transformer lifespan assessment and efficient asset management. Future research will enhance model performance by incorporating diverse environmental conditions and comparative analyses with other machine learning (ML) algorithms, aiming to optimize estimation reliability and safety for distribution-level transformers. Consistency in the methodology description and actual models used will be maintained to avoid discrepancies.

Three-dimensional bioconvection in a nanofluid film over a wedge surface with entropy generation and nonlinear radiation: A revised Buongiorno model

ABSTRACT The advances in the field of nanotechnology tends to improve the rate of heat extraction and transmission from foreseeable causes and has fascinated researchers and scientists. Furthermore, nanofluids are having a useful impact on various fields such as nuclear industries, powered lasers, chilling of microelectronic devices, solar energy capture, transformers oil cooling, and in cancer diagnosis. Hence, magnetohydrodynamic (MHD) three-dimensional bioconvective flow of nanofluid accommodating gyrotactic microorganisms over a wedge surface with zero nanoparticles mass flux boundary conditions is studied, using large Reynolds number approximation. The additional novelty of the study is the implementation of the revised Buongiorno model, which deliberates the effects of thermo-migration and Brownian diffusion of nanoparticles, together with passive control of nanoparticles fraction on the wedge surface. The self-similar form of conservation equations of energy, nanoparticle fraction, gyrotactic microorganisms, and momentum are handled numerically. T The results of the Blasius and the Hiemenz flows are retrieved as special cases of the model. It was found that the temperature of the nanofluid increases considerably when considering the nonlinear thermal radiation compared to the linear radiant heat. Increasing the strength of the Brownian diffusion increases the heat transport but reduces the mass transport.

Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information

This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. Traditional diagnoses are based on strict measurements that do not account for the factors of variability and uncertainty of the actual data. In this article, we perform six different types of tests in this regard, and data have been collected during the period of 2021 to 2022 of 188 power transformer failures in the New KotLakhpat Lahore unit, whose voltage range is 132/66 kv and rating capacity is 40/50 MVA. In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. Moisture, acidity, and a dissolved gas analysis indicator, along with other indication approaches such as interfacial tension, viscosity, and tangent delta measurement, are used to analyze the deterioration process in transformer oils. In the visual representation, oil samples with the following properties were first fuzzified: 19.9 mm2/s of viscosity, 0.453 mgKOH/g of acidity, 695 ppm of DGA, 20.8 mg/kg of moisture, 19.98 of IFT, and 4.35 × 100.14 of tangent delta. The output that was generated by software using the values entered into the parameters (HI and Age) after defuzzification is 45. Fuzzy logic serves as a concrete framework for transforming the diagnostics system and deterring the threats to the entire transformer’s health and reliability in the future. By using this technique, various faults were hypothetically and practically analyzed in a transformer to implement early detection technologies with the possibility to reduce maintenance costs and extend operational life up to 45 years. Various case studies indicate the effectiveness of fuzzy logic in comparison to traditional diagnostics.

Study on Mechanical Properties and Fatigue of Cold-rolled Steel Plate for Distribution Transformer

The oil tank steel plate of the distribution transformer is covered with welds, and the fatigue failure of the oil tank often occurs in the internal defects of fillet welds. Given the above problems, this paper puts forward the bearing capacity calculation formula of cold-rolled steel plate and carries on the force analysis of steel plate and the fatigue analysis of weld through finite elements. Based on the theory of plastic limit design, the ultimate flexural bearing capacity of the control section of steel plate members is proposed. The calculation formula of equivalent structural stress is given based on the calculation method of structural stress and linear elastic fracture mechanics, and the calculation method of fatigue life and fatigue cumulative damage is given. Then, the elastic-plastic equation is solved according to three criteria: Mises yield criterion, plastic flow criterion, and strengthening criterion. Based on the above numerical simulation analysis, the mechanical model of steel plate weld is constructed, the mesh is divided, the boundary conditions are restricted and the same load is applied. ABAQUS analysis results show that the stress distribution curve of the connector has a maximum value at X = 80 mm and X = 210 mm, that is, the top surface of the connector steel plate has an obvious stress concentration at 80 mm and 210 mm. When the length of the weld is not more than 60 times the size of the welding foot, the full section of the core plate will yield, and the maximum stress value of the weld element will not exceed the tensile strength value of the welding material. The error of the results calculated by the formula in this paper is mostly within 10%, and the rest is basically within 20%. Therefore, the bearing capacity formula of the steel plate in this paper has ideal calculation accuracy and can provide effective guidance for the design of distribution transformer oil tanks.

Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting

This paper presents a new approach in the field of probability-informed machine learning (ML). It implies improving the results of ML algorithms and neural networks (NNs) by using probability models as a source of additional features in situations where it is impossible to increase the training datasets for various reasons. We introduce connected mixture components as a source of additional information that can be extracted from a mathematical model. These components are formed using probability mixture models and a special algorithm for merging parameters in the sliding window mode. This approach has been proven effective when applied to real-world time series data for short- and medium-term forecasting. In all cases, the models informed by the connected mixture components showed better results than those that did not use them, although different informed models may be effective for various datasets. The fundamental novelty of the research lies both in a new mathematical approach to informing ML models and in the demonstrated increase in forecasting accuracy in various applications. For geophysical spatiotemporal data, the decrease in Root Mean Square Error (RMSE) was up to 27.7%, and the reduction in Mean Absolute Percentage Error (MAPE) was up to 45.7% compared with ML models without probability informing. The best metrics values were obtained by an informed ensemble architecture that fuses the results of a Long Short-Term Memory (LSTM) network and a transformer. The Mean Squared Error (MSE) for the electricity transformer oil temperature from the ETDataset had improved by up to 10.0% compared with vanilla methods. The best MSE value was obtained by informed random forest. The introduced probability-informed approach allows us to outperform the results of both transformer NN architectures and classical statistical and machine learning methods.

Power Transformer Fault Diagnosis Based on Random Forest and Improved Particle Swarm Optimization–Backpropagation–AdaBoost

This paper proposes a novel fault diagnosis methodology for oil-immersed transformers to improve the diagnostic accuracy influenced by gas components in power transformer oil. Firstly, the Random Forest (RF) algorithm is utilized to evaluate and filter the raw data features, solving the problem of determining significant features in the dataset. Secondly, a multi-strategy Improved Particle Swarm Optimization (IPSO) is applied to optimize a double-hidden layer backpropagation neural network (BPNN), which overcomes the challenge of determining hyperparameters in the model. Four enhancement strategies, including SPM chaos mapping based on opposition-based learning, adaptive weight, spiral flight search, and crisscross strategies, are introduced based on traditional Particle Swarm Optimization (PSO) to enhance the model’s optimization capabilities. Lastly, AdaBoost is integrated to fortify the resilience of the IPSO-BP network. Ablation experiments demonstrate an enhanced convergence rate and model accuracy of IPSO. Case analysis using Dissolved Gas Analysis (DGA) samples compares the proposed IPSO–BP–AdaBoost model with other swarm intelligence optimization algorithms integrated with BPNN. The experimental findings highlight the superior diagnostic accuracy and classification performance of the IPSO–BP–AdaBoost model.

Reference Material for the Composition of Fuel Oil

Electrical transformers are a key element in the process of distributing electricity from the producer to the final consumer. The reliability of electrical transformers is ensured through systematic monitoring of the structural condition using chemical analysis of fuel (transformer) oil used for electrical insulation and cooling of transformers. The working life of energy oil and paper insulation can be assessed by evaluating the content of antioxidant additive (ionol) and furan derivatives (furfuryl alcohol, furfural, 2-acetylfuran and 5-methylfurfural). The article provides a critical analysis of methods for measuring ionol and furan derivatives in oils. In particular, it has been established that the most widely used methods for the identification of ionol and furan derivatives are liquid and gas chromatography methods with preliminary isolation of analytes based on the principles of liquid/solid-phase extraction. At the same time, the need for matrix reference materials with established metrological traceability was identified for metrological support of methods for measuring the content of ionol and furan derivatives in oils. Therefore, the purpose of this study was the development of a certified reference material (CRM) for the composition of fuel oil. The technology for producing such a CRM makes it possible to prepare the material with the required concentrations of analytes. The article describes the sequence of preparation of a CRM batch and presents the conclusions of studying the stability and between-bottle homogeneity of the material. The given calculation of the standard uncertainty for the certified value of the CRM from the characterization method, heterogeneity, and instability of the material in accordance with GOST ISO Guide 35–2015 deserves attention. The metrological traceability of certified values of the CRM to the unit of value «mass fraction of a component» reproduced by the State Primary Standard of units of mass (molar) fraction and mass (molar) concentration of organic components in liquid and solid substances and materials based on liquid and gas chromatography-mass spectrometry with isotope dilution and gravimetry (GET 208–2019). The competence of the study is confirmed by the fact that the CRM was recognized as GSO 12232–2023.

Impact of sol-gel synthesized α-aluminium oxide nanoparticles for the enhancement of transformer oil insulation properties

Transformers require advanced insulating materials that outperform mineral oil in terms of cooling, insulation effectiveness, eco-friendliness, and operational efficiency in extreme operational and weather conditions. As a result, emphasis has shifted to renewable and ecologically friendly materials. This change in emphasis is motivated by worries about the environment, fuel shortages, and the disposal of waste oil. Transformers have historically employed solid insulators like paper and pressboard as well as mineral or synthetic oil. However, the development of ecologically friendly insulating materials has been spurred by new environmental regulations as well as economic benefits. This research investigates the use of sol-gel synthesized aluminium oxide (Al2O3) nanoparticles to improve the insulation properties of host transformer oil. The synthesized aluminium nanoparticles were characterized with X-ray diffractometer (XRD) and found rhombohedral structure, whose chemical composition was studied by energy dispersive X-ray spectrum (EDAX). Investigation using Fourier transform infrared spectroscopy (FTIR) also revealed the production of AlOOH and hydroxyl vibrational bands at wavenumbers of 690 and 2976 cm−1, respectively. Studies using field emission scanning electron microscopy (FESEM) showed that the nanoparticles are spherical in form and have a diameter of around 38 nm. Additionally, the incorporation of α-aluminium oxide nanoparticles into the host oil showed an improvement in the breakdown voltage and suggested a possible use for better transformer oil insulation.

Thermal (TG/DTA) and mass (GC-HRMS) analysis of waste transformer oil and its blends

ABSTRACT This study investigates the potential use of waste transformer oil (WTO) and its blends as alternative fuels for CI engines. Thermal (TG/DTA) and mass (GC-HRMS) analyses were performed on neat samples of diesel, biodiesel, WTO, and four sets of samples with different volumetric ratios of WTO, diesel, and biodiesel. TG/DTA analysis showed that the blended samples WTO20BD10D70 and WTO30D70 had a lower range of rapid disintegration temperatures (150°C), while WTO30BD20D50 exhibited the lowest temperature range for enthalpy change. The weight loss and enthalpy change of WTO and its blends were similar to those of standard diesel fuel. GC-HRMS analysis revealed that the compounds present in WTO and its blends were n-alkanes, alkenes, aromatics, alcohols, phenols, carboxylic acids, esters, and cyclic compounds, similar to those found in diesel fuel. Sample WTO20BD10D70 showed a narrow range of compounds (C8 to C27) and a similar composition of hydrocarbons to that of neat diesel, indicating its potential as an alternative fuel. Blended samples with higher carbon numbers may be harder to ignite but more stable for long-term storage, and their composition is similar to diesel fuel, suggesting their potential as eco-friendly diesel alternatives.

Electric‐Thermal Dual‐Responsive HASEL Actuator for Solid–Liquid Bi‐Stabilized Smart Switching

AbstractHydraulically amplified self‐healing electrostatic (HASEL) actuators generally consisting of dielectric elastomer (DE) and transformer oil have garnered interest in the realm of soft actuators. However, existing DE can hardly reconcile contradictions between high dielectric constants and low modulus, while traditional transformer oil demands a continuous power supply to sustain strain. Herein, by incorporating liquid metal (LM) featuring high dielectric constant and low modulus, with poly(ε‐caprolactone) (PCL) bearing low phase change temperature, a new concept of electric‐thermal dual‐responsive HASEL actuator is first proposed for solid–liquid bi‐stabilized smart switching. It is not only able to simultaneously deliver a tripled dielectric constant of DE from 3.1 to 9.7 (at 1 kHz) and a low modulus (0.12–0.15 MPa), thus achieving a strain of 9% and a specific power of 64.8 W kg−1; but also, PCL replaces the transformer oil, acting as a “temperature switch” for the HASEL actuator, i.e., when PCL solidifies, the HASEL actuator stabilizes the deformation, allowing it to continue working even without power supply. Exemplified by valve, the as‐prepared dual‐responsive HASEL actuator can independently control the flow rate of each valve unit. This electric‐thermal dual‐responsive HASEL actuator introduces an innovative strategy for developing the next generation of multifunctional smart switching.

Impact of atomizer design on slurry fuel atomization behavior

The paper presents experimental findings on the atomization characteristics of coal–water slurries with and without petrochemicals. The fuels were based on flame coal filter cake (slime), which is a typical coal processing waste, flame coal of different particle sizes, wood biomass (sawdust), used transformer oil, and water. The atomized flow characteristics—droplet size and velocity as well as jet angle—were found to depend on the atomizer dimensions and slurry rheology. The experimental data were used to calculate the slurry atomization efficiency factor. The findings were generalized to provide a mathematical description of how the slurry composition and atomizer geometry affect the slurry atomization behavior. Approximations were obtained for atomization characteristics that can be used to predict the jet angle as well as droplet radii and velocities. The developed mathematical tool can be employed to calculate the spraying characteristics when using devices like external-mix twin-fluid atomizers. The approach proposed for data generalization can be applied to adapt the set of approximation equations to other types of nozzles.

Effects of DBDS and DBPC antioxidants on the corrosion of copper strips immersed in transformer oil

Effects of DBDS and DBPC antioxidants on the corrosion of copper strips immersed in transformer oil

Dynamic simulation of differential accumulation history of deep marine oil and gas in superimposed basin: A case study of Lower Paleozoic petroleum system of Tahe Oilfield, Tarim Basin, NW China

According to the complex differential accumulation history of deep marine oil and gas in superposition basins, the Lower Paleozoic petroleum system in Tahe Oilfield of Tarim Basin is selected as a typical case, and the process of hydrocarbon generation and expulsion, migration and accumulation, adjustment and transformation of deep oil and gas is restored by means of reservoine-forming dynamics simulation. The thermal evolution history of the Lower Cambrian source rocks in Tahe Oilfield reflects the obvious differences in hydrocarbon generation and expulsion process and intensity in different tectonic zones, which is the main reason controlling the differences in deep oil and gas phases. The complex transport system composed of strike-slip fault and unconformity, etc. controlled early migration and accumulation and late adjustment of deep oil and gas, while the Middle Cambrian gypsum-salt rock in inner carbonate platform prevented vertical migration and accumulation of deep oil and gas, resulting in an obvious “fault-controlled” feature of deep oil and gas, in which the low potential area superimposed by the NE-strike-slip fault zone and deep oil and gas migration was conducive to accumulation, and it is mainly beaded along the strike-slip fault zone in the northeast direction. The dynamic simulation of reservoir formation reveals that the spatio-temporal configuration of “source-fault-fracture-gypsum-preservation” controls the differential accumulation of deep oil and gas in Tahe Oilfield. The Ordovician has experienced the accumulation history of multiple periods of charging, vertical migration and accumulation, and lateral adjustment and transformation, and deep oil and gas have always been in the dynamic equilibrium of migration, accumulation and escape. The statistics of residual oil and gas show that the deep stratum of Tahe Oilfield still has exploration and development potential in the Ordovician Yingshan Formation and Penglaiba Formation, and the Middle and Upper Cambrian ultra-deep stratum has a certain oil and gas resource prospect. This study provides a reference for the dynamic quantitative evaluation of deep oil and gas in the Tarim Basin, and also provides a reference for the study of reservoir formation and evolution in carbonate reservoir of paleo-craton basin.

Heat transfer research on the cooling process of waxy crude oil storage in the vault tank based on VOF model

This paper focuses on the static cooling process for waxy crude oil stored in dome roof tanks. For the three phases of gas on top, liquid crude oil, and bottom water in storage tank, the VOF method is used to describe the evolution of physical quantities at the “oil–water”/“oil–gas” interface. The porous medium method is used to quantitatively characterize the sol–gel conversion process for waxy crude oil. A physical and mathematical models are established to describe the flow-heat transfer coupling behavior of the three-phase medium of crude oil, gas on top, and water at the bottom of the dome roof tank. In terms of the overall cooling process,The gas at the top of the tank has the simplest and fastest physical field evolution. It has the most uneven distribution (average temperature variance of 4 °C2), the strongest flow (average flow velocity of 0.4 m/s), the highest cooling rate (0.632 °C/h), and the lowest temperature (14.84 °C at the end). Its physical field is influenced by both the atmosphere and crude oil. The evolution of the physical field of crude oil is the most complex. It lags behind the gas at the top of tank and is directly effectted by it. Based on the evolution characteristics of the flow field of crude oil, the cooling process is divided into three stages: Stage I (0–––10 h) is the stage of convection generation and evolution in the crude oil region; Stage II (10 h − 34 h) is the stage of convection stability in the crude oil region; Stage III (after 35 h) is the stage of flow field transformation of crude oil. In stages I and II, the flow and momentum exchange at the oil–gas interface are significant. Crude oil is jointly influenced by the natural convection of the gas at the top of the tank and its own natural convection, forming a counterclockwise large vortex structure. The low-temperature area is near the central axis boundary of storage tank, oil–gas interface, and tank wall. The high-temperature area is within a range of 0.1 m − 3.3 m from the tank wall. After entering stage III, the flow and momentum exchange at the oil–gas interface weaken. The flow field of crude oil is only controlled by its own natural convection and transforms into a clockwise large vortex dominated. The low-temperature area is concentrated in the enclosed area of “oil–gas interface − tank wall” and “oil–water interface − tank wall”. The temperature field changes accordingly. Eventually, the high-temperature area is concentrated in the area slightly above the center of the tank. The physical field evolution of bottom water lags behind crude oil and is most unstable. Its cooling rate is 0.164 °C/h, slightly higher than crude oil’s 0.157 °C/h. The temperature is always slightly lower (33.47 °C at the end), and the physical field is the most uniform (average temperature variance of 0.0003 °C2), affected by the tank bottom environment and liquid crude oil.

Experimental study on the thermal management performance of immersion cooling for 18650 lithium-ion battery module

Direct liquid cooling technology stabilizes the battery module at the ideal operating temperature by leveraging the coolant's high heat capacity and its heat dissipation ability through circulation. This study introduced a forced-flow immersion cooling method employing transformer oil as the cooling medium for 18650 lithium-ion battery modules. The performance of this cooling system design was assessed under various discharge rates, coolant flow rates, and channel positions. Experimental data reveals that the average temperature of the oil-immersion-cooled battery module was around 26.3% lower than that of the naturally air-cooled battery module under a 2C discharge condition with zero flow rate. The cooling capacity of the oil-immersion system was limited, with theoretical analyses indicating an optimal flow rate of 200mL/min. Four unique cooling channel configurations was designed: side center inlet to center outlet, side upper inlet to lower outlet, front upper inlet to lower outlet, and front center inlet to center outlet. The peak temperatures of the battery module for these setups were 31.7 ℃, 31.0 ℃, 31.0 ℃, 31.0 ℃, and 31.6 ℃, respectively, with a temperature difference of about 2 ℃. Notably, the side upper inlet to lower outlet channel configuration displays superior cooling performance. These findings contribute to advancing more efficient cooling systems and offer valuable insights for optimizing direct liquid-cooled thermal management systems for lithium-ion batteries in the future.