Prediction Of Temperature Rise Research Articles

Research on temperature rise prediction model for circuit breaker based on numerical laplace transform

Abstract The temperature rise in circuit breakers' thermal paths is a critical indicator influencing their tripping characteristics, directly affecting response speed, reliability, and safety. Existing models for predicting circuit breaker temperature rise are often structurally limited, lack generality, and exhibit low predictive accuracy. Addressing this issue, this paper investigates an efficient, precise, and widely applicable theoretical model for predicting circuit breaker temperature rise. This model focuses on the thermal conduction mechanisms within small-scale circuit breakers, establishing a fundamental numerical heat transfer model based on Newton's cooling formula and Fourier's heat conduction law. By applying numerical Laplace transformation, the model is simplified into the complex frequency domain, and employing residue theorem for solving, it is transformed back into the time domain using Laplace inverse transformation to derive the predictive model. Experimental validation using a 32A rated current circuit breaker demonstrates the model's high predictive accuracy, suitability across various circuit breaker structures, with an average deviation below the permissible deviation in industry standards. This research holds significant implications for enhancing the thermal tripping characteristics of circuit breakers.

Machine‐Learning‐Based Accurate Prediction of Vanadium Redox Flow Battery Temperature Rise Under Different Charge–Discharge Conditions

ABSTRACTAccurate prediction of battery temperature rise is very essential for designing efficient thermal management scheme. In this paper, machine learning (ML)‐based prediction of vanadium redox flow battery (VRFB) thermal behavior during charge–discharge operation has been demonstrated for the first time. Considering different currents with a specified electrolyte flow rate, the temperature of a kW scale VRFB system is studied through experiments. Three different ML algorithms; linear regression (LR), support vector regression (SVR), and extreme gradient boost (XGBoost) have been used for prediction. The training and validation of ML algorithms have been done by the practical dataset of a 1 kW 6 kWh VRFB storage under 40 , 45, 50, and 60 A charge–discharge currents and 10 L min−1 of flow rate. A comparative analysis among ML algorithms is done by performance metrics such as correlation coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE). XGBoost shows the highest R2 value of around 0.99, which indicates its higher prediction accuracy compared to other ML algorithms used. The ML‐based prediction results obtained in this work can be very useful for controlling the VRFB temperature rise during operation and act as an indicator toward further development of an optimized thermal management system.

A mechanism-data driven resistance transfer algorithm for lithium-ion batteries and its application to thermal modeling

In this paper, a resistance transfer algorithm (RTA) is proposed to transfer a known battery's resistance data to a new battery, it saves the cost of testing required for thermal modeling. Firstly, the resistance linearization process is derived based on the Arrhenius equation, and a calibration algorithm for the resistance transfer from the reference battery to the target battery is presented. Then, taking the NCM622 battery (50 Ah) as the reference battery, the RTA is performed on an NCM622 battery (51 Ah) to verify the feasibility. Three schemes are compared to explore the appropriate test number of the target battery required for RTA. Subsequently, the RTA is applied to construct the thermal model of the target battery, and the simulation of the NCM622 (51 Ah) battery temperature rise is completed. Finally, RTA is utilized for resistance transfer and temperature rise simulation at different temperatures for four different batteries to further explore the universality. The verification results demonstrate that the proposed RTA can save a significant amount of resistance testing time and the thermal model based on RTA can supply precise temperature rise prediction. In the cost-effective 4-SOC scheme, the number of resistance test points can be reduced by 55 %, the maximum error of the transferred resistance remains within 0.1495 mΩ and the maximum error of the simulated temperature rise at three ambient temperatures stays below 1.727 °C.

Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting

5MW wind turbine gearbox high-speed bearing temperature rise failure is one of the important factors affecting the stable operation of the wind turbine, accurate prediction and timely diagnosis can effectively improve the efficiency of the wind turbine. In this paper, a combined modelling wind turbine gearbox high-speed bearing temperature rise prediction method based on Bayesian-LightGBM and improved PSO-SVM is proposed with a 5 MW wind turbine as the research object. Firstly, the initial dimensionality reduction of SCADA data is performed by sparse random projection matrix, which reduces the redundant data. Secondly, feature selection is performed on the remaining data using Bayesian-LightGBM to identify 13 key input feature parameters. Then, the hyperparameters of the PSO algorithm are optimised using Bayesian algorithm and further, the optimised PSO algorithm is applied to identify the SVM parameters. Finally, a simulation experiment platform is established based on MATLAB to verify the temperature rise of high-speed bearings in gearboxes of wind turbines by example calculation and comparative analysis. The results show that the model established in this paper is effective, the prediction results are accurate and the performance is stable, and then compared with the algorithms such as PSO-SVM, SVM, BP, etc, the coefficient of determination of the algorithm is greater than 0.994 in both the training set and the test set, and the average decision percentage error is around 1.88% in both.

Prediction of the Upwarp Buckling Critical Temperature Rise for Longitudinally Connected Slab Track Under Joint Damage State

The joint of longitudinally connected slab track is vulnerable to damage from environmental impacts and repeated train loads. Under high temperature environments, the joint becomes a high risk area for track slab upwarp, which significantly affects the upwarp stability of the track slab and the safe operation of trains. This study employs the arc length approach and a finite element model to investigate the upwarp equilibrium development path of the track slab, the upwarp evolution process of the track slab under the joint damage is further analyzed. Then, the influence of different initial defects on the vertical stability of the track slab is studied. Utilizing dimensional analysis, a general formula for calculating the critical temperature rise of the track slab is proposed. The results are as follows: (1) The entire upwarp process of track slab under joint damage can be divided into three stages: stability, upwarping development, and instability. (2) A nonlinear correlation exists between the upwarp critical temperature rise of the track slab and three types of initial defects. Height defects in narrow joints exert the most significant impact on the critical temperature rise, followed by initial Out-of-straight (initial OOS), with the initial bending shape having the least effect. The complete defect of the narrow joint reduces the upwarp critical temperature rise of the track slab by 53.26°C, a 48.4% reduction. (3) A unified expression, derived from the characteristic parameters of initial defects and dimensional analysis, can more accurately predict the upwarp critical temperature rise of the track slab.

Research on Temperature Rise Characteristics Prediction of Main Shaft Dual-Rotor Rolling Bearings in Aircraft Engines

Traditional aero-engine bearings rotate simultaneously with their inner and outer rings, which makes the temperature rise prediction model computationally large with low accuracy, and it cannot be accurately verified due to the means of testing. This paper presents a method for predicting the temperature rise characteristics of aero-engine bearings under composite load conditions. Firstly, the local method is used to calculate the heat generation from heat sources such as bearing spin, lubricant drag, and the differential sliding of steel ball and collar, respectively, then finite element modelling and steady-state thermal analysis are carried out for aero-engine bearings under the simultaneous action of axial and radial external loads, a double-rotor test setup is designed and the predictive model is validated, and finally, the influences of rotational speed and load on the temperature rise characteristics of the bearings are investigated. The study shows that the aero-engine bearing prediction model proposed in this paper has high accuracy; with the increase in the rotational speed of the inner ring of the bearing, the temperatures of both the inner and outer rings of the bearing increase significantly; the temperatures of the inner and outer rings of the bearing increase with the increase in the axial load, and the effect of the radial load on the temperature of the bearing is not obvious.

A Novel Temperature Rise Prediction Method of Multi-component Feed System for CNC Machine Tool Based on Multi-source Fusion of Heterogeneous Correlation Information

A Novel Temperature Rise Prediction Method of Multi-component Feed System for CNC Machine Tool Based on Multi-source Fusion of Heterogeneous Correlation Information

Full-scale experimental study on combustion characteristics and smoke temperature of double-source fires in different tunnels

Through a series of full-scale fire tests conducted in three different tunnels, the common characteristics of combustion and smoke temperature of double pool fires in actual operation tunnel environments are investigated. The evolution process of the coupling effects of shielding entrainment and thermal feedback enhancement is revealed. It is found that the ventilation state and the fire source spacing can alter the dominant relationship between the shielding entrainment effect and the thermal feedback enhancement effect, resulting in different evolution patterns of combustion characteristics and smoke flow patterns of double pool fires in tunnels. The heat release rate increases by 4 times when the double pool fire flames merge under the longitudinal ventilation compared with the double pool fire flames without fusion under the natural ventilation. The flame tilt angles of double pool fires were determined through the image processing method, and the prediction model of the flame inclination angle of downstream fire sources was established, considering fire source spacing. At the same time, the characteristic of temperature measured by Fiber Bragg Grating in double-source fire scenarios was investigated, developing a model to predict the longitudinal temperature rise distribution. It is found that the maximum temperature rise prediction model based on steady-state fire has poor applicability in the weak-plume fire scenario of full-scale tunnels. The analysis of the smoke flow patterns shows that the two-stage ventilation is more suitable for smoke control compared to full longitudinal ventilation in tunnel double-source fire accidents, especially for ensuring the safety of individuals trapped in the area between the two fire sources.

Prediction of temperature rise in ball-on-disk contacts under electromechanical loading

Traction motor bearings in electric vehicles fail prematurely due to electrical environments. Current flow through the bearings causes lubricant degradation due to a rise in the contact temperature. This study utilizes experimental and numerical methods to predict the expected temperature rise in ball-on-disk contacts subjected to electromechanical loading. Contact resistance and temperature rise are measured using a modified tribo device under static, dynamic, lubricated, and unlubricated conditions. The contact resistance depends on the magnitude of the current applied and contact conditions. A numerical model is proposed to predict the temperature rise at the electromechanical contact and is verified with measured temperatures. Prediction of contact temperatures due to electromechanical loads will assist in life estimation and development of appropriate lubricants.

Thermal Response Characteristics of Concrete-Filled Steel Tube Columns with Flame Encapsulation Thickness

In order to elucidate the influence of flame encapsulation thickness on the thermal response characteristics of concrete-filled steel tube columns in a fire environment, a study was conducted focusing on the primary control mechanism of heat radiation power from fire——the thickness of fire encapsulation. The thermal resistance effect at the interface between the steel tube and concrete, as well as the temperature rise characteristics of the flame, were comprehensively considered. A calculation method was established for the thermal response characteristics of concrete-filled steel tube columns under different flame encapsulation thickness conditions, providing support for the simulation of thermal response and temperature rise prediction of concrete-filled steel tube columns in fires. The results indicate that the flame emissivity and radiant heat power increase with the increase of flame encapsulation thickness. As the flame encapsulation thickness gradually increases, the growth trend of flame radiant power slows down. When the flame encapsulation thickness L < 1 m, the temperature rise rate of the concrete-filled steel tube column is significant. When the flame encapsulation thickness L ≥ 1 m, the temperature rise rate of the concrete-filled steel tube column tends towards a constant value.

Experimental study on the effects of branch tunnel ventilation on the smoke movement and temperature characteristics in bifurcated tunnel fires

A series of fire tests were conducted in a bifurcated tunnel model with branch tunnel ventilation. Three fire locations were considered. The characteristics of smoke movement and temperature profile under various fire source location scenarios were analyzed. The results indicate that when the fire source is not at the intersection, the ventilation airflow in the branch tunnel is diverted at the intersection before it is imposed on the fire source, which results in the actual velocity of ventilation air imposed on the fire source being less than the velocity of ventilation air in the branch tunnel. A new parameter, named the diversion coefficient, was introduced for convenient analysis. By substituting the diversion coefficient values into a classic maximum temperature rise prediction model for the single-line tunnel fires, good prediction results were observed. Moreover, a new dimensionless smoke temperature decay model was developed. The applicability of the model was validated using full-scale fire test data from previous research. The dimensionless temperature decay law of smoke was analyzed based on the newly established model. Results show that when the fire is positioned at the intersection, the decay coefficient of the smoke downstream of the fire decreases linearly as the ventilation rate increases, while decay coefficient of the smoke upstream of the fire decreases slowly at first and then increases with the increase of ventilation rate. When the fire source is not at the intersection, the branch tunnel ventilation conditions could be classified into three categories: sub-critical, critical, and super-critical velocity. Changes in the ventilation velocity within the branch tunnel have little influence on temperature decay process of smoke in the main tunnel under critical and sub-critical velocity conditions. However, under super-critical velocity conditions, the smoke temperature decreases rapidly after reaching the intersection. Furthermore, predictive models for the critical velocity of the branch tunnel under various fire locations were established based on theoretical analysis and experimental data. Within a specific range of heat release rate, the critical velocity is proportional to the cube root of the heat release rate. Compared to when the fire is located at the intersection, the critical velocity is reduced significantly when the fire is not in the intersection.

Experimental study on the temperature distribution of impingement flow in a double slope roof generated by jet fire

The double slope roof is a commonly used building structure due to its adequate drainage and stable structural features. The thermal impinging on the double slope roof generated by the jet fire caused many casualties and property damage, whose thermal hazard has not been quantified in literatures. The temperature distribution at different source-ridge heights (H), heat release rates (HRR), and roof angle (θ) was measured in the experiment, with a total of 125 sets of experimental conditions. Results show that the ceiling maximum temperature rise increases with the roof angle decreases. A maximum temperature rise prediction model was established based on the analysis of the free plume length beneath the roof, which considering the effect of θ. Moreover, the model's accuracy was validated by comparing previous experimental data. The mean deviation between the proposed model and the experimental results is less than 5.7 %. The rate of temperature decay beneath the ridge decreased as the θ decreased. When the H is smaller, and the HRR is larger, the influence of the θ on the temperature decay profile is more significant. A new correlation has been proposed to correlate the temperature decay profile of a double slope roof with different θ by introducing flame extension length to modify the characteristic radius b. The model prediction agreed well with the experimental data, with a maximum error of around 20 %. New findings are helpful in guiding the building fire prevention and detection design.

An experimental investigation into the fire behaviors and smoke characteristics of continuous spill fires in road tunnels

Continuous fuel spill fires are a common accident scenario which needs to be considered for the safe operation of tunnels, given the potential threat posed to trapped persons. In this paper, a series of continuous spill fire experiments on a concrete surface were studied using a 1/8 reduced-scale tunnel model. Gasoline was used as the discharge fuel and the discharge rate varied from 1.5 to 5.2 ml/s. The burning area, steady regression rate, smoke front arrival time, and ceiling temperature were analyzed. The results show that the burning area spreads slowly following an initial rapid spill stage, with the spread process following a pattern of exponential decay. The steady regression rate is found to be approximately 63% of that of pool fires for the same burning area. At the same heat release rate, the smoke front moves faster for spill fires than pool fires because of the larger burning area, and a correlation is built to predict the smoke front arrival time. Finally, a ceiling temperature rise prediction model is developed which considers the spread and burning processes of the fire. The results are of practical importance in the quantitative risk assessment of liquid fuel fire accidents in tunnels, and their implications for personnel evacuation.

Judgment method of the dynamic threshold value of motor protection at a dynamic load rate

To address the shortcomings of traditional motor thermal protection, which uses the motor’s temperature or temperature rise threshold operating at full load as the basis for the judgment method, a dynamic threshold judgment method based on a study of the motor’s temperature rise characteristics under a dynamic load rate is proposed. Taking a forced air-cooled, three-phase asynchronous motor with 11 kW power as the research object, a 2D/3D motor model under steady-state conditions is established. The loss distribution of asynchronous motors at different load rates is obtained through electromagnetic field simulation calculations. The finite element method is used to simulate and calculate the motor’s temperature field. Taking ambient temperature and load factors into account, the study takes place from the perspective of motor temperature rise in order to acquire the law governing the change in motor temperature increase under various working circumstances. A method of converting the temperature and warming between the motor’s stator, winding, and rotor is proposed. A dynamic threshold judgment system for accurate warning of overheating problems in motors under any load rate is set up so that the thermal protection of motors can accurately be judged under variable load conditions, which offers a crucial theoretical foundation for the design of intelligent motor temperature rise prediction systems. It contributes to a methodological underpinning for the diagnosis and early warning of thermal health in smart motor systems.

Dynamic Temperature Prediction on High-Speed Angular Contact Ball Bearings of Machine Tool Spindles Based on CNN and Informer

This study addressed the issues related to the difficulty of determining the operating status of machine tool spindle bearings due to the high rotational speeds and rapid temperature fluctuations. This paper presents an optimized model that combines Convolutional Neural Networks (CNNs) and Informer to dynamically predict the temperature rise process of bearings. Taking the H7006C angular contact ball bearing as the research object, a combination of experimental data and simulations was used to obtain the training dataset. Next, a model for predicting the temperature rise of the bearing was constructed using CNN + Informer and the structural parameters were optimized. Finally, the model’s generalization ability was then verified by predicting the bearing temperature rise process under various working conditions. The results show that the error of the simulation data source model was less than 1 °C at steady state; the temperature error of the bearing temperature rise prediction model was less than 0.5 °C at both the temperature rise and steady-state stages under variable rotational speeds and variable load conditions compared to Informer and Long Short Term Memory (LSTM) models; the maximum prediction error of the operating conditions outside the dataset was less than 0.5 °C, and the temperature rise prediction model has a high accuracy, robustness, and generalization capability.

Numerical Computation of Temperature Rise of Gas‐Insulated Transmission Lines Considering Thermal Properties of Insulating Gas

Accurate temperature rise prediction of the gas‐insulated transmission lines (GIL) can help to lower the cost of equipment through optimization design. To investigate the temperature rise of GIL and the heat transfer efficiency of new eco‐friendly insulating gas, the electromagnetic‐thermal‐fluid field coupling method that considers the thermal properties of solid and gaseous media is proposed. The finite element method is applied to solve the eddy‐current field and obtain the Joule loss of the conductive rod and the enclosure accurately. The GIL temperature distribution of different insulating gases is computed based on their thermophysical parameters. The heat transfer efficiency is found to be positively correlated with gas density, constant pressure heat capacity and thermal conductivity. A parameter that characterizes the heat transfer efficiency of the insulating gas is defined, such that a larger value indicates a higher heat transfer efficiency. This parameter helps to quickly determine the heat transfer capacity of new eco‐friendly insulating gas, and facilitate the optimal design of GIL equipment. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Optimization Design and Experimental Study of Cooling System in a High Voltage Induction Motor after Power Density Upgrade

Background: In order to upgrade a motor based on the YXKK450-2 for high power density with high efficiency, low energy consumption, and low weight with the same volume, its power is increased from the original 900 kW to 1250 kW. To ensure good ventilation and heat dissipation characteristics, it is necessary to redesign the ventilation and cooling system of the entire machine. Methods: Based on the finite volume method, a physical model of the entire flow field of the motor's inner and outer air passages was established. The internal and external cooling systems of the motor were simulated, and the fluid flow law of the cooling system was realized. By extracting the pressure difference between the inlet and outlet of the cooler and the circulating cooling air velocity in the inner air passage, the boundary conditions for calculating the flowheat coupling field were determined. The temperature rise trend and overall temperature distribution were obtained. Results: The results of the test resistance method were in good agreement with the numerical simulation test results, The temperature rise error was 4%, and the wind speed value error was 2.7%, all within allowable limits (<s5%), verifying the accuracy and effectiveness of the calculation method. Conclusion: An accurate prediction of motor temperature rise, fluid flow law, and temperature distribution is achieved.

Temperature and humidity sensor monitoring of directly buried cable based on temperature field distribution simulation of power cable

Power cable is a piece of major transmission equipment, and its operating temperature as a major factor determines whether the cable system can operate safely and reliably and the current-carrying capacity. Therefore, it is of great significance to master the real-time temperature and the distribution of the power cable core. During the aging of cable insulation, temperature, as a major factor, directly determines the aging rate. One of the basic parameters on the power cable is the ampacity. If the ampacity is high, the cable will be overloaded. In this paper, the thermal circuit method is used to construct and calculate the cable, and the whale algorithm is used to estimate the temperature of the cable conductor. The conductor is estimated accurately within the allowable error range. The results are compared with the results of finite element simulation to verify the effectiveness of the finite element method. Through the experimental analysis, the model is established according to the cable trench on the spot. The steady-state temperature field is calculated through parameter setting. The average packet loss rate is 0.066 %, and the relative error is 0.32 %, which proves that this study can optimize the communication mode of the network and achieve a better monitoring effect. The method realizes the real-time temperature rise prediction of the cable core conductor by using the temperature rise of the outer skin. It can provide a certain theoretical basis for the online monitoring and engineering practical application of the cable core temperature and has practical significance.

A theoretical study on the hydrogen filling process of the on-board storage cylinder in hydrogen refueling station

With the development of the hydrogen fuel automobile industry, higher requirements are put forward for the construction of hydrogen energy infrastructure, the matching of parameters and the control strategy of hydrogen filling rate in the hydrogen charging process of hydrogen refueling stations. At present, the technological difficulty of hydrogen fueling is mainly reflected in the balanced treatment of reducing the temperature rise of hydrogen and shortening the filling time during the fast filling process. Vehicle hydrogen storage cylinder (VHSC) is one of the important components of hydrogen fuel cell vehicles. This study proposed a theoretical model for calculating the temperature rise in the VHSC during the high pressure refueling process, and revealed the hydrogen temperature rise during refueling. A hydrogen temperature rise prediction model was constructed to elucidate the relationship between filling parameters and temperature rise. The filling process of VHSC was analyzed from the theoretical method. The theoretical analysis results were consistent with the simulation and experimental analysis results, which provided a theoretical basis for the current hydrogen temperature control algorithm of the gas source in the hydrogen refueling station, and then reduced the energy consumption required for hydrogen cooling in the hydrogen refueling station.

A real-time temperature rise prediction method for PM motor varying working conditions based on the reduced thermal model

Real-time and accurate temperature rise calculation can play a preventive role in preventing overheating motor damage. This article proposes a temperature rise calculation method for varying working conditions PM motors based on a reduced order model. The calculation model of this method consists of a thermal conductance matrix and a heat source matrix. The thermal conductance matrix is obtained by reducing the order of the detailed lumped parameter thermal network (DLPTN) conductance matrix, which significantly reduces the model order while retaining computational accuracy. A loss prediction function is introduced in acquiring the heat source matrix, which is constructed based on the relationship between motor loss and speed and power. It can predict the stator iron loss and PM loss with different speeds and powers in real-time, ensuring the accuracy of heat source loading. The experimental results show that this method can predict the temperature rise of critical nodes of the PM motor in real-time under varying working conditions. Its calculation results have high accuracy, providing an effective method for overheating PM motor protection.