Hot Spot Temperature Research Articles

Periodic open cellular structures (POCS) as catalyst support for intensified heat transport in the partial oxidation of methanol to formaldehyde

Heat transport in catalytic reactors is one of the most important factors in reactor design, especially for highly endo- or exothermic reactions. The limited thermal conductivity of randomly packed beds can be significantly improved when alternative catalyst supports are used. A new generation thereof are periodic open cellular structures (POCS), which are used in this study as catalyst support for the partial oxidation of methanol to formaldehyde, an exothermic gas phase reaction. A comparison to traditional packed bed reactors revealed that a POCS made of the highly conductive alloy AlSi10Mg can significantly reduce the hot-spot temperature, allowing almost isothermal operation at optimal reaction conditions. The improved temperature control allows for operation with higher methanol inlet concentrations and wall temperatures as compared to the commercial process. The beneficial heat transport properties of POCS were used to conduct isothermal kinetic measurements at elevated temperature. Based on these findings and the design freedom of additive manufacturing, an optimized cellular structure was designed and fabricated, which improved the heat transport especially in the critical inlet section of the reactor.

The residual life prediction of power grid transformers based on GA-ELM computational model and digital twin data

As one of the core equipment of the power grid, the operation status of transformers directly affects the stability and reliability of the power system. To accurately evaluate the remaining life of power grid transformers, a genetic algorithm is applied to optimize the Extreme Learning Machine based on digital twin technology. Then, considering changes in load rate, a residual life prediction model for power grid transformers is constructed. From the results, the error of the research method was within 2℃, with a maximum error of only 1.76℃. The research model converged with a fitness value of 0.04 at 150 iterations. It showed good predictive performance for hot spot temperatures under different load rates, with an average accuracy of 99.97%. Compared with backpropagation models and extreme learning machine models, the research method improved accuracy by 2.85% and 1.01%, respectively, with small and stable prediction errors. It verified the superiority of the research model, indicating that the research method can improve the accuracy of predicting the remaining life for power grid transformers. By monitoring the operation status of transformers in real-time, potential faults can be detected in a timely manner. The maintenance and replacement can be carried out in advance to avoid power outages caused by equipment damage. In addition, the research can provide reference for the planning and design of power systems, and support the stability and reliability of power systems.

Numerical study on the critical characteristics of internal short-circuit hot spot in lithium-ion batteries

High current density resulting from internal short circuit (ISC) in lithium-ion batteries leads to rapid local temperature rise, forming a hot spot. This study quantitatively characterized the critical properties of ISC hot spot in batteries. ISC hot spot in batteries exhibit two different evolution patterns. When the short circuit resistance approaches the internal resistance of the battery, the hot spot temperature reaches its peak at 1165 K. The thermal runaway characteristics of batteries vary depending on the short circuit resistance, with the hot spot growing and spreading rapidly when the resistance value is 30 mΩ. In addition, a modeling study was conducted to examine the critical characteristics of short circuit resistance. At a hot spot radius of 2 mm, the critical resistance was determined to be 281 mΩ, accompanied by a critical hot spot temperature of 562 K. Under subcritical conditions, the SEI film decomposes completely, while the electrolyte undergoes minimal decomposition. Interestingly, it was observed that the critical resistance and critical hot spot temperature decrease as the hot spot radius increases. Finally, the study quantified the effects of hot spot thermal conductivity, convective heat transfer coefficient, and hot spot position on the critical threshold of hot spots. These findings provide valuable references for the design of batteries with high critical thresholds.

Non-equilibrium thermal transport study in steady state GaN MISHEMT channel layer based on electron Monte Carlo and phonon BTE

An electro-thermal coupling simulator for GaN devices based on electron Monte Carlo (e-MC) simulations is established. Taking GaN Metal Insulator Semiconductor High Electron Mobility Transistor (MISHEMT) as example, the non-equilibrium thermal transport processes of self-heating effect in the channel layer are studied. This simulator is mainly coupled by e-MC and the phonon Boltzmann transport equation (pBTE), physical property parameters and electric field parameters are provided by first-principles and Technology Computer Aided Design (TCAD), respectively. We first verify the e-MC program by calculating the electron transport properties of GaN materials, verify the feasibility of the established GaN MISHEMT model by using TCAD and obtained its operating characteristics. Further, the simulator is used to evaluate the non-equilibrium processes inside the channel layer in detail, the results show that there is significant consistency in the peak positions of electric field strength, heat generation and diffusion temperature, the diffusion temperature peak occurs at the secondary peak of heat generation. The frequency distribution of phonon emission under different drain-source bias voltages is revealed by phonon emission spectrum analysis. The strength of the non-equilibrium effect is measured by effective temperature. Increasing the drain-source bias voltage will significantly increase the peak temperature of hotspot and further enhance the non-equilibrium effect. Our study reports an efficient scheme for electro-thermal simulations of GaN MISHEMT, which provides insights for thermal management of GaN-based transistor devices.

Hotspot temperature analysis of distribution transformer under unbalanced harmonic loads using finite element method

In an electrical power distribution system, harmonic distortion is the most prominent power quality problem that causes long-term adverse effects such as failure of distribution transformers. Considering that most transformer problems are caused by heat losses due to the presence of harmonics, it was decided to use a numerical method with the highest accuracy, finite element method (FEM) to analyze the hot spot temperature (HST) of the thermal distribution transformer model. Through the use of COMSOL Multiphysics software, three phases of unbalanced harmonic loads are considered, which contribute to three different total harmonic distortion current (THDI) levels and five different insulation temperature classes. Using the IEEE C57.110-2018 guidance, the simulation outputs are then verified with HST results from the HST mathematical model. The findings indicated that with the increased loadings, the unbalanced harmonic currents have impacted the HST increment and distinguished the HST values between the phases.

Thermal-flow characteristics analysis of a novel resilient capacity ceramic insulated winding dry type transformer

With the increasing demand for the resilient capacity of transformers in high-proportion renewable energy grids, the overload capacity of transformers and the thermal conductivity of winding insulation materials have been put forward as important requirements. In response to these requirements, a novel ceramic high temperature tolerance insulation winding is proposed in this paper and is applied in a ceramic insulated winding transformer. A combination of simulation and experimentation is used to analyze the thermal-flow characteristics of this transformer. The temperature and flow field distribution characteristics of transformers with both winding insulation methods (ceramic and Nomex paper) are compared. The internal mechanism of reflux near the iron core and high voltage winding under forced air cooling is clarified. A superior outside cooling condition is obtained. A prototype ceramic insulated winding transformer is developed and tested to verify the accuracy of the simulation model. The results show that the hotspot temperature of the ceramic insulated winding transformer under natural cooling is 10.7% lower than that of the Nomex paper insulated winding transformer. With forced air cooling of 2, 3, 4, 5, and 6 m/s applied at the bottom, the hotspot temperature of the ceramic insulated winding transformer is 11.4%, 10.5%, 9.7%, 14.0%, and 17.8% lower than that of the Nomex paper insulation winding transformer, respectively. Under forced air cooling, a reflux phenomenon is observed in both transformers in the vicinity of the iron core and high voltage winding due to the formation of adverse pressure gradient region and wall viscous force blocking. The strength of the reflux is affected by the magnitude of the forced air cooling flow velocity and the construction of the transformer. The optimal range of the external cooling flow velocity for the ceramic insulated winding transformer is 3–4 m/s. The errors between the simulated temperature and the measured temperature at the nine monitoring points of the prototype are all less than 5%, which verifies the effectiveness of the simulation model. The experimental and theoretical basis for the design and application of resilient capacity dry type transformers is provided by this research.

Methods of determining internal damage in power transformers

Due to the variety of defects that arise in electrical machines, it is necessary to use more effective methods for monitoring their condition. All over the world research and development of new means and methods for monitoring powerful electrical machines during their operation is underway. Some examples of recent advances are vibration diagnostic methods for assessing the compaction of components inside a transformer, acoustic and electrical systems for monitoring partial discharges, data processing using digital methods, and new sensors for continuous monitoring of gases and moisture in oil, as well as hot spot temperatures. Additionally, thermal imaging testing of power equipment is also an important tool to ensure reliable operation. It is believed that the most effective method is gas chromatographic oil analysis, which can identify most defects in oil-filled equipment. During the operation of powerful electrical machines, the use of existing non-destructive testing methods does not allow a complete assessment of the condition of the main parts of the equipment, as an analysis of damage locations shows, 25% are damage to the core and windings. Effective monitoring of the condition and determination of the performance of transformers is of particular importance, since they are key elements in the operation of nuclear power plants. The paper considers the possibility of using the eddy current testing method; determining a defect in magnetic core steel is based on fixing the unevenness of the magnetic field on the horizontal or vertical planes of a yoke or rod consisting of electrical steel plates. Monitoring and evaluating the functioning of existing equipment, detecting deficiencies in the early stages of their development, when repair costs are still minimal, and preventing emergency failures become a priority. In accordance with the growth rate of detected deficiencies, monitoring is carried out from time to time or continuously, the maximum number of monitored characteristics is achieved when the transformer is fully tested to determine its functionality.

Enhancing the methanol yield of industrial-scale fixed bed reactors using computational fluid dynamics models

Achieving our decarbonisation goals for the maritime transport sector requires the bulk production of liquid hydrocarbon fuels, suitable for the existing infrastructure, such as methanol (MeOH). For this, optimisation of fixed bed chemical reactors is vital. Unlike demonstration-scale setups, optimising the design of such reactors using Computational Fluid Dynamics (CFD) models is both cheaper and faster. In this study, using a 2D pseudo-homogeneous CFD model, a single tube from a multi-tubular industrial-scale MeOH reactor is simulated. Using available experimental data, the CFD model was validated yielding excellent accuracy, with an average error of 2.6 %. The model identified a temperature hot-spot near the bed entrance, while the predicted pressure drop was 11 % of the operating pressure. Both effects could considerably reduce the efficiency of the reactor, either by catalyst deactivation or by increasing the compressor requirements, respectively. Through a parametric study where the tube’s length and diameter were varied within the ±50 % range, 53 total cases are produced and solved, creating an extensive pareto set of data for the key output parameters, such as methanol production, pressure, and temperature. A response surface was also generated, revealing the interconnection between the tube’s design and the operating parameters. This enabled a performance optimisation of the reactor design for two industrially relevant scenarios, with the optimised reactor achieving a 6.9 % higher MeOH yield and a 75 % reduced pressure drop. Through industrial involvement, the reactor can be further optimised, and would act as a critical foundation for more extensive techno-economic and socio-economic evaluations for sustainable carbon–neutral methanol production.

Calculation method of electromagnetic losses and hot-spots temperature of giant magnetostrictive transducer

Due to the complex energy conversion processes and limited avenues for heat dissipation in the giant magnetostrictive transducer (GMT). Large losses and elevated internal temperature rise are inevitable, this would bring into serious reliability problem for GMT. Accurately analyzing its electromagnetic losses and hot-spots temperature are crucial for designing and optimizing the transducer. High-power GMT typically use permanent magnet (PM) to provide a bias magnetic field for enhanced power density. Although, this structure could significantly reduce the volume of driving part, it also caused issues such as non-uniform magnetic field distribution and bias magnetic field, which have great influence on the magnetic energy loss and hot-spots temperature rise. The previous researches seldomly investigate these influences on total loss at GMT system level. Additionally, the differential excitation coil loss caused by AC resistance among multi-layers can’t be neglected, which can lead to variations in coil loss and temperature rise. Therefore, this paper proposed a detailed electromagnetic losses and hot-spots temperature rise calculation model from material level to GMT system level. This method can obtain the distribution of electromagnetic losses within multiple factors, and the hot-spots temperature rise considering the temperature non-uniform distribution. Firstly, we have developed a precise loss calculation model, which takes the influence caused by PM bias and non-uniform magnetic field on magnetic energy loss into account. Additionally, the proposed model could conclude the impact of inter-coil resistance variations on the eddy current loss in excitation coil. Secondly, based on of the non-uniform distribution of losses in driving part, using the divisional thermal modeling approach and a 2-D T-shaped equivalent thermal network, we further constructed a transient temperature calculation model for GMT. This approach can effectively improve the energy conversion efficiency of GMT, so as to enhance the thermal reliability of the transducer. Finally, a testing system for the loss-thermal of GMT was established to validate the effectiveness of proposed model. Results indicate that the average error between our loss calculation model and experimental results is 2.93%, while the corresponding error for without considering the above factors is 15.97%. This confirms the necessity of conducting a detailed electromagnetic losses calculation model. In addition, the average error of the temperature rise calculation model is less than 5%, while the error for without considering the losses distribution and heat dissipation paths difference is exceed 10%. In conclusion, our proposed method accords well with the measured results, and can provide significant fundamental for design and optimization of GMT.

Enhancing Heat Transfer Efficiency in Permanent Magnet Machines through Innovative Thermal Design of Stator Windings

This paper investigates innovative methods for enhancing heat transfer efficiency in high-power permanent magnet electrical machines. The objectives are to quantify the effects of increasing the air speed, increasing the turbulence intensity, and introducing the spacing between windings on cooling performance. The cooling of stator windings is studied through experimental wind tunnel testing and Computational Fluid Dynamics (CFD) modelling. The CFD model is validated against wind tunnel measurements to within 4 Kelvin (K). The results demonstrate that each enhancement method significantly improves the cooling capability. Increasing the air speed from 10 m/s to 40 m/s reduces the winding hotspot temperature by 34%. Introducing a high turbulence intensity of 40% leads to a 21% lower hotspot temperature compared to 0.5% turbulence intensity. Creating a 1.5 mm spacing between coils also substantially improves convection and conduction heat transfer. Overall, combining these optimised design parameters yields over a 40% reduction in hotspot temperature compared to the original design. This research provides practical guidance for maximising heat transfer efficiency in high-power permanent magnet machines, without increasing complexity. The findings will lead to higher machine efficiency, reliability, and longevity for aerospace and other applications.

Ambient temperature modelling from surface characteristics and associating urban morphology with thermal discomfort

Urban heat island assessment is of paramount importance when monitoring microclimate changes, increased heat stress, mortality and energy consumption. Simply analysing land surface temperature patterns for human comfort and health assessment is often inadequate. In this study, we attempt to resolve this inadequacy with ambient temperature modelling from multiple surface characteristics for a tropical megacity. A 336 datapoint‐based multilinear regression model was formulated to predict the maximum summer air temperature with a mean absolute error of 0.694°C. Specific locations of critical thermal environments were demarcated with Getis‐Ord statistic. Based on our results, extreme hotspots covered 10.53 per cent of the city on a daily basis at 99 per cent confidence level. The application of an outdoor thermal comfort index highlighted the existence of very strong heat stress zones over 14.67 per cent of the study area. The air temperature hotspots were verified with intra‐urban variation in carbon sequestration. This environmental parameter was used to strengthen the observed results since, carbon sequestration directly links urbanization with degradation of thermal environments. Further, five urban morphological parameters were analysed to conclude that building density and height were the most significant urban design factors leading to increased air temperature. Simultaneous local climate zone mapping depicted that heat islands were dominated by mid and high‐rise built‐up areas, of which 68.44 km2 of that area is suitable for vertical and roof gardening. Another 33.29 km of road stretch was delineated within low‐rise built‐up areas with scope for green landscaping to improve urban sustainability.

Loss-of-Life Analyses Based on Modified Arrhenius and Relative Aging Rate for Non-Thermally Upgraded Paper in Oil-Immersed Transformer

This study evaluates the Loss-of-Life (LOL) based on the modified relative aging rate of an Oil Natural Air Natural (ONAN) transformer with voltage and power ratings of 132/33 kV and 60 MVA. The study’s methodology included the determination of the Hotspot Temperature (HST) based on the differential equation in IEC 60076-7. The loading and ambient temperature profiles for HST determination are forecasted based on the Seasonal Autoregressive Integrated Moving Average (SARIMA). Next, a new relative aging rate was developed based on the Arrhenius equation, considering the pre-exponential factors governed by oxygen, moisture in paper, and acids at different content levels. The LOL was computed based on the new relative aging rate. The study’s main aim is to examine the impact of pre-exponential factors on the LOL based on modified Arrhenius and relative aging rate. The results indicate that the LOLs for different conditions increase as the oxygen, moisture, low molecular weight acid (LMA), and high molecular weight acid (HMA) increase. The LOLs are 46 days, 1,354 days, and 2,662 days in the presence of 12,000 ppm, 21,000 ppm, and 30,000 ppm of oxygen. In 1%, 3%, and 5% moisture, the LOLs are 477 days, 2,799 days, and 7,315 days. At 1% moisture, the LOL is 1,418 days for LMA, while for HMA, it is 122 days. The LMA has the highest impact on the LOL compared to other aging acceleration factors.

Analisis Umur Pakai Transformator Distribusi 800 Dan 1600 kVA Di PDAM Ngagel Surabaya

Distribution transformers have a very important role in the electric power system. The lifespan of transformers in electric power systems will decrease over time. The reduced service life of distribution transformers is caused by several factors, including loading, ambient temperature, transformer winding temperature and transformer oil temperature. The author uses quantitative and qualitative research types. This research was conducted to determine the remaining useful life of distribution transformers. The data used in this research are transformer template data and peak load data during the day and night. The results of data processing obtained state that the first transformer's estimated remaining life with a load > 80% is 18 years starting from 2023, the second transformer's estimated remaining life with a load > 80% is 16 years starting from 2023, for the third and fourth transformers it is not calculated because it has been used since 1982 or is around 41 years old. For the winding temperature on the first transformer LBP 84 ℃ and BP 89 ℃, on the second transformer the winding temperature LBP 81 ℃ and BP 96 ℃. Both transformers are still considered good because the hot spot temperature is below the maximum limit set by the IEEE in 1955, namely a temperature of 98 ℃.

Real-Time Early Warning Method of Distribution Transformer Load Considering Meteorological Factor Data

The traditional real-time load warning method for distribution transformers has problems such as low recall rate, low warning accuracy, and long warning time, which may lead to potential equipment failures or overload situations not being detected and dealt with in a timely manner, increasing the safety risk of transformer operation and potentially causing safety issues such as equipment damage, fire, or power outage. Therefore, a real-time early warning method of distribution transformer load considering meteorological factor data is designed. The meteorological factor data are collected by the light sensor, humidity sensor, temperature sensor and rainfall sensor, and the load data collection architecture is built by the load monitor, central master station and maintenance station to realize the load data collection of the distribution transformer. The K-nearest neighbor (KNN) method is used to process the missing values of the data, and the LOF algorithm is used to determine the local outliers and eliminate the outliers in the data set to achieve data cleaning. Considering the load loss, hot spot temperature and meteorological factors of the distribution transformer, an early warning model is built, and the cleaned data are input into the model to realize Real-time early warning of the distribution transformer load. The experimental results show that the recall rate of this method varies from 95% to 97%, the accuracy rate of early warning is always above 94%, and the maximum value of early warning time is 0.63s. Having good early warning ability.

Modeling the impact of high thermal conductivity paper on the performance and life of power transformers

Degradation of insulation paper is a key contributor to the failure of power transformers. Insulation degradation accelerates at elevated temperatures, which highlights the potential for better thermal management to prolong life. While several studies have analyzed the benefits of high thermal conductivity oil for reducing temperatures inside a transformer, this study is an initial assessment of the benefits of high thermal conductivity paper on transformer life. Blending particulates with cellulosic fibers offers a pathway for high thermal conductivity paper (with good dielectric properties), which can reduce internal temperatures. Presently, life extensions that can be achieved by the use of such thermally conducting papers were estimated, with the thermal conductivity of the paper being the key parameter under study. The analytical-numerical thermal model used in this study was validated against experimental measurements in a distribution transformer, adding confidence to the utility of the model. This model was then used to provide estimates of hot-spot temperature reduction resulting from the use of papers with higher thermal conductivity than baseline. Transformer life was predicted conventionally by tracking the degree of polymerization of paper over time, based on an Arrhenius model. Results indicate that increasing the thermal conductivity of paper from 0.2 W/mK (baseline) to 1 W/mK reduces the hot spot temperature by 10 °C. While degradation significantly depends on the moisture and oxygen content, the model shows that such a temperature reduction can increase life for all conditions, by as much as a factor of three.

Determination of Hotspot Temperature Margin for Rectangular Wire Windings Considering Insulation Thermal Degradation and Partial Discharge

Increasing current density is a common way to improve the power density of electrical machines (EMs) which also boosts the winding temperature. Higher winding temperature accelerates the thermal degradation of insulation and also increases the risk of partial discharge (PD). Commonly, the winding hotspot temperature constraint is decided based on an over-engineering approach (i.e., the winding hotspot temperature is 30°C below the wire thermal class) constraining the EM’s performance. In this paper, the margin of winding hotspot temperature is precisely determined focusing mainly on the insulation degradation issues through experimental investigation. The partial discharge inception voltage and partial discharge extinction voltage have been measured under different temperature conditions for samples with different thermal aging statuses. Rectangular wires which find application in automotive motors are selected as test samples. The results link the temperature with the PD risk and the thermal lifetime of the insulation, and the winding hotspot temperature margin is accordingly determined. An automotive case study is presented to prove the applicability of the investigation outcomes.

Calculation Method for the Transient Hot-Spot Temperature Rise of Oil-Immersed Bushing in High-Speed Railway

Traction oil-immersed bushing is the only channel for connecting the high-speed railway system with the external power grid, and its transient hot spot is one of the most important factors reflecting its operation status. Since the traction load of a high-speed railway has obvious impulse characteristics, the existing calculation method for bushing given in IEEE Std C57.19-100™-2012 is incompatible because it is designed for steady electrical loads. Thus, in this paper, the equivalent hot spot temperature rise of the bushing under varying traction loads is calculated by the traction parameters (i.e., operating time <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T_ot</i> , interval time <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T_it</i> , and per unit transient traction current <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I_tc</i> ). Then, the difference value of transient hot spot temperature rise is modified by analyzing the change of transient hot spot temperature rise under varying traction loads. Finally, a calculation method is proposed for the transient hot spot temperature rise of the oil-immersed bushing in high-speed railway under different traction loads. A case study of a 110 kV oil-immersed bushing shows that the proposed method is speedy and accurate.

Training-free performance of the wax-impregnated SuShi septum magnet

In the framework of the Future Circular Collider Study a new septum magnet concept, nicknamed ‘SuShi’ has been developed, and a prototype was built at Wigner Research Center for Physics, and tested at the FREIA facility of Uppsala University in April 2023. The concept uses a canted cosine theta (CCT)-like superconducting magnet and a passive superconducting shield to create a zero-field and high-field region within its aperture. SuShi is the first CCT magnet with both of its winding layers simultaneously impregnated with wax. This paper describes the first powering test of the empty magnet at 4.2 K, without the shield being inserted in its aperture. The performance of the magnet, including the observation of quench-back, estimation of hot-spot temperatures and the fraction of energy dissipated in the magnet are presented, and most interestingly the absence of any quench during the entire testing period is reported. Sushi reached its nominal +5% peak field of 3.64 T at 450 A, which corresponds to 80% of the calculated short sample limit along the load line, without training.

Research on Temperature Sensing Method for Three-Core Cable Intermediate Joint Considering Three-Phase Load Imbalance

Temperature is a key factor affecting the insulation performance and operation safety of cable joints. Accurate acquisition of hot spot temperatures of cable joints is a difficult issue in cable operation and maintenance. Three-core cables may have unbalanced three-phase loads in actual operation. This paper takes a 10 kV three-core cable joint as the research object; based on the temperature field numerical simulation method, it analyzes the diffusion path of the main heat flow inside the joint and establishes an inversion model that fits the hot spot temperature of the joint through the surface temperature of the cable body. At the same time, considering the special situation of the unbalanced three-phase load of a three-core cable, the joint hot spot temperature inversion model of a three-core cable under an unbalanced three-phase load is further established. This paper further uses the cable joint multi-step unbalanced load temperature rise test to verify the accuracy of the cable joint hot spot temperature inversion model. The maximum error of the transient hot spot temperature inversion does not exceed 4.5 °C, and the steady-state error is within 3 °C. A higher inversion accuracy was achieved. The research results of this article can provide a reference for real-time monitoring of the hot spot temperature of cable joints.

Exploration of Temperature Inversion in Intermediate Joints of 10 kV Three-Core Cable

In order to precisely ascertain the temperature at the hot spot within the intermediate joint of a three-core cable, this study focused on a 10 kV three-core cable joint as its primary subject. A three-dimensional finite element model of the cable joint was constructed, enabling the calculation of both the steady-state hot spot temperature field distribution and the transient temperature rise curve of the joint. Employing a one-dimensional transient thermal path model for the cable body, a radial inversion model for the cable core temperature was established. Through simulating the transient temperature field of the cable joint under varying currents, a fitting relationship was determined for the axial temperature points of the cable core. Subsequently, an inversion perception model was devised to calculate the hot spot temperature of the cable joint based on temperature measurements at specific points on the outer surface of the cable. Under both continuous and periodic loads, the inversion results revealed a consistent trend in the temperature at the joint crimping point with the finite element calculation outcomes, demonstrating a maximum error of within 3 degrees Celsius. This verification underscores the precision of the temperature combination inversion method when applied to three-core cable joints.