Real-time Temperature Distribution Research Articles

Towards Understanding and Control of Thermal Processes in Lithium-Ion Batteries

Despite lithium-ion batteries (LIBs) being state-of-the-art commercial rechargeable batteries, there are still significant challenges. For example, heat generation during cycling can lead to performance degradation and safety issues1-2. During the process of charging and discharging, the heat that is generated from the chemical reactions taking placing is ideally distributed uniformly in space, to dissipate out the cell easily. However, in practice, heat generation tends to be heterogeneous throughout the battery, leading to localized overheating3. This phenomenon can result in e.g. decomposition of the solid-state electrolyte interphase (SEI) layer, triggering electrode reactions with the electrolyte and degradation of the electrolyte (producing combustible gases) and even melting of the separator4. Hence, comprehending the origins of temperature generation and its heterogeneity is crucial.To address this challenge, operando X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) are applied to monitor the structural changes in the electrode materials during charge and discharge, while simultaneous temperature measurements are conducted using a thermal camera, as such obtaining spatial resolved structure/temperature/performance relationships. We have focused on state-of-the-art nickel rich NMC (Nickel Manganese Cobalt Oxide) versus graphite batteries and by comparing the structural changes of the electrode materials during cycling in ‘hot’ versus ‘cool’ areas of the electrode and battery, we were able to establish a structure-temperature relationships, on top of the electrochemical structure-performance relationships and as such unravel “heat-generation” process and reactions. The real-time temperature distribution was compared to the computational models using COMSOL, and insights in thermal processes and their possible control measures could be obtained.References Lain, M. & Kendrick, E. Understanding the limitations of lithium-ion batteries at high rates. Journal of Power Sources. Volume 493, 229690 (2021).Ma, S., et al. Temperature effect and thermal impact in lithium-ion batteries: A review. Progress in Natural Science: Materials International. Volume 28, Issue 6, Pages 653-666 (2018).Rafael, M., et al. Operando Radiography and Multimodal Analysis of Lithium–Sulfur Pouch Cells—Electrolyte Dependent Morphology Evolution at the Cathode. Adv. Energy Mater. 2103432 (2022).Joris, J., et al. A comprehensive review of future thermal management systems for battery electrified vehicles. Journal of Energy Storage 31, 101551(2020).

Prediction of icicles on lining surface in high-speed railway tunnel in severe cold region based on the characteristics of daily temperature fluctuation

：Icicles in high-speed railway tunnels in cold regions pose a serious threat to operational safety. Tunnels with long lengths and large sizes require manual inspection, generating considerable work and expense for operation management. To reduce the workload of icicle inspection and guide manual deicing, a growth and development model of tunnel icicles was developed based on a tunnel icicle simulation system, and a tunnel lining icicle prediction and warning system was established, that provides guidance for deicing by predicting the range and development degree of tunnel icicles. The icicle simulation test shows that there is an obvious division of icing and non-icing area in the tunnel, and the boundary of the division is −5 °C. There is an optimum temperature range for the growth and development of icicle in tunnels. Under daily temperature fluctuations, the icicles grow back after being removed. A model for degree of icicle development was established. The degree of icicle development is affected by leakage flow, daily fluctuation amplitude of temperature, and daily average temperature. The smaller the daily temperature fluctuation and the closer the daily average temperature to the optimum temperature for icicle growth, the better the development of icicle. Based on the icicle development model, a prediction and warning method for icicles in tunnel was developed. Based on the network of instruments measuring and reporting temperature, the real-time temperature distribution of the tunnel was obtained, combined with the leakage distribution and volume in the tunnel, the icicles section and the icicles severity of the tunnel were obtained by analyzing the icicle growth model embedded in the system, providing guidance for the inspection of icicles in the tunnel. A comparison shows that the icicle prediction and warning system can reduce the walking inspection workloads by half.

Optimization of heating temperature uniformity for multi-microwave source group based on dynamic switching topology

Aiming at the mutual coupling of multiple physical fields in the microwave heating process and the generation of thermal runaway phenomenon, in this paper, a cooperative variable power heating strategy with multi-microwave source clusters under dynamic switching topology is proposed in order to improve the temperature uniformity. Firstly, an algebraic graph theory is used to establish a communication topology for complete information transfer, which is used to construct a distributed structure among multiple microwave source intelligences. Secondly, the dynamic topology switching algorithm under event triggering is introduced, and the real-time temperature distribution of the heated materials is considered to achieve the dynamic switching of the topology connection mode between microwave source clusters in order to synchronously coordinate the power consistency output between different clusters. On this basis, a numerical calculation model is constructed to solve the mixed optimization of integer and continuum variables by means of the finite element method. Finally, the effectiveness of the heating strategy to improve temperature uniformity is verified by microwave heating SiC media simulation calculation. The numerical calculation results show that the temperature uniformity indexes are improved by 34.1%–50.4% and 28.1%–55.2% in each horizontal and vertical section for single materials, and by 59.1%–59.7% and 46.5%–63.4% in each horizontal and vertical section for multi-materials, respectively, in comparison with the general heating method. This strategy effectively avoids the residence of hot and cold spots in the material, which in turn optimizes the temperature distribution.

Multi-point thermometry tool and in-situ measurement of temperature fields

In-situ real-time measurement of instantaneous milling temperature distribution is a key issue to realize efficient machining. For the foregoing reasons, the milling model of Inconel 718 was established, and the cloud diagram of tool temperature distribution during milling was obtained. A multi-point temperature measurement tool for milling temperature with an integrated thin-film temperature sensor was designed. The real-time temperature distribution of the tool during milling was obtained from 27 sets of milling tests. The impact of each milling parameter on the milling temperature was analyzed by ANOVA.

Research on Real-Time Calculation Method of Transformer Temperature Field Based on Reduced Order Model and Sparse Measurement

The lifespan of transformers is closely related to their operating temperature. Among the existing temperature acquisition methods, the measurement method cannot obtain the complete temperature field temperature, while the numerical calculation method presents the challenge of significant computational expenses. This study theoretically derived how to determine the real-time temperature distribution of transformer windings based on sparse measurement data and reduced order models and solved sensor layout issues, including the number and placement position of sensors. In this study, the maximum calculation error of the temperature distribution is 1.8 K, and the calculation time is 0.38 seconds. The research findings suggest that multiple modes can contribute to the temperature distribution of a transformer. Under a constant load condition, the calculation of transformer temperature can be achieved by utilizing a temperature sensor positioned at the hot spot in conjunction with the first mode.

Multi-source microwave heating temperature uniformity study based on adaptive dynamic programming

Abstract In view of the multi-physical field coupling and time-varying characteristics of the microwave heating medium process, how to dynamically plan the state characteristics of multiple microwave sources and optimize the material temperature uniformity becomes the focus of this article. To this end, first, algebraic graph theory is used to construct the multiple microwave sources as a multi-agent system, and a perfect communication topology is established to ensure the transfer and sharing of information. Second, according to the real-time temperature distribution of the material, an event-triggered adaptive dynamic planning algorithm is used to co-operate with the power input of the multiple microwave sources to ensure that no new hot spots are generated during the optimization of the temperature distribution using the self-organizing properties of the medium. Finally, a numerical calculation model for optimizing a mixture of integer and continuous variables is solved using the finite-element method. The experimental and numerical results show that this article improves the temperature uniformity by 32.4–73.5% and the heating efficiency by 14.3–39.4% compared to the generic heating model, and the feasibility of the method is verified by the different shapes of the heated material.

Fast multilayer temperature distribution estimation for lithium-ion battery pack

Fast and accurate temperature estimation is crucial for ensuring battery packs' safety and operation performance. However, the full-scale online temperature estimation is still challenging. In this work, a novel reduced-order multi-physics model for a lithium-ion battery pack is proposed for real-time temperature distribution estimation, containing the distributed equivalent circuit model, the three-heat-source thermal model, and the flow resistance network model. The proposed model is conducted on a direct contact liquid-cooled battery pack composed of three modules connected in series. An online parameterization methodology with a closed loop observer is designed, and the key parameters can be automatically identified and corrected. The validation results suggest that the multilayer temperature distribution of cell, module, and pack levels can be commendably described under both steady and transient conditions, where the maximum error can be controlled within 2.8 °C. Besides, the temperature variation of the coolant can be estimated during the operation. The proposed model shows excellent potential in onboard temperature estimation with tens of milliseconds for each temperature update.

Real-time temperature distribution reconstruction via linear parameter-varying state-space model and Kalman filter in rack-based cooling data centers

Rapidly growing data centers (DCs) are facing challenges with energy consumption increase and thermal environmental security. Thus, this paper proposed a novel real-time temperature distribution prediction and reconstruction model for rack-based cooling DCs, in order to facilitate efficient energy consumption and thermal environment management. The parameter identification method coupling with inherent physical relationships was employed to obtain the linear parameter-varying state-space model, rapidly and approximately predicting the nonlinear thermal dynamic processes within rack-based cooling DC. Then, Kalman filter was adopted to reconstruct the temperature distribution in real-time based upon the developed linear parameter-varying state-space temperature prediction model and measurement information. This study comprehensively analyzed the temperature estimation performance of the proposed model under various model input biases, different sensor numbers and layouts. The results show that the input biases have significant impacts on the accuracy of the temperature prediction model, e.g., ±5% bias in IT workload resulting in an increase of 0.6 times in the mean absolute error (MAE) of the temperature prediction. The proposed temperature reconstruction model reveals excellent performance: compared to the original temperature prediction model, the MAE was decreased by about 5%, 10%, and 13% for reconstruction scenarios using one, two, and three sensors, respectively.

The impact of permeability barriers on steam-solvent coinjection – A mechanistic study using a physical model

Coinjection of steam and condensate has been studied for improving the energy efficiency of steam-assisted gravity drainage (SAGD) as solvent-assisted SAGD or SA-SAGD. However, it is not well understood how tortuous hydraulic paths under heterogeneous permeability can influence the compositional and thermal flow characteristics in SA-SAGD. We addressed this question by performing an experiment of the coinjection of steam and condensate for bitumen recovery. This paper discusses the experimental results and gives our mechanistic analysis of how the tortuous hydraulic paths affected the thermal and compositional flow and the properties of the produced bitumen in the experiment.The physical model was a cylindrical pressure vessel with a diameter of 0.425 m and a length of 1.2 m, which was filled with unconsolidated sands. Two shale plates were horizontally installed above the well pair at different elevations so that they could represent permeability barriers to cause tortuous flow paths during the SA-SAGD experiment. The porosity and permeability of the sandpack was 0.34 and 5.6 D, respectively. Initially, the oil and water saturations were 95% and 5%, respectively.After preheating for 1 day, a mixture of 98.2 mol% steam and 2.8 mol% condensate was injected at 3500 kPa for 4 days (35 cm3/min of steam, cold water equivalent). The injection and production histories along with the real-time temperature distribution were recorded during the experiment. Produced oil samples were frequently taken and analyzed for density and asphaltene content. After the experiment, the sandpack was excavated and sampled from different locations to analyze the saturation and asphaltene content of the remaining oil. The experimental results in this paper were compared with the previous SAGD and SA-SAGD experiments that used the same experimental set up with a homogeneous sandpack.Results showed that, in comparison to the homogeneous SAGD case, SA-SAGD was able to lower the cumulative steam-oil ratio (SOR) by a factor of two to three even in the presence of shale plates. Analysis of the temperature profiles indicated that the steam chamber vertically expanded from the lower part to the upper part through tortuous paths at lower temperatures. An emerging steam chamber above the shale plates occurred by convective heat from the injection well through lower-temperature flow paths between shale plates, involving light to intermediate solvent components that enabled the steam chamber to expand away from the injection well. This highlights the important role of volatile solvent components in the growth of a steam chamber in SA-SAGD under heterogeneity. The produced bitumen density in this research was closer to the original bitumen than in the homogeneous SA-SAGD case because the bitumen dilution and the solvent retention increased by the tortuous flow regime resulted in efficient drainage of oil at lower temperature.

Real-Time Temperature Distribution Monitoring in Chinese Solar Greenhouse Using Virtual LAN

The internal air temperature of Chinese solar greenhouse (CSG) has the problem of uneven spatial and temporal distribution. To determine temperature distribution at different locations, we designed a greenhouse temperature real-time monitoring system based on virtual local area network (VLAN) and estimate, including interpolation estimation module, data acquisition, and transmission module. The temperature data were obtained from 24 sensors, and the Ordinary Kriging algorithm estimated the temperature distribution of the whole plane according to the data. The results showed that the real-time temperature distribution monitoring method established was fast and robust. In addition, data validity rate for VLAN technology deployed for data transmission was 2.64% higher than that of cellular network technology. The following results are obtained by interpolation estimation of temperature data using gaussian model. The average relative error (ARE) of estimate, mean absolute error (MAE), root mean square error (RMSE), and determination coefficient (R2) were −0.12 °C, 0.42 °C, 0.56 °C, and 0.9964, respectively. After simple optimization of the number of sensors, the following conclusions are drawn. When the number of sensors were decreased to 12~16, MAE, RMSE, and R2 were 0.40~0.60 °C, 0.60~0.80 °C, and >0.99, respectively. Furthermore, temperature distribution in the greenhouse varied in the east–west and north–south directions and had strong regularity. The calculation speed of estimate interpolation algorithm was 50~150 ms, and greenhouse Temperature Distribution Real-time Monitoring System (TDRMS) realized simultaneous acquisition, processing, and fast estimate.

Temperature distribution prediction in control cooling process with recurrent neural network for variable-velocity hot rolling strips

Control cooling is an essential method for microstructure and mechanical property control in hot rolling strip making. Therefore, it is vital to realize high-precision temperature distribution prediction and control in cooling process to ensure the industrial production. In this paper, a traditional mechanism model based on finite-difference method combined with online cycle velocity calculation strategy was introduced as one of the baseline methods estimating temperature distribution. However, considering calculation time, variable-velocity rolling makes it difficult to rapidly realize temperature and modifying water distribution of all segments in cooling zone. Herein, a temperature distribution prediction method based on recurrent neural network was proposed, by fully considering the variable-velocity rolling dynamic characteristics. And the temperature distribution prediction performance of the model with different recurrent cell and time steps was evaluated. The results indicated that the proposed model could realize temperature distribution prediction, and the model based on bi-LSTM and 48 timesteps has the highest determination coefficient value of 0.976, the lowest root mean square error of 8.03, and a mean absolute error of 5.7. Furthermore, compared with baseline model, the proposed model retained lower computational cost, making it applicable in industrial application by providing real-time temperature distribution prediction.

Study on thermal runaway warning method of lithium-ion battery

The battery pack design is limited by manufacturing cost and space energy, so it is impossible to set a temperature sensor on each battery and accurately determine the whole battery pack's temperature distribution by BMS (Battery Management System). However, the temperature is an important parameter to judge the security features of the battery. The finite element model could be dedimensionalized by a lumped parameter heat transfer model to meet the computational capacity of BMS, and the real-time temperature distribution within the battery module could be calculated and the thermal runaway location could be predicted. A temperature distribution back-calculated model for the battery module based on three measurement points was established. The calculation result showed that if only the temperature term was input, the temperature of the node interval without the heat source term was remarkably accurate. However, the temperature distribution results in the node interval with the heat source term meeting a vast error. After taking the temperature change rate into account, the difference between the calculated result and the actual temperature distribution is slight. It realizes an accurate calculation of the temperature distribution.

Evaluation of circulating temperature in wellbores using drilling microchips: Modeling and case studies

Using cost-effective drilling microchips to collect real-time temperature distribution while drilling is advantageous to accurately predict the variation of drilling fluid density and rheological parameters in wellbore. This study introduces a methodology for analysis of measured temperature of drilling microchips. Multiple sets of drilling microchips were deployed into two wells to measure the distribution of circulating temperature in tubular and annular space. An iterative algorithm is developed to calibrate the time-scale of drilling microchips to depth-scale considering variable pump rates, transit times and slippage of drilling microchips. A transient thermal model is modified to simulate the variation of wellbore temperature during circulation of tracers. It is shown that the velocity of tracers in each interval depends on the flow regime and rheological properties of drilling fluid. Comparing the predicted and actual transit times of tracers, it is realized that the maximum fluid velocity in each interval is a better choice to represent the velocity of tracers. It is shown that predictions of the transient model strongly depend on temperature distribution of the wellbore prior to deployment of tracers. This study provides new insights about the temperature distribution in wellbore while drilling and elaborates on the necessity to address the transient processes particularly during startups in wells with critical downhole conditions.

Effect of process parameters on temperature and force distribution during friction stir welding of armor-marine grade aluminum alloy

This research investigates the effect of process parameters on real-time temperature and forces distribution during friction stir welding of AA7039. Experiments are conducted at different rotational speed, welding speed, and tilt angle conditions. For the experimentation, a low-cost real-time force-measuring fixture is indigenously developed in-house. However, eight K-type L-shaped thermocouples are used to examine the real-time temperature distribution. The forces in the z-direction are of a higher magnitude than the x-direction. The maximum force in the z-direction of 3.25 kN is witnessed for 2° tilt angle and a minimum of 2.1 kN for 26 mm/min of welding speed. The maximum force in the x-direction of 0.97 kN is obtained at 2° tilt angle and a minimum of 0.27 kN is obtained at 1.3° tilt angle. The maximum temperature of 390 °C is observed at 1812 r/min, whereas a minimum of 283 °C is observed at 43 mm/min of welding speed. The variations in temperature and force distribution during friction stir welding are also evaluated by utilizing two phenomenological models.

Understanding time-temperature characteristics in microwave cladding

Microwave cladding is an emerging surface modification technique. Temperature control is the key issue in any surface modification technique. In microwave cladding, non-contact temperature measurement methods are widely used; however, these methods report only the surface temperature of the susceptor. In the present study, a modified B-type thermocouple was used to measure the real time-temperature distribution while developing Ni-based clad. Formation of clad has been discussed with respect of time-temperature distribution. Effect of microwave power on heating profile was also investigated.

Characteristics of the transient thermal load and deformation of the evacuated receiver in solar parabolic trough collector

As a core element in solar parabolic trough collector, the evaluated receiver often runs under severe thermal conditions. Worse still, the transient thermal load is more likely to cause structural deformation and damage. This work develops an efficient transient multi-level multi-dimensional (M2) analysis method to address photo-thermal-elastic problems, thereby estimating transient thermal load and deformation for the receiver: (i) one-dimensional (1-D) thermo-hydraulic model is adopted to determine the transient thermo-hydraulic state, (ii) 3-D finite volume method (FVM) model for the receiver tube is established to obtain the real-time temperature distribution, (iii) 3-D finite element method (FEM) model is employed to make thermoelastic analysis. Based on this M2 method, the typical transient cases are conducted in cold-start, disturbed-operation and regulated-process. Three indicators (average temperature of the wall (ATW), radial temperature difference (RTD), circumferential temperature difference (CTD)) are defined for overall analysis of the receiver thermal load. It is found that in the transient process, receivers face response delay and endure significant thermal load fluctuation. The response time for a single HCE (heat collecting element) under lower mass flow rate (1.5 kg s−1) could sustain 280 s. During the cold-start stage (DNI=200 W m−2 to 800 W m−2), the maximum value of CTD in receiver is as high as 11.67°C, corresponding to a maximum deflection of 1.05 cm. When the mass flow rate decreases sharply by 80%, the CTD reaches 33.04°C, causing a 2.06-cm deflection. It should be pointed out that in the cold-start stage and the lower mass flow rate operation for solar parabolic trough collector, alleviating the transient thermal load and deformation is of importance for safely and efficiently running evaluated receiver.

Anti-freezing prediction model for different flow patterns of air-cooled heat exchanger

Water heat load may get lower than the huge cooling capacity of air for air-cooled heat exchanger in winter, resulting in the freezing risk of finned tube bundles, so the water temperature distribution inside the tube under various working conditions stands the premise issue for the security and energy efficiency of dry cooling system. Based on the energy balance and heat transfer analyses, the anti-freezing prediction model of air-cooled heat exchanger is developed and experimentally validated at different low ambient temperatures with the maximum deviation of 16%. Taking a six-row plate finned tube heat exchanger as the research object, the water temperature distribution in any tube and the critical anti-freezing parameters are obtained with different air/water flow patterns at various ambient temperatures, air face velocities, inlet water temperatures, and water flow rates. The results show that the finned tube bundle with slotted fins is superior to the flat fins in heat transfer performance, but faces more serious freezing risks in cold winter. In the baseline case, the average outlet water temperature of the slotted finned tube bundle decreases by 3.9 °C compared to the flat finned tube bundle. For the air/water cross-counter flow pattern, the critical freezing position is fixed and appears at the water exit of upwind row. While for the air/water cross-cocurrent flow, the minimum water temperature varies with operating conditions, but it always happens at the row 1 or row 4. The anti-freezing of air-cooled heat exchanger can be realized by reasonably matching the air/water heat capacity as well as transforming the air/water flow patterns. The proposed anti-freezing prediction model is of potential benefit to the real-time temperature distribution forecast, freezing analyses, and control strategies for air-cooled heat exchanger in winter.

Optimal Sensor Placement Methods in Active High Power Density Electronic Systems With Experimental Validation

Abstract Increasing the efficiency and density of power electronic systems (PESs) is an important objective for many high-impact applications, such as electric vehicle charging and aircraft electrification. Due to compactness and high heat dissipation, careful thermal monitoring of such PESs is required. Strategic placement of temperature sensors can improve the accuracy of real-time temperature distribution estimates. Enhanced temperature estimation supports increased power throughput and density because PESs can be operated in a less conservative manner while still preventing thermal failure. This article presents new methods for temperature sensor placement for 2- and 3-dimensional PESs that (1) improve computational efficiency (by orders of magnitude in at least one case), (2) support the use of more accurate evaluation metrics, and (3) are scalable to high-dimension sensor placement problems. These methods are tested via sensor placement studies based on a single-phase flying capacitor multi-level (FCML) prototype inverter. Information-based metrics are derived from a resistance-capacitance (RC) lumped parameter thermal model. Other more general metrics and system models are possible through the application of a new continuous relaxation strategy introduced here for placement representation. A new linear programming (LP) formulation is presented that is compatible with a particular type of information-based metric. This LP strategy is demonstrated to support an efficient solution of finely discretized large-scale placement problems. The optimal sensor locations obtained from these methods were tested via physical experiments. The new methods and results presented here may aid the development of thermally aware PESs with significantly enhanced capabilities.

Sensitivity Analysis of Temperature Distribution along Horizontal Wells in Gas Reservoir

The application of distributed temperature sensors(DTS) to monitor producing zones ofhorizontal well through a real-time measurement of a temperature profile is becoming increasinglypopular. The information from DTS can potentially be transformed to obtain the permeability alongto the wellbore and well completion method and so on. The relationship between these parametersand the real-time temperature distribution along the wellbore is very important. Based onmass-,momentum-,and energy-balance equations, this paper established a model to predict thetemperature along the horizontal wellbore. The models presented in this paper account for heatconvective, fluid expansion, heat conduction, and viscous dissipative heating. Wellbore temperaturecurves are plotted by computer iterative calculation. In addition, this paper revealed the relationshipbetween wellbore temperature distribution and different characteristics, such as permeability alongto the wellbore and well completion method. The analysis results show that permeability differenceand different well completion methods may lead to different downhole temperature distribution atthe same time step, different production rate, different wellbore temperature as well as the change offriction factor in the wellbore. From the temperature distribution and temperature derivative curvesin different cases, we could easily derive the permeability distribution along wellbore and thelocation of the perforated intervals and the fractures.

High spatial resolution temperature field measurements by apodized short fiber Bragg grating sensors

To realize the high spatial resolution measurement of the temperature field, a temperature sensor array composed of eight apodized short fiber Bragg gratings with grating length of 1 mm and spatial spacing of 2 mm are fabricated. To suppress the side lobes, apodization methods by single-slit diffraction are designed. The sensor array is proposed to measure the real-time temperature distribution. The experimental results show that the temperature-sensing array can accurately measure the temperature field distribution with high spatial resolution and rapid response.