1491 results about "Thermal threshold" patented technology

The invention relates to a method for intelligently monitoring the temperature of important parts of a server, which comprises the following steps: acquiring specified data of the server, inputting the specified data into a dynamic threshold model for training, acquiring various items in real time, inputting the trained dynamic threshold model, and adjusting the temperature threshold of each important part in real time according to the load change and environment change of the server; when the real-time temperature of a certain part is greater than or equal to the corresponding temperature threshold value, correcting the temperature threshold value of the associated part in real time, and performing coupling analysis on the temperature data of different parts under the same time dimension and the temperature change curve of different time nodes; when the real-time temperature of a certain part is greater than or equal to the temperature threshold determined by the dynamic threshold model, an early warning signal is sent out; and generating a temperature control strategy based on the early warning signal and executing a corresponding action by an execution component. The server temperature condition is comprehensively mastered through a dynamic threshold value model, correlation analysis and coupling analysis, an optimized control strategy is generated according to the early warning level, and rapid and accurate regulation and control of the server temperature are achieved.

The invention relates to the technical field of cold-chain commodity transportation, in particular to a temperature monitoring and control method in a cold-chain commodity transportation process, which comprises the following steps: acquiring real-time temperature data, and generating a thermal response digital file of a cold-chain commodity according to the real-time temperature data and a cold-chain commodity category database; real-time positions and external air temperature data of the cold chain commodities are collected, and a temperature threshold value of the next time period is predicted according to the heat capacity characteristic parameters reflected by the thermal response digital archive; a three-dimensional temperature field distribution diagram is constructed based on the temperature threshold value of the next time period and the vibration data of the compartment where the cold-chain commodities are located; generating a control instruction according to the coordinates of the temperature anomaly region in the three-dimensional temperature field distribution diagram; after the control weight coefficient is calculated according to the control instruction and the preset energy consumption optimization objective function, the temperature control operation is executed according to the control weight coefficient and the control instruction, and balance temperature monitoring and control and energy consumption optimization are effectively achieved.

The invention relates to a battery thermal runaway intelligent grading early warning method, and relates to the technical field of battery thermal runaway early warning, and the method comprises the steps: loading a pre-control parameter and an environment temperature of a target cell, and constructing a cell dynamic portrait; obtaining a first battery cell temperature extreme value through a battery cell temperature extreme value prediction model; when the first battery cell temperature extreme value is smaller than the thermal runaway temperature threshold value, loading the abnormal compression time sequence information and the cycle index of the target battery cell, and constructing a battery cell static portrait; when the abnormal compression time sequence information is not empty, or / and the cycle index is greater than a cycle index threshold value, retrieving a sample set of the battery cells of the same model; counting the proportion of the thermal runaway samples in the same type of battery cell sample set, and setting the proportion as a target battery cell thermal runaway risk coefficient; and executing the grading early warning strategy. The problems that thermal runaway is difficult to accurately predict, early warning lags and potential safety hazards exist due to the fact that traditional battery thermal runaway management depends on a battery pack temperature sensor to collect temperature and early warning is executed only when the temperature reaches a preset value are solved.

A method of cooling a mammal with an implantable blood pump. The method includes measuring a temperature of an internal controller, the internal controller being in communication with the implantable blood pump. an alert is generated if the temperature of the internal controller exceeds a predetermined temperature threshold.

The invention relates to a cold chain transportation intelligent early warning and abnormity processing method based on temperature sensor data, and the method comprises the following steps: carrying out the temperature data collection of different regions in a cold chain transportation carriage, and obtaining the temperature collection data; performing temperature fluctuation analysis based on the temperature acquisition data to obtain a temperature fluctuation trend parameter; based on the temperature fluctuation trend parameters, temperature threshold value judgment is conducted on the cold chain transportation compartment, and a temperature judgment result is obtained; and when the temperature judgment result is that the temperature of the core cargo area in the cold-chain transportation carriage exceeds the preset threshold range, temperature early warning grade information is determined according to the temperature judgment result, and an abnormity processing instruction is generated based on the temperature early warning grade information, so that the problem that potential temperature risks cannot be predicted in advance is solved, and the safety of the cold-chain transportation carriage is improved. And the exception processing is often lagged.

The invention relates to the technical field of immersion liquid cooling data center cooling, and particularly provides a single-phase immersion liquid cooling server circulation cooling method and system, and the method comprises the steps: comparing the real-time temperature of a cooling liquid with a preset temperature threshold value, transmitting a first program instruction by a control system, and carrying out an immersion liquid cooling cabinet internal circulation mode; or a second program instruction is sent, and a heat exchange circulation mode is carried out; after the heat exchange circulation mode is started, a main liquid outlet pipeline is opened; the cooling liquid flows back to the liquid outlet of the immersed liquid cooling cabinet through the backflow branch pipeline, the real-time temperature of the cooling liquid and the preset temperature threshold value are continuously judged, and switching between the internal circulation mode and the heat exchange circulation mode of the immersed liquid cooling cabinet is achieved according to the comparison result. The system comprises an immersed liquid cooling cabinet, a branch pipeline valve, a main pipeline valve, a main liquid outlet pipeline, a pump, a heat exchanger and a branch pipeline. According to the invention, the topology reconstruction capability of the cooling liquid flow is realized, and local circulation and global circulation are dynamically switched according to the thermal load.

The invention discloses a fan control method and device, a product, a server and a medium, and relates to the field of computer hardware control. Under the condition that the temperature value of the server component is larger than or equal to the new current temperature threshold value, the target rotating speed value of the fan is output through the proportional-integral-differential control model, then the fan is controlled to rotate according to the target rotating speed value, and cooling of the server component through the fan is achieved; secondly, when the temperature threshold value is determined, the historical temperature values of the components under the multiple environment temperatures are considered, and the temperature threshold value is updated, that is, the fan is controlled by depending on the dynamic threshold value. The threshold value is adjusted in advance according to the environment temperature, so that frequent triggering of starting of the fan due to transient fluctuation of the environment temperature is avoided, and the stability of the server is ensured; and thirdly, based on an environment-load combined compensation mechanism, the rotating speed of the fan is dynamically adjusted to offset the influence of the environment temperature, the influence of the environment temperature and load factors on fan control is avoided as much as possible, and the fan control precision is improved.

The invention relates to the field of power equipment intelligent control, and discloses a power equipment maintenance management system and method based on artificial intelligence, and the method comprises the steps: carrying out the multi-source data collection through a sensor, eliminating the noise of the sensor, generating a three-dimensional thermal field model, displaying the temperature gradient between power equipment, and recognizing a high-temperature aggregation region; the heat conduction coefficient and the convection heat dissipation efficiency are corrected in real time by combining environmental parameters to build a model, historical data temperature changes are analyzed, the temperature abnormal condition is analyzed through a temperature threshold value according to the average temperature change and the highest temperature in a period, and the heat dissipation power is adjusted in time; the temperature of the power equipment is predicted based on the temperature change trend of the power equipment, the future heat dissipation efficiency is adjusted, the heat dissipation efficiency is improved to the minimum, the temperature of the power equipment after the heat dissipation efficiency is adjusted is predicted, the actual temperature and the adjusted predicted temperature are analyzed, the deviation is compared, and the formula for adjusting the heat dissipation power is dynamically compensated. And ensuring that the deviation degree and the deviation proportion meet preset standards.

The invention discloses a motorcycle emission fuel injector control method, system and equipment and a storage medium, and relates to the technical field of internal combustion engine control. According to the method, the real-time temperature of the fuel injector under the unheated condition is obtained, and the preheating temperature threshold value of the fuel injector is determined based on the difference value between the real-time temperature and the target temperature; acquiring a first temperature change rate of the fuel injector in each preset time period under the condition that the fuel injector is heated by a heat source of the motorcycle according to the preset heat supply amount; the preset heat supply amount is adjusted according to the first temperature change rates, and the target heat supply amount is obtained; a heat source of the motorcycle is controlled to heat a fuel injector according to the target heat supply amount until the real-time temperature reaches the preheating temperature threshold value, and emission parameters of a motorcycle engine are monitored; and the fuel injection amount of the fuel injector is determined based on the emission parameters and the emission parameter standard, and the fuel injector is controlled to inject according to the fuel injection amount. The motorcycle engine has the effect of improving the emission performance of the motorcycle engine.

The invention relates to the technical field of industrial computer heat dissipation, in particular to an industrial computer memory and storage collaborative heat dissipation system which is used for solving the problems that in the prior art, temperature distribution modeling and state evaluation cannot be achieved, thermal state categories cannot be divided by integrating a temperature threshold value and an operation state, and the equipment health judgment accuracy is reduced. According to the invention, a temperature control monitoring module constructs a thermal field model by using operation state and thermal behavior data, divides hardware units, establishes a heat conduction path, realizes temperature distribution modeling and state evaluation, calculates thermal power density through standardized parameters, and solves steady-state temperature by using a numerical method in combination with boundary conditions and a cooling model. Structured temperature information is output, a temperature threshold value and an operation state are integrated to divide thermal state categories, and the equipment health judgment accuracy is improved.

The invention relates to the technical field of new energy automobile and battery safety, and discloses a power battery thermal runaway risk early warning method, which comprises the following steps: synchronously acquiring battery internal resistance dynamic change, characteristic gas concentration and temperature gradient distribution through a multi-physics field coupling sensor network, and constructing an electrochemical-thermal-gas ternary early criterion; the internal resistance mutation rate is calculated through self-adaptive sliding window differential, the gas precipitation rate and the temperature space heterogeneity index are combined and input into a multi-branch fusion neural network containing a gating attention mechanism, the continuous thermal runaway risk probability is output, and corresponding early warning is triggered according to grading threshold values. The system comprises an internal resistance, gas and temperature monitoring module and a multi-modal fusion evaluation and grading early warning execution module. According to the method, the traditional early warning logic singly depending on a temperature threshold value is abandoned, a ternary early criterion system with the internal resistance abrupt change rate, the characteristic gas precipitation rate and the temperature space heterogeneity index as the core is constructed for the first time, and electrochemical and physical field anomalies caused by thermal runaway precursor events such as lithium dendrite piercing of a diaphragm and SEI membrane rupture can be effectively captured.

The invention relates to the technical field of wind driven generator control, in particular to a thermal management system and method for a wind driven generator, and the system comprises a data collection layer, a prediction module, a digital twin model, an intelligent control and diagnosis engine, and a heat dissipation execution mechanism. In the prior art, an open-loop or simple feedback control scheme based on a real-time temperature threshold value is mainly adopted, the problem of response lag exists, and all heat dissipation parts always work independently and lack cooperation, so that the energy efficiency is low; according to the invention, a closed-loop intelligent thermal management scheme based on a digital twin model is adopted, and real-time simulation and future state prediction are carried out by constructing virtual mapping of a generator thermal system, so that a control system can actively and cooperatively manage all heat dissipation resources according to a simulation result; the method has the core advantage of converting passive into active, and can intervene in advance before excessive accumulation of heat, so that collaborative optimal control of all parts of the system is realized, and the accuracy, timeliness and overall energy efficiency of heat management are remarkably improved.

The invention discloses a power transmission and distribution line iron accessory temperature abnormity control method and system, and relates to the technical field of power component control, and the method comprises the steps: obtaining an infrared thermal image of a target fitting; performing hot spot separation on the infrared thermal image according to a preset separation temperature threshold to obtain a hot spot region; performing boundary sharpness evaluation on the hot spot region to obtain a boundary sharpness evaluation result; performing shape regularity analysis on the hot spot area to obtain a shape regularity analysis result; and determining a heat source of the hot spot area according to the boundary sharpness evaluation result and the shape regularity analysis result. According to the method, the boundary sharpness and the shape regularity can be combined to analyze a heat source so as to realize temperature anomaly control of the hardware fitting, the temperature anomaly detection accuracy is improved, and the iron accessory hardware fitting is effectively controlled to maintain a normal state.

The invention discloses a cold-chain logistics temperature control supervision method and system based on GPS linkage, and relates to the related technical field of cold-chain logistics, and the method comprises the steps: installing a vehicle-mounted terminal on a cold-chain logistics transport vehicle, and collecting the vehicle position information and carriage temperature data in real time; encrypting and uploading to a monitoring processing center, and calling cold-chain logistics temperature control analysis dual channels of the target cold-chain goods; obtaining a temperature comparison result with a preset safe temperature threshold value, and matching and determining a target temperature control analysis channel; and performing temperature control analysis, determining a temperature control adjustment strategy parameter, and performing cold-chain logistics temperature control supervision. The technical problems that in the prior art, temperature control supervision lags behind, deep fusion analysis with the vehicle position and the transportation state is not carried out, specific reasons of temperature abnormity cannot be distinguished, and the regulation and control strategy is lack of accuracy and predictability are solved, and real-time, accurate and intelligent cold chain transportation temperature control abnormity recognition and supervision are achieved. And the reliability, the safety and the efficiency of cold-chain logistics are improved.

The invention discloses a method for measuring the focus heat effect and the heat damage of a Raman probe. The method comprises the following steps: S1, establishing a stable laser output system, and configuring a proper optical focusing system; s2, heating the standard sample to a target temperature according to a preset step length, keeping for several minutes at each target temperature, and performing spectral measurement on the standard sample by using a Raman spectrometer; s3, in the Raman spectrum measurement process, carrying out real-time temperature monitoring on the surface of the standard sample, and carrying out normalization processing on collected Raman spectrum data; s4, establishing a quantitative relation model between the relative intensity change characteristic # imgabs0 # of the Raman spectrum and the temperature T; and S5, predicting the temperature T of the standard sample under the current preset parameters according to the model, and adjusting the measurement parameters according to the prediction result, so that the predicted temperature T is lower than the temperature threshold value of the to-be-detected sample. According to the method, the thermal effect of the laser can be predicted before Raman measurement, proper measurement parameters are set in advance, and thermal damage to a measured sample is avoided.

The invention relates to the technical field of liquid cooling heat dissipation control. The invention provides a temperature self-adaptive control method, system and device for a liquid cooling cable of a high-power charging gun and a storage medium. The method comprises the following steps: acquiring a cable body structure, a charging condition and a cooling liquid state parameter, and constructing an initial data set; based on a data set fusion heat conduction mechanism, establishing a dynamic control model of the cable temperature, the working condition and the cooling liquid flow rate; collecting parameters in real time, inputting the parameters into the model, and calculating a target temperature and a cooling liquid flow velocity threshold; comparing the target temperature with a safe temperature threshold, if the target temperature exceeds the standard, adjusting the rotating speeds of the water pump and the fan, otherwise, maintaining the current state; actual temperature and flow velocity are monitored in real time, and model coefficients are corrected according to temperature difference. The problems that an existing liquid cooling control method for the high-power charging gun is lagged in response, high in computing resource requirement and insufficient in control precision and energy efficiency under complex working conditions are solved.

The invention discloses a load prediction method considering data enhancement in extreme weather, which relates to the technical field of power system load prediction and comprises the following steps: acquiring meteorological data and historical industry load data of a target area according to a fixed sampling interval; calculating the correlation between a temperature sequence and a load sequence in the multivariable feature matrix, and screening a temperature-sensitive target industry load set by combining the correlation strength and stability in an extreme scene; calculating daily extreme temperature of the temperature sequence by day, and judging and identifying different extreme weather days and corresponding similar day sets according to a temperature threshold value; performing sample expansion and elimination according to the similar day set and the representative test day, and establishing a basic training set and an enhanced training set; and constructing a reference model through double-stage training. Compared with a traditional method, all load data are simply used, redundant features are remarkably reduced, and model training efficiency and prediction accuracy are improved.

The invention relates to the technical field of transformer intelligent monitoring and heat dissipation control, in particular to a transformer system based on intelligent monitoring and self-adaptive heat dissipation and a transformer heat dissipation method, and the system comprises an intelligent monitoring module which is used for collecting physical quantity data in the operation process of a transformer in real time through a sensor; the data processing and analyzing unit is used for receiving the data transmitted by the intelligent monitoring module and establishing a transformer operation state model; the self-adaptive heat dissipation control module is used for receiving the operation state analysis result and dynamically adjusting operation parameters of the heat dissipation system based on a temperature threshold value and a load rate; and the fault early warning and diagnosis module is used for establishing an operation state evaluation model and a fault prediction model by adopting a machine learning algorithm, receiving an operation state analysis result and comparing the operation state analysis result with an early warning threshold value. Accurate monitoring, self-adaptive heat dissipation and fault early warning of the transformer are achieved, stable operation is guaranteed, and energy consumption is reduced.

The invention discloses an induction heating path optimization method suitable for a heterogeneous noise elimination structure, and particularly relates to the field of induction heating path optimization of the heterogeneous noise elimination structure, and the method comprises the steps: building a grid coordinate in a target region, collecting the heat conductivity coefficient, the specific heat capacity, the thermal resistance value and the induction coil gap value of each grid node in the grid coordinate, generating a thermal response model; and performing heat conduction calculation on the thermal response model and a preset heating power curve, calculating a temperature rise value of each grid node in a fixed preset heating time, marking the grid nodes of which the temperature rise values reach or exceed a safe temperature threshold and the adjacent grid nodes as heat concentration areas, and generating risk area data after gathering the heat concentration areas. A risk assessment and dynamic reordering mechanism based on local thermal characteristic difference is introduced in a heating path planning process, so that advanced identification and real-time avoidance of a heat concentration area are realized.

The invention relates to the technical field of wireless charging temperature control, in particular to a self-adaptive intelligent temperature control method and a refrigeration wireless charger. According to the method, the inherent heating tendency of the mobile equipment is quantified through the charging initial data, the heating index is obtained, the basic temperature threshold interval is obtained according to the heating index, and the charging environment data is introduced to intervene in the obtaining of the personalized temperature threshold in real time; the method solves the problem of unreasonable threshold setting caused by the difference of batteries of new and old equipment and the difference of heating characteristics of different models, then, by capturing charging process data of mobile equipment and combining threshold judgment, early warning and refrigeration triggering can be carried out in the early stage of abnormity, and the charging efficiency of the mobile equipment is improved. The emergency degree of the current refrigeration demand can be accurately described by analyzing the temperature control demand intensity value calculated by the charging process data, and the accurate temperature control adjustment parameters are dynamically generated in combination with the preset control parameter group of the refrigeration wireless charger, so that the charging and refrigeration assembly is directly controlled, and the temperature control response speed is favorably improved.

The invention discloses a thermal management control method for a hydraulic hybrid power system of a mining vehicle in order to solve the technical problem that multi-power-source coupling optimization and an energy control strategy are poor, and belongs to the technical field of underground vehicle thermal management. According to the method, data such as real-time temperature, pressure, methane concentration and hydraulic oil viscosity are collected through a sensor module; the reference temperature threshold value is dynamically adjusted according to the methane concentration to obtain the maximum allowable temperature, the opening degree of a flow valve of a cooling system is adjusted through a dynamic PID algorithm when the real-time temperature exceeds the limit, and PID parameters are adjusted in real time along with the viscosity of hydraulic oil; and after a data error is compensated by adopting a least square method, a specific enthalpy and a specific entropy of a key node are calculated by utilizing a ratio algorithm, a physical ratio is deduced, and an abnormal node is positioned. Through cooperative control of thermal management and hydraulic mixing, the energy efficiency and safety bottlenecks are overcome, the energy utilization efficiency is improved, and technical support is provided for low-carbon transportation of mines.

The invention discloses a heat dissipation control method and device of a liquid cooling charging pile and a medium, is applied to a liquid cooling control panel, and relates to the technical field of electric vehicle charging, and the method comprises the steps: collecting the original temperature data of a plurality of key nodes in a charging pile liquid cooling system in real time; the key node at least comprises a charging gun head and a cooling liquid inlet / outlet; comparing the original temperature data with a preset multi-stage temperature threshold value, and determining a current thermal state of the charging pile liquid cooling system according to a comparison result; according to the current thermal state, control parameters of a heat dissipation actuator in the charging pile liquid cooling system are generated through a pre-constructed temperature control engine; and generating a heat dissipation driving signal based on the control parameter, and sending the heat dissipation driving signal to a heat dissipation actuator so as to adjust the operation state of the heat dissipation actuator, so that the temperature of the charging pile liquid cooling system is maintained within the target temperature range. And according to different thermal state intelligent switching control strategies, it is ensured that the liquid cooling system can quickly respond and maintain the optimal thermal balance under any working condition.

The invention relates to a sintering furnace temperature prediction method and device based on an LSTM model and a medium. The method comprises the steps that sintering furnace multi-source sensor data are collected and preprocessed to generate time sequence data, binary features are generated through continuous stable temperature interval detection, and the binary features are fused with the time sequence data to form a feature set; the sensor combination is dynamically screened according to a real-time temperature threshold, and a feature set is converted into a sequence sample by adopting a sliding window. And carrying out standardization processing on the input features, and normalizing the target temperature value into a supervision label. And constructing an LSTM network model, and training by using the sequence sample and the supervision label. And finally, performing temperature prediction on real-time data through the trained model, and outputting a normalized prediction result. According to the method, a dynamic feature switching mechanism and an LSTM network are combined, high-precision real-time prediction and control of the sintering furnace temperature field are achieved through adaptive sensor optimization and time sequence feature fusion, and the temperature regulation response speed and prediction accuracy are effectively improved.

The invention relates to the field of cable aging detection, particularly discloses a household wire and cable insulation aging evaluation system and a detection method, and aims to solve the problem of insulation aging detection of a hidden cable in a wall threading pipe. The system comprises a detection head pipe penetrating module which enables a miniature detection head to adaptively adjust the advancing speed according to the curvature of a pipeline; the suspected aging identification module is used for acquiring surface temperature data of the cable in a load state through an infrared thermal imager, and identifying suspected aging points based on the temperature difference and a temperature threshold value; the aging degree evaluation module is used for synchronously acquiring an insulating layer image, gas data and partial discharge capacity, comparing the acquired insulating layer image, gas data and partial discharge capacity with a cable aging characteristic database and performing multi-dimensional fusion analysis on the cable insulation aging degree; and the aging point determination module determines a cable aging point according to the aging degree and sends the position. According to the method, the problems that the hidden cable is difficult to detect and the evaluation dimension is single are solved, the detection reliability and accuracy are improved, and the household electricity utilization safety is guaranteed.

The invention relates to the technical field of water tank temperature monitoring, in particular to a monitoring system for a temperature detector to detect the temperature of a water tank, which comprises an intelligent temperature control core management module, a heating effect self-adaptive optimization module and a temperature abnormity sound-light alarm module, setting a heating time interval A according to a specific heat capacity and power formula; the heating effect self-adaptive optimization module adjusts a heating time interval A to a heating time interval B through a time adjustment method, and outputs a control instruction and the heating time interval B to a heating fan; if the indoor temperature value B is larger than the upper limit of the temperature threshold value, the heating completion time is set as the starting time of the detection time threshold value, and in the northeast cold region, the temperature between the fire water tanks is influenced by various factors such as the outside air temperature and the operation state of a heating fan, and the detection time threshold value is adjusted; and the temperature inspection intelligent scheduling unit closely fits the actual change condition of the indoor temperature.

The invention discloses an intelligent heat dissipation method and system for case heat dissipation, and belongs to the technical field of server case heat dissipation, and the intelligent heat dissipation method comprises the following steps: S1, arranging a heat detection unit and a diversion unit in a case; s2, acquiring real-time temperature information in the case, comparing the real-time temperature information with a temperature threshold value to judge whether a hot spot appears or not, and if the hot spot appears, turning to step S3; s3, confirming a hot spot coordinate, reconstructing a cold air conveying path, and calculating to obtain deflection angle information of the flow guide unit; and S4, the flow guide unit conducts corresponding deflection, cold air conveying path reconstruction is completed, and meanwhile the system capable of achieving the method is provided. According to the intelligent heat dissipation method and system for heat dissipation of the case, the cold air conveying path in the case is reconstructed, so that targeted efficient heat dissipation is carried out on the hot spot position in the case, energy consumption waste is avoided, and the heat dissipation efficiency is improved.

Aircraft capable of hovering comprising a fuselage at least one rotor that is rotatable with respect to the fuselage, electrical drive means adapted to rotate the rotor and electrically powered by a battery, and a cooling system of the battery. Said cooling system comprises, in turn, a first opening for the air to enter, second openings for the air to escape and a passage which places the first opening in fluidic communication with the second openings and within which the battery is placed. The cooling system further comprises a fan adapted to increase the kinetic energy of the air contained in the passage and which is operated when the forward speed of the aircraft with respect to the ground is lower than a speed threshold value and / or when the temperature of the battery exceeds a temperature threshold value.

The brake assembly includes a housing, a rotor disc. The rotor disc includes at least one internal cavity. The at least one internal cavity includes a pawl and a thermal fuse. In use, the thermal fuse is configured to maintain the position of the pawl in the at least one internal cavity when a temperature is below a predetermined threshold, and wherein the thermal fuse is configured to melt when a predetermined threshold of temperature is reached during braking to release the pawl out of the at least one internal cavity towards the housing. The housing includes at least one recess configured to receive the pawl.

The invention relates to the technical field of vehicle lamps, in particular to a real-time intelligent temperature control system for a high-power bullet train headlamp. According to the high-power bullet train headlamp real-time intelligent temperature control system, the temperature detection module monitors the temperature of the double lamp sets in real time and feeds back the temperature to the decision module. Based on a control strategy generated by real-time data, the main lamp group can be dynamically switched according to a temperature threshold value, for example, the first lamp group is switched to the second lamp group when the temperature is high, and the first lamp group and the second lamp group alternately work to balance heat dissipation; meanwhile, the decision-making module adopts a progressive brightness control strategy, and brightness sudden change during threshold triggering in a traditional scheme is avoided through staged linear adjustment of the brightness of the lamp set.

The invention provides a battery cooling control method, a controller, a vehicle and a medium, and relates to the technical field of new energy. The method comprises the steps that the real-time battery temperature of a power battery in the vehicle is obtained; under the condition that the real-time battery temperature is smaller than the safety temperature upper limit of the power battery, the real-time heat production power of the power battery is determined; according to the safety temperature upper limit and the real-time heat production power of the power battery, a dynamic temperature threshold value of the power battery is determined, and the dynamic temperature threshold value is smaller than the safety temperature upper limit; and performing temperature cooling control on the power battery according to the real-time battery temperature and the dynamic temperature threshold. According to the invention, the accuracy and safety of battery cooling control can be improved.