High-current connector temperature control method based on temperature rise management and high-current connector thereof

Abstract

The invention discloses a high-current connector temperature control method based on temperature rise management and a high-current connector thereof, and relates to the technical field of high-current connector temperature control, and the method specifically comprises the following steps: collecting thermal state information of the high-current connector in an operation process under the condition that a heat conduction path is limited; a structure heat distribution model used for representing the conduction process of heat of the contact area to the metal shell is established by combining the internal structure configuration of the large-current connector; based on the established structure heat distribution model and the collected heat state information, the heat information collection deviation degree under the condition that the heat conduction path is limited is evaluated; and according to the evaluation result, whether temperature control processing should be executed is judged, and corresponding temperature control processing measures are executed according to the judgment result. The problem of thermal information acquisition deviation caused by a limited heat conduction path is solved, and accurate sensing and dynamic temperature control response to the thermal state of the large-current connector are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of high-current connector temperature control, and in particular to a high-current connector temperature control method based on temperature rise management and a high-current connector thereof. Background Art

[0002] Temperature control for high-current connectors based on temperature rise management refers to the process of dynamically evaluating the connector's temperature rise during operation by monitoring its temperature change trends in real time, combining parameters such as current load, contact resistance, and ambient temperature. Active temperature control strategies are then implemented to ensure the connector operates within a safe and stable temperature range. Because high-current connectors are susceptible to significant temperature rises at their contact points due to resistive heating during continuous high-load operation, if the temperature cannot be effectively and timely controlled, it can lead to decreased conductivity, material aging, and even serious faults such as contact erosion and melting, thus affecting the stability and safety of the entire electrical system. Therefore, temperature control based on temperature rise management not only reflects the connector's thermal risk status in real time, but also enables intelligent adjustment and protection of the connector's operating status by linking cooling equipment, adjusting current-carrying strategies, or issuing early warning signals. This significantly improves the connector's reliability, extends its service life, and ensures the continued safe operation of power or industrial systems.

[0003] Existing high-current connector temperature control technology based on temperature rise management usually arranges high-precision temperature sensors at key parts of the connector to collect its temperature data under different working conditions in real time, and combines the current information obtained by the current sensor to dynamically predict and judge the temperature rise trend of the connector using a preset temperature rise model or algorithm; when the temperature rise reaches the set threshold or shows a rapid upward trend, the system will automatically trigger the temperature control mechanism, including starting forced air cooling or liquid cooling devices, reducing system current, switching backup lines, adjusting the connector contact structure or sending early warning signals, etc., to reduce the local temperature of the connector and prevent problems such as poor contact, material heat loss, and shortened life caused by overheating; the entire temperature control process generally includes five core links: temperature acquisition, data processing and analysis, temperature rise prediction and judgment, control decision execution, and feedback optimization. Through closed-loop control, real-time adjustment and safety assurance of the connector's working thermal state are achieved, thereby improving the intelligent management level and operational reliability of the entire electrical system while ensuring the stability of current transmission.

[0004] The existing technology has the following deficiencies: When high-current connectors continuously carry high currents, heat accumulates first in their internal contact areas. Because connectors are typically enclosed in a metal housing, the housing's structure restricts the thermal conductivity path between the contact area and the housing. This leads to heat transfer delays and energy attenuation as heat is transferred from the contact area to the exterior of the housing. This can cause significant deviations in the temperature rise data collected by the temperature acquisition device located outside the housing. Due to this deviation, even when the contact area is overheated, the recorded external temperature value may still be within the normal range, leading to a misinterpretation of thermal risks during the temperature control process. Existing high-current connector temperature control technologies based on temperature rise management cannot accurately determine whether temperature control should be initiated based on the degree of thermal information collection deviation in this situation with a restricted thermal conductivity path. Instead, they rely on surface temperature values ​​as the basis for decision-making, resulting in delayed or even complete failure of temperature control. This in turn leads to continued heat accumulation in the contact area, localized ablation, and increased contact resistance, ultimately leading to serious consequences such as connector functional degradation, breakdown failure, or power outages.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] The object of the present invention is to provide a high-current connector temperature control method based on temperature rise management and a high-current connector thereof, so as to solve the problems in the above-mentioned background technology.

[0007] In order to achieve the above objectives, the present invention provides the following technical solution: a high current connector temperature control method based on temperature rise management, specifically comprising the following steps: Detect the current transmission status of high-current connectors during operation to determine whether they are continuously carrying high current; When the high-current connector is in continuous high-current operation, obtain the structural parameters of the high-current connector to determine whether there is a restricted heat conduction path between the metal shell of the high-current connector and the contact area; In the presence of a restricted heat conduction path, the thermal state information of the high-current connector during operation is collected. Combined with the internal structural configuration of the high-current connector, a structural thermal distribution model is established to characterize the heat conduction process from the contact area to the metal shell. Based on the established structural thermal distribution model and the collected thermal state information, the degree of thermal information collection deviation is evaluated when the heat conduction path is restricted; Based on the evaluation results, determine whether temperature control should be performed, and implement corresponding temperature control measures based on the judgment results; Based on the compatibility between the evaluation results and the temperature control operations, the generation mechanism of the evaluation results is continuously optimized to enhance the dynamic response capability of the temperature control processing.

[0008] Preferably, when the high-current connector is in continuous high-current operation, the structural parameters of the high-current connector are obtained to determine whether there is a restricted heat conduction path between the metal shell of the high-current connector and the contact area in the structure, specifically: When the high-current connector is in continuous high-current operation, the structural parameters of the high-current connector are obtained, including the structural distance between the metal shell and the contact area of ​​the high-current connector, the thermal conductivity of the materials included in the thermal path, and the spatial distribution characteristics of the insulation barrier layer; When the structural distance exceeds the preset critical length of thermal conduction, the thermal path contains a material segment with thermal conductivity lower than the set thermal conductivity value, and there are also continuously arranged insulating barrier layer segments, it is determined that the metal shell of the high-current connector has a structurally restricted thermal path between it and the contact area.

[0009] Preferably, in the case of a limited heat conduction path, the thermal state information of the high-current connector during operation is collected, and combined with the internal structural configuration of the high-current connector, a structural thermal distribution model is established to characterize the process of heat conduction from the contact area to the metal shell, specifically: In the case of limited heat conduction paths, collect thermal status information of high-current connectors during operation, including surface temperature data of the metal shell and current-carrying thermal performance parameters generated under operating current; Combined with the internal structural configuration of the high-current connector, the contact area is taken as the starting point of the heat source. The spatial arrangement relationship, material thermal conductivity, structural dimension information and coverage of the insulation barrier layer of each structural segment are extracted in sequence according to the heat conduction path. A corresponding structural thermal distribution model is established to characterize the thermal energy distribution trend, energy attenuation process and spatial position of the obstructed part in the heat conduction path from the contact area to the outside of the metal shell.

[0010] Preferably, based on the established structural thermal distribution model and the collected thermal state information, evaluating the degree of thermal information collection deviation under the condition of limited heat conduction path specifically includes the following steps: Extract the structural heat conduction configuration information from the established structural heat distribution model, extract the external thermal response dynamic information from the collected thermal state information, and perform normalization processing after extraction; Based on the normalized structural heat conduction configuration information and external thermal response dynamic information, the structural thermal response deviation coefficient and thermal load perception hysteresis index are generated respectively. Based on the generated structural thermal response deviation coefficient and thermal load perception hysteresis index, the acquisition deviation index is generated through weighted summation; A preset acquisition deviation index threshold range is determined, and after determination, it is compared with the generated acquisition deviation index, and the degree of thermal information acquisition deviation under the condition of limited heat conduction path is evaluated based on the comparison result.

[0011] Preferably, the logic for obtaining the structural thermal response deviation coefficient is as follows: The structural heat conduction configuration information is extracted from the established structural heat distribution model, specifically including the theoretical temperature value of each node of the heat conduction path and the physical length of the heat conduction path. These two types of data are divided by their corresponding preset maximum values ​​to obtain the normalized theoretical temperature value of each node of the heat conduction path and the physical length of the heat conduction path, and are calibrated as and , represents the normalized heat conduction path The theoretical temperature value of each node, represents the normalized physical length of the heat conduction path, , is a positive integer; The external thermal response dynamic information is extracted from the collected thermal state information, specifically including the sensor measured temperature value at each node of the corresponding heat conduction path, and divided by the corresponding preset maximum value to obtain the normalized sensor measured temperature value at each node of the corresponding heat conduction path, and calibrated as , Represents the normalized corresponding heat conduction path The actual temperature value measured by the sensor at each node; Calculate the structural thermal response deviation coefficient. The specific calculation formula is as follows: Where, is the structural thermal response deviation coefficient.

[0012] Preferably, the logic for obtaining the heat load perception hysteresis index is as follows: The external thermal response dynamic information is extracted from the collected thermal state information, specifically including two types of data: the theoretical thermal power generated by the large current carrier per unit time and the temperature rise rate of the metal shell surface per unit time. These two types of data are divided by their corresponding preset maximum values ​​to obtain the normalized theoretical thermal power generated by the large current carrier per unit time and the temperature rise rate of the metal shell surface per unit time, and are calibrated as and , It represents the normalized theoretical heat power generated by the large current per unit time. It represents the normalized rate of temperature rise per unit time on the surface of the metal shell; Calculate the thermal load perception hysteresis index. The specific calculation formula is as follows: Where, is the heat load perception hysteresis index.

[0013] Preferably, based on generating the thermal response deviation coefficient of the structure and thermal load perception hysteresis index , the acquisition deviation index is generated by weighted summation. The specific calculation formula is as follows: Where, is the acquisition deviation index, and are the structural thermal response deviation coefficients and thermal load perception hysteresis index The non-zero weight coefficient of .

[0014] Preferably, a preset acquisition deviation index threshold interval is determined , and after determination, the generated acquisition deviation index A comparison was performed and the degree of thermal information collection deviation under the condition of limited heat conduction path was evaluated based on the comparison results. The specific comparison analysis is as follows: like ,The deviation degree of thermal information collection under the condition of ,limited heat conduction path is low deviation degree; like ,The degree of thermal information collection deviation under the condition of ,limited heat conduction path is medium in degree; like ,The degree of thermal information collection deviation under the condition of ,limited heat conduction path is severe deviation.

[0015] Preferably, based on the evaluation result, it is determined whether temperature control should be performed, and corresponding temperature control measures are performed based on the determination result, specifically: When the evaluation result shows a low deviation, it is determined that no temperature control is required, and the current operating state of the high-current connector remains unchanged; If the evaluation result shows a medium deviation, it is determined that temperature control warning processing is required. The implemented temperature control processing measures include limiting the current intensity within the set pre-downshift range and triggering the temperature rise risk warning instruction; When the evaluation result is a serious deviation, it is determined that forced temperature control must be performed. The temperature control measures implemented include starting the forced cooling device and cutting off the current supply to the high-load channel to reduce the temperature of the contact area and prevent further thermal runaway.

[0016] Preferably, the high current connector based on temperature rise management includes a high current identification module, a thermal conductivity constraint determination module, a thermal characteristic modeling module, a deviation evaluation module, a temperature control decision module and a response optimization module; The high current identification module detects the current transmission status of the high current connector during operation and determines whether it is continuously carrying high current; The thermal conductivity constraint determination module obtains the structural parameters of the high-current connector when the high-current connector is continuously carrying high current, and determines whether there is a structurally restricted thermal conductivity path between the metal shell of the high-current connector and the contact area; The thermal characteristics modeling module collects thermal status information of the high-current connector during operation when the heat conduction path is restricted. Combined with the internal structure of the high-current connector, it establishes a structural thermal distribution model to characterize the process of heat conduction from the contact area to the metal shell; Deviation assessment module, based on the established structural thermal distribution model and the collected thermal state information, evaluates the degree of thermal information collection deviation under the condition of limited heat conduction path; The temperature control decision module determines whether temperature control should be performed based on the evaluation results and executes the corresponding temperature control measures based on the judgment results; The response optimization module continuously optimizes the generation mechanism of evaluation results based on the adaptation between the evaluation results and the temperature control operation to enhance the dynamic response capability of the temperature control processing.

[0017] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. This invention establishes a structural thermal distribution model and combines it with thermal status information during operation to assess the degree of thermal information collection deviation for high-current connectors with restricted heat conduction paths. This significantly improves the previous problem of thermal status misjudgment caused by relying solely on the external temperature collection results of the metal shell. The degree of deviation is comprehensively reflected through two quantitative indicators: the structural thermal response deviation coefficient and the thermal load perception hysteresis index. This allows the system to accurately determine whether the contact area is in a thermal risk state. Even if the external temperature appears normal, it can still identify potential internal overheating, effectively avoiding delays or omissions in temperature control operations.

[0018] 2. The present invention refines the deviation assessment results into three levels: low deviation, medium deviation, and severe deviation, and matches differentiated temperature control processing strategies for different levels, building a closed-loop control logic for temperature control judgment and decision-making. Compared with the traditional fixed threshold triggered temperature control mode, this solution has stronger judgment granularity and response flexibility. It can not only issue early warnings in the event of minor anomalies, but also quickly perform forced cooling and current cut-off in high-risk situations to prevent thermal runaway escalation. At the same time, the evaluation logic can be continuously adaptively optimized to achieve feedback learning of the actual performance during operation, thereby continuously improving the system's dynamic response capability and adaptation efficiency.

[0019] 3. This invention integrates structural parameters (structural distances, material thermal conductivity, insulation layer distribution) with thermal data (temperature variation, current-carrying thermal power) into a model-driven evaluation mechanism, forming a digital modeling system for the thermal behavior of high-current connectors. The modeling process, data normalization, and weighting algorithm are all based on objective, collectible, and calculable data, ensuring the system's high feasibility. Furthermore, the model exhibits excellent scalability and adaptability to high-current connector application scenarios of varying specifications and structural forms. It possesses strong versatility, portability, and industrial applicability, laying a solid foundation for the development of intelligent electrical connection management systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0021] Figure 1 The present invention is a flow chart of a high-current connector temperature control method based on temperature rise management and a high-current connector.

[0022] Figure 2 The figure is a schematic diagram of a module of a high-current connector temperature control method based on temperature rise management and a high-current connector thereof according to the present invention. DETAILED DESCRIPTION

[0023] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0024] The present invention provides Figure 1 The high current connector temperature control method based on temperature rise management shown in the figure specifically includes the following steps: Detect the current transmission status of high-current connectors during operation to determine whether they are continuously carrying high current; By collecting the current change data of the high-current connector during operation, and combining it with the historical operating conditions, load duration and current-carrying trends, a comprehensive analysis of its current transmission status can be conducted. In specific implementation, the sampling device is first used to record the current value in the connector's current-carrying channel in real time, and the continuously collected current data is input into the calculation model. By statistically analyzing indicators such as the current mean value, fluctuation amplitude and high-load maintenance time within the cycle, characteristic information representing the continuous high-current operating state is extracted. Then, by setting a set of combined judgment conditions for characterizing "continuously carrying high current", including the average current exceeding the threshold, the continuous exceeding of the high-current threshold time to meet the set cycle, and the stable rate of change, with the help of a rule engine or algorithm judgment module, it is determined whether the current operating state meets the characteristic requirements of "continuous high current". All judgment logic can be executed in the controller as a software algorithm to automatically identify whether the connector has entered a high-heat risk operating state that requires temperature control management.

[0025] The reason why it is necessary to accurately judge whether a high-current connector is in a state of continuous high-current operation is because this state is often a prerequisite for heat accumulation in the contact area, especially in structures with limited heat conduction paths. The instantaneous current alone cannot effectively reflect the risk of thermal backlog. By identifying the intensity, stability and continuity characteristics of the current, an initial assessment basis that is highly correlated with the heat accumulation process can be established. Only when it is determined that the connector is in a long-term high-current operation condition is it necessary to further evaluate its structural heat conduction path and the degree of temperature rise risk, so as to ensure that the temperature control process is activated only when there is a real thermal risk. This kind of pre-operation status identification by software not only improves the accuracy and real-time performance of the temperature control response, but also avoids the false triggering of the temperature control mechanism under low load or instantaneous fluctuations, ensuring that the temperature rise management process is targeted and efficient.

[0026] When the high-current connector is in continuous high-current operation, obtain the structural parameters of the high-current connector to determine whether there is a restricted heat conduction path between the metal shell of the high-current connector and the contact area; In this embodiment, when the high-current connector is in continuous high-current operation, the structural parameters of the high-current connector are obtained to determine whether there is a restricted heat conduction path between the metal shell of the high-current connector and the contact area. Specifically, When the high-current connector is in continuous high-current operation, the structural parameters of the high-current connector are obtained, including the structural distance between the metal shell and the contact area of ​​the high-current connector, the thermal conductivity of the materials included in the thermal path, and the spatial distribution characteristics of the insulation barrier layer; The structural parameters of high-current connectors can be obtained by establishing an association with their design modeling data or manufacturing configuration information. The specific approach is to import the contact area position, metal shell outline, insulation layer arrangement, material type and other data contained therein into the control software in a standard structured format based on the three-dimensional structural modeling file, structural data list or engineering drawing provided by the connector when it leaves the factory. In the software environment, by setting identification rules, the geometric distance information from the metal shell to the contact area is extracted, the material type of each component on the heat conduction path and its corresponding thermal conductivity parameters are marked, and the spatial arrangement and coverage length of the insulating material are further identified. All structural information is stored in an electronic form in an associated database. The control logic automatically obtains and calls the structural parameters by reading the connector structure data of the corresponding model or number without relying on manual measurement, ensuring that the subsequent temperature rise judgment logic is based on a real and verifiable structural foundation.

[0027] The structural parameters of high-current connectors must be acquired while they are operating continuously and carrying high currents. This is because the physical characteristics of the heat rise conduction path determine the efficiency and hysteresis of heat transfer from the contact area to the metal housing. However, this structure is inherently static and cannot be reflected in real time through thermal measurement. Therefore, a clear understanding of the connector's geometry and material composition is essential to determine whether any deviations in thermal data collection are caused by the heat conduction path itself. This is particularly true when there is a long structural distance between the metal housing and the contact area, a high proportion of low-thermal-conductivity materials, or a continuous insulating barrier layer. Heat transfer is significantly delayed, causing surface temperature measurements to fail to reflect internal thermal risks. Without preemptive structural understanding through software, it is impossible to effectively model and evaluate the source of these deviations, making it impossible to accurately determine the risk of "temperature rise misinterpretation," thus making subsequent temperature control decisions unreliable. Therefore, this step is an essential structural prerequisite for the entire deviation assessment and temperature control management process.

[0028] When the structural distance exceeds the preset critical length of thermal conduction, the thermal path contains a material segment with thermal conductivity lower than the set thermal conductivity value, and there are also continuously arranged insulating barrier layer segments, it is determined that the metal shell of the high-current connector has a structurally restricted thermal path between it and the contact area.

[0029] This judgment logic is automatically executed in the software using a structural parameter analysis model. It is implemented by first extracting the geometric path information from the contact area to the metal shell from the structural data and using spatial analysis tools to determine whether the distance along this path exceeds the critical heat conduction length. Next, the software compares the thermal conductivity of each segment from the imported material property table to identify any structural segments along the path whose thermal conductivity falls below a specified threshold. Finally, the material layout index is used to analyze whether there are continuously arranged insulation barrier segments and verify whether their lengths meet the set judgment criteria. If all three conditions are met, the software generates a "limited heat conduction path" flag. This judgment is based on the following: longer structural distances increase the path hysteresis during heat conduction; lower material thermal conductivity results in lower heat transfer efficiency; and continuously distributed insulation barriers significantly disrupt the continuity of the heat path. These three factors together constitute a typical pattern of reduced heat conduction efficiency and are the physical root cause of the difficulty in timely heat transfer from the contact area to the shell. Therefore, using these three structural dimensions as conditional triggers, the software can accurately identify whether the current connector faces the risk of delayed temperature rise response.

[0030] Preset critical heat conduction lengths, material segments with set thermal conductivity values, and continuous insulation barrier segments can all be centrally configured and maintained within the software system using engineering experience data combined with experimental statistical models. Specifically, the critical heat conduction length is a structural distance threshold established based on experimental measurements of the heat dissipation capacity of various high-current connector models under standard loads. When the structural path exceeds this length, heat transfer from the source to the housing is significantly delayed. The thermal conductivity value is determined by referencing the thermal conductivity coefficients of various commonly used engineering materials (such as nylon, polyimide, and engineering plastics) under thermal conditions, selecting a threshold that represents a material with high thermal resistance and poor heat transfer as the identification threshold. The continuity of insulation barrier segments is determined by ensuring that they are arranged as adjacent units along the structural path and that their cumulative length exceeds a specified proportion of the thermal conduction segments, for example, exceeding 1 / 3 of the path length. All these threshold parameters can be preset by professional engineers within the structural analysis platform and integrated into the control software as a configuration file. The algorithm automatically calls these parameters and performs a logical comparison with the actual structural parameters, achieving a standardized and automated judgment process.

[0031] In the presence of a restricted heat conduction path, the thermal state information of the high-current connector during operation is collected. Combined with the internal structural configuration of the high-current connector, a structural thermal distribution model is established to characterize the heat conduction process from the contact area to the metal shell. In this embodiment, when there is a limited heat conduction path, the thermal state information of the high-current connector during operation is collected, and combined with the internal structural configuration of the high-current connector, a structural thermal distribution model is established to characterize the process of heat conduction from the contact area to the metal shell. Specifically, In the case of limited heat conduction paths, collect thermal status information of high-current connectors during operation, including surface temperature data of the metal shell and current-carrying thermal performance parameters generated under operating current; The thermal status information of high-current connectors during operation can be collected automatically under the software control logic through the linkage between thermal monitoring components and data interfaces. Specifically, the software first accesses the temperature data stream transmitted by the temperature measuring element set on the outside of the metal shell through a standard communication protocol, and extracts the surface thermal change value as the first type of data reflecting the external temperature rise trend. At the same time, the software synchronously calls the real-time load current value, voltage value and contact impedance information uploaded by the current monitoring node, and converts it into the corresponding current-carrying thermal performance parameters as the second type of data through the thermal power conversion rule. All collected data are uniformly stored in the form of time series, classified and sorted according to the connector number and operating conditions, and then directed by the software scheduler for subsequent structural model matching and deviation evaluation processing. The entire acquisition process is driven by a preset threshold, and the data acquisition process is triggered only when the heat conduction path is detected to be restricted, which not only ensures the real-time acquisition of information, but also avoids the waste of redundant monitoring resources.

[0032] The reason why it is necessary to collect surface temperature data and current-carrying thermal parameters on the exterior of the metal shell when there is a restricted heat conduction path is that the restricted structure will cause a significant attenuation of heat from the contact area to the shell's conduction path. Relying solely on external temperature values ​​cannot accurately restore the internal thermal conditions. Therefore, it is necessary to introduce thermally dependent variables and current-carrying characteristic parameters as a basis for evaluation. Surface temperature, as a direct manifestation of the connector's external thermal response, can reveal whether there is heat transfer lag, while current-carrying thermal parameters are the core indicators of internal heating intensity. The combination of the two establishes an effective basis for thermal conduction comparison. By collecting and storing these two types of data in parallel in the software, it is possible to provide authentic, continuous, and highly correlated data support for subsequent structural thermal distribution modeling and deviation assessment. This ensures that temperature control decisions are based on reliable thermal operation data, avoids issues such as delayed or even failed temperature control decisions due to information distortion, and ensures the safety and response accuracy of high-current connectors in complex thermal structures.

[0033] Combined with the internal structural configuration of the high-current connector, the contact area is taken as the starting point of the heat source. The spatial arrangement relationship, material thermal conductivity, structural dimension information and coverage of the insulation barrier layer of each structural segment are extracted in sequence according to the heat conduction path. A corresponding structural thermal distribution model is established to characterize the thermal energy distribution trend, energy attenuation process and spatial position of the obstructed part in the heat conduction path from the contact area to the outside of the metal shell.

[0034] The structural thermal distribution model is established in combination with the internal structural configuration of the high-current connector, and the structural parameters and heat source positioning data can be orderly integrated through the software. The specific method is: the software first takes the contact area as the starting point of the heat source, calls the structural parameter file obtained in the early stage, and divides the structural segments according to the physical path of heat extending from the internal contact area to the metal shell; the spatial arrangement relationship, material thermal conductivity, size characteristics and coverage position of the insulating barrier layer of each structural segment are extracted in turn, and the nodes are described and the heat conduction path is linked in a graph structure in the modeling algorithm. Subsequently, the software allocates the node heat capacity and thermal resistance value according to the arrangement order and properties of the structural segments, completes the structural thermal distribution modeling of the entire heat conduction path in the software environment, and retains the spatial coordinates and attribute labels of each node in the model to characterize the flow trend of thermal energy, the change in strength and the location distribution of conduction obstacles, thereby constructing a model path that reflects the heat flow conduction under the real structure.

[0035] The core of this structural thermal distribution model is to map the heat conduction behavior to the internal structural parameters of the high-current connector one by one, and to express it graphically according to the physical thermal channel. Among them, the contact area is defined as the heat source point, corresponding to the source node of the model; each section of structural material and insulation unit connected to the metal shell corresponds to the relay node, and each node is accompanied by specific thermal resistance properties and spatial coordinate information in the model. The structural segments are connected in series to form a link in physical order. If there is a sudden increase in thermal resistance, a decrease in thermal capacity, or a closed area of ​​the insulation barrier layer in the link, a conduction weakening mark is formed in the model. This model no longer only reflects the structural form of the connector, but encodes the actual attenuation process of heat transfer, the energy distribution path and the restricted points in a logically readable and data-judgable form, so that subsequent thermal data input can be accurately projected onto the structural node, completing the structural restoration and identification of the actual temperature rise deviation path.

[0036] The fundamental reason for establishing a structural thermal distribution model is to address the problems of path shielding, energy attenuation, and delayed feedback during the process of heat conduction from the contact area to the external shell. Due to the complex internal structure of high-current connectors, the thermal conductivity of different materials varies greatly, and the insulation layer may cause thermal isolation. As a result, even if the shell temperature is normal, internal thermal risks are difficult to identify in a timely manner. Traditional temperature control strategies make it difficult to judge the degree of internal risk based on surface temperature, which leads to delayed or even missed temperature control responses. By constructing this model, dynamic distribution mapping of thermal state data in spatial paths can be achieved, thereby establishing a physical basis for evaluating the degree of deviation in subsequent thermal information collection. The structural thermal distribution model not only helps identify potential areas of concentrated thermal resistance, but also serves as an inference support chain for determining temperature rise anomalies, enhancing the accuracy and foresight of temperature control processing. It is a key intermediary link in the transition from data-driven to structure-behavior fusion judgment.

[0037] Based on the established structural thermal distribution model and the collected thermal state information, the degree of thermal information collection deviation is evaluated when the heat conduction path is restricted; In this embodiment, based on the established structural thermal distribution model and the collected thermal state information, the degree of thermal information collection deviation under the condition of limited heat conduction path is evaluated, which specifically includes the following steps: Extract the structural heat conduction configuration information from the established structural heat distribution model, extract the external thermal response dynamic information from the collected thermal state information, and perform normalization processing after extraction; Extracting structural thermal conductivity configuration information and external thermal response dynamic information is handled through object-oriented data parsing and structure mapping. For extracting structural thermal conductivity configuration information, a directed thermal conductivity graph is constructed by reading the topological structure, spatial arrangement, path length, node sequence, material type, and corresponding thermal conductivity of each heat conduction path within the established structural thermal distribution model. Each path segment is then parsed segment by segment, and information such as the physical dimensions, thermal conductivity parameters, and insulation coverage of each structural segment is encapsulated into standard structural data units and output as configuration information. For extracting external thermal response dynamic information, the data stream from the temperature sensor acquisition interface is parsed in real time to extract the temperature time series curve of the metal shell surface. Combined with the current and voltage sampling results during high-current operation, the built-in I²R model is used to calculate the current-carrying heat input. Parameters such as the surface temperature rise rate, maximum temperature difference, and thermal response delay are converted into dynamic thermal response feature vectors through an algorithm parsing module. The entire extraction process is automated based on data structure recognition and physical meaning mapping, requiring no human intervention, ensuring the uniformity and computability of the extracted results.

[0038] Based on the normalized structural heat conduction configuration information and external thermal response dynamic information, the structural thermal response deviation coefficient and thermal load perception hysteresis index are generated respectively. Based on the generated structural thermal response deviation coefficient and thermal load perception hysteresis index, the acquisition deviation index is generated through weighted summation; A preset acquisition deviation index threshold range is determined, and after determination, it is compared with the generated acquisition deviation index, and the degree of thermal information acquisition deviation under the condition of limited heat conduction path is evaluated based on the comparison result.

[0039] Determining the pre-set acquisition deviation index threshold interval is typically accomplished through feature clustering and multidimensional statistical regression methods based on historical sample data. Specifically, a dataset of historical thermal response samples under multiple known operating conditions is first constructed. Each sample includes a combination of the structural thermal response deviation coefficient and the thermal load perception hysteresis index, along with its corresponding actual thermal risk label (e.g., normal, deviation, or severe deviation). This sample space is then clustered using density clustering (e.g., DBSCAN) or a Gaussian mixture model to preliminarily delineate three natural distribution intervals for the acquisition deviation index. Based on the clustering results, linear discriminant analysis (LDA) or support vector regression (SVR) methods are then introduced to construct fitted boundaries in a two-dimensional projection space, thereby extracting boundary values ​​corresponding to each thermal risk level as the "acquisition deviation index threshold interval." Finally, this threshold interval is embedded in the evaluation module as an interval comparison table for automatic identification and comparison. The entire process can be completed through automated iterative modeling using software, offering high accuracy, adaptability, and scalability, making it suitable for dynamically evolving operating environments.

[0040] In this embodiment, the logic for obtaining the structural thermal response deviation coefficient is as follows: The structural heat conduction configuration information is extracted from the established structural heat distribution model, specifically including the theoretical temperature value of each node of the heat conduction path and the physical length of the heat conduction path. These two types of data are divided by their corresponding preset maximum values ​​to obtain the normalized theoretical temperature value of each node of the heat conduction path and the physical length of the heat conduction path, and are calibrated as and , represents the normalized heat conduction path The theoretical temperature value of each node, represents the normalized physical length of the heat conduction path, , is a positive integer; The path parsing mechanism within the structural thermal distribution model automatically acquires two types of data: the theoretical temperature values ​​of each node along the heat conduction path and the physical length of the heat conduction path. Specifically, the acquisition of the theoretical temperature values ​​relies on the results of heat source modeling. This modeling typically uses the contact area as the heat source point and calculates the theoretical steady-state temperature distribution of each structural node along the heat conduction path using finite difference or finite element methods. The position of each node is determined by the three-dimensional structural topology, and its temperature calculation is based on the relationship between the heat flux transfer and thermal conductivity between nodes in the heat conduction equation. The output is the theoretical temperature field of the node under unit current heat input. The physical length of the heat conduction path is derived by accumulating the Euclidean distance between nodes or the path geometry routing information in the structural modeling data. The system automatically traverses the node sequence and solves the spatial length of each path segment, accumulating them to form the total physical length of the complete heat conduction path. Both types of data can be extracted and stored as vector sequences in real time through the numerical parsing module during model initialization or operation, enabling full software implementation.

[0041] The theoretical temperature values ​​and physical lengths of each node in the thermal path are normalized. This primarily aims to eliminate the influence of different units and numerical magnitudes on the subsequent evaluation formula calculation results, thereby ensuring that the output of the structural thermal response deviation coefficient (TRD) has a uniform dimension and is comparable. The "preset maximum value" used in normalization is not a static value set manually, but a boundary parameter automatically generated through historical sample analysis. Specifically, the maximum theoretical temperature value is extracted from the highest node temperature previously simulated for the same connector model and similar current-carrying conditions and set as the normalization benchmark. The maximum physical length value is derived from the longest effective thermal conduction path statistically obtained from high-current connector structural models in the product database, combined with the actual maximum configuration. The preset maximum value is automatically set during the initial system modeling or deployment process and can be dynamically updated based on new data collection to ensure the stability and generalizability of the normalized data input. This approach not only improves the versatility of model evaluation but also enhances the software's adaptability across different product models.

[0042] The external thermal response dynamic information is extracted from the collected thermal state information, specifically including the sensor measured temperature value at each node of the corresponding heat conduction path, and divided by the corresponding preset maximum value to obtain the normalized sensor measured temperature value at each node of the corresponding heat conduction path, and calibrated as , Represents the normalized corresponding heat conduction path The actual temperature value measured by the sensor at each node; To obtain the sensor-measured temperature values ​​at each node in the corresponding heat conduction path, the thermal state acquisition interface typically automatically parses the data stream of each temperature measurement point and aligns them with the heat conduction path node mapping table. In implementation, the software first establishes a one-to-one mapping between each structural heat conduction path node and the physical sensor location using the structural model and the sensor location configuration table. During operation, the temperature acquisition module periodically obtains the current temperature values ​​of each measurement point from the sensor bus (such as I²C, SPI, or CAN). After data cleaning and anomaly removal, it extracts the stable temperature readings for each sensor node. These measured temperature values ​​are automatically stored in the corresponding data vector and spatially aligned with the heat conduction path using a path indexing mechanism. This creates a complete "measured temperature-node location" matrix, providing the foundation for subsequent deviation analysis. This entire process requires no human intervention, relying on the consistency of modeling and structural coordinates to ensure the accuracy and schedulability of the measured data.

[0043] The primary purpose of normalizing measured temperature values ​​is to establish a consistent input space across multiple sensor nodes, preventing distortion of overall evaluation metrics due to excessively high or low temperature values ​​at a single sensor point. Normalization aligns all measured temperature values ​​within the range [0, 1], facilitating subsequent deviation comparisons with theoretical temperature values ​​and complex function calculations. The "corresponding preset maximum value" used here is a dynamic upper temperature limit set for each sensor-specific node in the heat transfer path, not a static fixed value. This is typically determined in two ways: one is to extract the maximum temperature at that node based on historical measured data for that type of connector under typical full-load or overload conditions; the other is to estimate the permissible temperature limit based on the material environment at that location (such as housing material, air cooling path) and thermal safety regulations. This preset maximum value can be generated offline using thermal simulation software before software deployment, or dynamically modified during early equipment operation through a monitoring and learning mechanism to achieve adaptive matching. This normalization step standardizes the measured temperature values, providing a data foundation for the scientific calculation of the structural thermal response deviation coefficient and significantly enhancing adaptability and generalization capabilities under diverse operating conditions.

[0044] Calculate the structural thermal response deviation coefficient. The specific calculation formula is as follows: Where, is the structural thermal response deviation coefficient.

[0045] The purpose of this calculation method is to comprehensively evaluate the overall deviation between the theoretical thermal distribution and the measured thermal response of high current connectors under the condition of limited heat conduction path, so as to reveal the risk of temperature rise misinterpretation caused by structural blocking, thermal attenuation or sensor failure. Characterize the absolute deviation between the theoretical temperature value and the measured temperature value of each heat conduction path node, which is used to capture the difference in thermal response between the model and the actual. Using absolute value operations can avoid misjudgment caused by the offset of positive and negative differences. The second step is to add 1 to the difference value and take the natural logarithm to achieve a nonlinear buffer mapping of the deviation. When the deviation is small, the function grows slowly, which helps to suppress the interference of small fluctuations on the overall evaluation; when the deviation is large, the function output grows rapidly, which can highlight the impact of significant abnormal nodes. The next multiplication is the normalized physical length of the heat conduction path. Its physical significance lies in introducing the overall length of the heat conduction path as an influencing factor into the model, emphasizing the increased thermal resistance and error amplification effects associated with structural complexity due to long paths. The final summation and averaging of all g nodes eliminates the dominant effect of single-point noise on the overall evaluation results, making TRD a representative indicator of full-path average deviation. This formula strikes a good balance between physical meaning, numerical stability, and data interpretability, providing a robust and engineering-sounding basis for determining thermal deviations for subsequent temperature control strategies.

[0046] The magnitude of the structural thermal response deviation (TRD) directly reflects the overall discrepancy between the theoretical temperature distribution and the measured temperature response under conditions of restricted heat conduction paths, thus serving to assess the severity of thermal information acquisition bias. A low TRD value indicates a small deviation between the theoretical temperature at each node in the heat conduction path and the corresponding sensor's measured temperature. This indicates that, despite structural constraints on heat conduction, no significant perception deviation occurs, and the temperature rise data accurately reflects the true thermal state of the contact area. Conversely, a high TRD value indicates significant theoretical-measured temperature discrepancies at most nodes. This is particularly true in structures with long paths or severe insulation barriers. This discrepancy is amplified by the path length factor, reflecting significant attenuation or delay during heat conduction. Consequently, the sensor-derived information no longer accurately reflects the thermal risk of the contact area. Therefore, an increase in the TRD value indicates an increase in thermal information acquisition bias, potentially leading to delayed or misjudgment of temperature control decisions, necessitating dynamic correction and response optimization of the temperature control strategy. The TRD value serves as a core evaluation metric in this model, providing a quantitative mapping between thermal modeling results and the degree of perception deviation. It is a key indicator for identifying the risk of temperature rise perception failure.

[0047] In this embodiment, the logic for obtaining the thermal load perception hysteresis index is as follows: The external thermal response dynamic information is extracted from the collected thermal state information, specifically including two types of data: the theoretical thermal power generated by the large current carrier per unit time and the temperature rise rate of the metal shell surface per unit time. These two types of data are divided by their corresponding preset maximum values ​​to obtain the normalized theoretical thermal power generated by the large current carrier per unit time and the temperature rise rate of the metal shell surface per unit time, and are calibrated as and , It represents the normalized theoretical heat power generated by the large current per unit time. It represents the normalized rate of temperature rise per unit time on the surface of the metal shell; The theoretical thermal power generated by large current carrying per unit time can be calculated by collecting the current data of the connector during operation through software, and combining it with the resistance parameters of the conductor part of the large current connector. This process does not require manual intervention. After collecting the real-time current, the software will process it accordingly with the preset conductor resistance to obtain the current-carrying and heating capacity within that time period. The temperature rise rate on the surface of the metal shell is obtained by collecting multiple consecutive temperature points on the outer surface of the shell within a specific interval, and calculating the temperature difference and time difference between the two adjacent temperature points to obtain the heating rate per unit time. These data are all from sensor sampling under software control during the thermal status monitoring process, and can be associated through timestamps to ensure that the thermal power and surface temperature rise form matching inputs within the same time segment, providing a continuous and reliable dynamic data source for subsequent analysis.

[0048] The purpose of normalization is to adjust two types of data with different numerical ranges and units to a unified magnitude range, avoiding imbalances in subsequent calculation weights due to differences in the original numerical values, while improving the comparability and mathematical stability between parameters. The preset maximum value of theoretical thermal power is usually taken from the maximum power output capacity of this type of high-current connector under experimental testing or safety design conditions. This value can be obtained from prototype test data or product standard information. The maximum value of the temperature rise rate is based on the thermal inertia of the material and environmental conditions. The maximum temperature rise slope of the connector under natural or forced heat dissipation conditions is selected as a reference. This value can be extracted from the high percentile of historical operating data. The software will load these maximum values ​​as the default benchmark at the beginning of operation, and can automatically optimize and self-learn through the model update mechanism during operation to ensure that the normalization process is always consistent with the actual working conditions. This processing method not only improves the accuracy of subsequent calculations, but also provides a good input guarantee for the perception hysteresis index.

[0049] Calculate the thermal load perception hysteresis index. The specific calculation formula is as follows: Where, is the heat load perception hysteresis index.

[0050] The calculation formula for the thermal load perception hysteresis index combines normalized theoretical thermal power and temperature rise rate to establish a dynamic assessment mechanism for the degree of temperature control response hysteresis. In the formula, theoretical thermal power reflects the heat generation trend during high-current operation and is an indicator of the strength of the system's internal heat source. The temperature rise rate represents the speed at which the metal shell surface responds to heat and is an external indicator of whether the system is responding promptly to the internal heat load. When the theoretical thermal power is high and the temperature rise rate is low, it means that internal heating is rapid but the external sensor response is slow. In this case, the exponential function will produce an amplifying effect, causing the overall index to rise rapidly, effectively identifying potential thermal hysteresis risks. Specifically, the exponential calculation increases the weight of "slow response" to enhance sensitivity in detecting temperature control judgment hysteresis scenarios. Multiplying it by the theoretical thermal power enables the index to adaptively adjust to different heat source intensities, ensuring no false positives under light loads and no missed warnings under heavy loads. The overall calculation logic not only reflects the dynamic balance between thermal input and thermal perception, but also forms a quantitative assessment method with high discrimination for thermal hysteresis in temperature control systems.

[0051] Thermal load perception hysteresis index The magnitude of the index is directly used to assess the degree of lag in thermal information collection when the heat conduction path is restricted. A larger value indicates a higher theoretical thermal power generated per unit time by the high-current connector, while the rate of rise in the metal shell's surface temperature decreases. This indicates a clear "internal heating, external response" situation. This indicates that heat is severely obstructed in the conduction path, the external collection device's ability to perceive actual thermal risks lags, and the collected temperature rise data deviates from the true thermal state. Conversely, a smaller index indicates a closer match between thermal power and temperature rise, better synchronization of thermal responses, and a higher accuracy of the collected data in reflecting the internal thermal state. Therefore, the magnitude of this index serves as a core criterion for the degree of lag deviation in thermal information collection when the heat conduction path is restricted. Higher values ​​indicate a greater degree of deviation and the need for stronger temperature control intervention.

[0052] In this embodiment, based on the generated structure thermal response deviation coefficient and thermal load perception hysteresis index , the acquisition deviation index is generated by weighted summation. The specific calculation formula is as follows: Where, is the acquisition deviation index, and are the structural thermal response deviation coefficients and thermal load perception hysteresis index The non-zero weight coefficient of .

[0053] After completing the calculation of the structural thermal response deviation coefficient (TRD) and the thermal load perception hysteresis index (LPL), two weight coefficients are introduced to perform weighted integration of the two to generate the acquisition deviation index (ADI). In the actual implementation process, a set of weight coefficients can be preset. and , which correspond to the evaluation weights of TRD and LPL respectively, and are used to control the influence ratio of the two in the final deviation judgment. It mainly measures the importance of thermal information conduction deviation in the structural heat conduction path and is suitable for connectors with complex structures and significant thermal attenuation. It reflects the mismatch weight between thermal load and sensory response, and is more suitable for scenes with frequent thermal fluctuations and sensitive response lag. Both coefficients are real numbers greater than 0 and less than 1, and always satisfy , ensuring the evaluation formula is closed and computable. In specific applications, this set of coefficients can be dynamically adjusted using historical thermal condition data, error feedback curves, or scenario-based strategy optimization algorithms to adapt the acquisition deviation index to and accurately represent different thermal distortion characteristics. This entire process does not rely on external hardware intervention and can be efficiently executed within embedded algorithms, data processing platforms, or cloud platforms.

[0054] In this embodiment, the preset acquisition deviation index threshold interval is determined , and after determination, the generated acquisition deviation index A comparison was performed and the degree of thermal information collection deviation under the condition of limited heat conduction path was evaluated based on the comparison results. The specific comparison analysis is as follows: like ,The deviation degree of thermal information collection under the condition of ,limited heat conduction path is low deviation degree; This indicates that the error between the theoretical thermal distribution and the measured thermal performance is small, the heat conduction delay effect is insignificant under the condition of a restricted heat conduction path, and the temperature collection points can well reflect the actual thermal state of the contact area. In this state, the data based on the temperature rise management system is highly reliable, indicating that the current temperature control strategy does not need to be adjusted and can continue to operate according to the established parameters, helping to ensure the long-term stable operation of the connector and avoid excessive intervention.

[0055] like ,The degree of thermal information collection deviation under the condition of ,limited heat conduction path is medium in degree; This indicates a certain degree of error in the thermal information collection process, but not yet a significant level of distortion. In this case, the actual internal temperature of the connector may be slightly higher than the temperature reported by the external sensor point, and thermal conduction lag is beginning to take effect, but it has not yet posed a systemic thermal risk. This situation suggests that the temperature control strategy needs to remain vigilant and appropriate intervention measures can be taken, such as reducing the current density, triggering a level 1 warning, or adjusting the heat dissipation structure in advance to suppress the spread of heat accumulation and thus control thermal risks without affecting system performance.

[0056] like ,The degree of thermal information collection deviation under the condition of ,limited heat conduction path is severe deviation.

[0057] This situation indicates a significant deviation between the thermal distribution model and the measured data, and a significant lag between the thermal power input and the external thermal response. This means that a significant temperature rise may have occurred in the connector contact area, but the external data collection device has not yet accurately captured it. This state indicates that the temperature rise risk is highly concentrated and there are blind spots in perception, which is very likely to cause local overheating, increased contact resistance, ablation, material degradation and other problems. To avoid connector damage or system power outages, mandatory temperature control measures must be immediately implemented, such as cutting off the current, activating advanced cooling mechanisms, or automatically switching to an alternative connection path to ensure safe operation and prevent the spread of the fault.

[0058] Based on the evaluation results, determine whether temperature control should be performed, and implement corresponding temperature control measures based on the judgment results; In this embodiment, based on the evaluation result, it is determined whether temperature control should be performed, and corresponding temperature control measures are performed based on the determination result, specifically: When the evaluation result shows a low deviation, it is determined that no temperature control is required, and the current operating state of the high-current connector remains unchanged; When the evaluation result is a low deviation, the software can be used to "determine that no temperature control is required and maintain the current operating state of the high-current connector unchanged." The implementation process includes the following key steps: First, the system compares the collected deviation index with the preset threshold range. When its value is lower than the set lower threshold, the software logic will classify the state as a low deviation and match the "do not trigger temperature control operation" response strategy in the internal state mapping table. Subsequently, based on this matching result, the software skips the temperature control logic in the temperature control decision sub-process and no longer issues any control instructions to the execution layer, such as not activating the cooling device or not triggering the current load reduction operation. Instead, it generates a "maintain status quo" flag and maintains the current operating parameters within the set working range, keeping the device running stably in the current operating state. The reason for adopting this judgment logic is that under low deviation conditions, the data obtained by external sensors is highly consistent with the calculation results of the theoretical model, indicating that heat conduction is not significantly affected and there is no risk of heat accumulation in the contact area. Therefore, it is not advisable to frequently intervene in regulation due to small fluctuations, so as to avoid increased system energy consumption or unnecessary resource scheduling, thereby achieving a balance between the accuracy and economy of the temperature control strategy.

[0059] If the evaluation result shows a medium deviation, it is determined that temperature control warning processing is required. The implemented temperature control processing measures include limiting the current intensity within the set pre-downshift range and triggering the temperature rise risk warning instruction; When the assessment result indicates a medium degree of deviation, the software can be used to determine that a temperature control warning process is required. The temperature control measures implemented include limiting the current intensity to within the set pre-reduction gear range and triggering a temperature rise risk reminder instruction. The specific implementation process is as follows: the software first compares the currently generated acquisition deviation index ADI with the preset threshold range. When its value is within the preset threshold range, it is judged to be a medium degree of deviation and mapped to the "warning processing" mode in the system's built-in deviation level judgment table. When this mode is triggered, the software will retrieve the corresponding "pre-reduction gear" setting parameters from the set graded current carrying strategy library and dynamically limit the current control command currently running on the high-current connector to ensure that the actual current carrying capacity drops to an acceptable range to suppress possible thermal imbalance risks. At the same time, the software will automatically generate a temperature rise risk reminder instruction and send it to the upper-level monitoring platform or operation and maintenance terminal through the communication interface, prompting relevant personnel to pay attention to changes in the connector's thermal status. The strategy is designed to balance operational continuity and safety. When the deviation does not reach a serious level, flexible control measures and risk warning mechanisms are adopted to alleviate potential heat loads and avoid excessive intervention, thereby improving the intelligent response capability and adaptability of the entire temperature control mechanism.

[0060] When the evaluation result is a serious deviation, it is determined that forced temperature control must be performed. The temperature control measures implemented include starting the forced cooling device and cutting off the current supply to the high-load channel to reduce the temperature of the contact area and prevent further thermal runaway.

[0061] If the assessment result indicates a severe deviation, the software determines that forced thermal control is necessary by comparing the acquisition deviation index (ADI) with the upper limit of a set threshold range. If the ADI significantly exceeds the upper limit of the set threshold range, the system, based on the built-in deviation level-response strategy mapping rules, determines that the thermal information acquisition deviation is severely distorted, posing a high risk of thermal runaway in the contact area. Based on this, the software automatically invokes the forced thermal control response chain. First, it activates the control logic of the cooling actuators associated with the high-current connector, for example, by sending a start signal to the cooling fan, liquid cooling pump, or phase change refrigeration unit to rapidly increase local heat dissipation efficiency. Second, the software simultaneously issues a high-load channel cutoff command to the current control unit, deactivating the high-current path before the thermal risk is resolved, thereby completely eliminating the heat source input. The key to executing this processing logic is that severe deviation indicates a high degree of distortion in the thermal conduction information, with the surface temperature measurement significantly underestimating the actual internal temperature rise. Continuing the current state can easily lead to catastrophic failures such as carbonization, melting, or insulation breakdown in the connector contact area. Therefore, rapid identification and forced intervention through software can prevent local overheating from further deterioration to the greatest extent possible, protecting the integrity of electrical connections and the safety of system operation.

[0062] Based on the compatibility between the evaluation results and the temperature control operations, the generation mechanism of the evaluation results is continuously optimized to enhance the dynamic response capability of the temperature control processing.

[0063] To achieve "continuously optimizing the generation mechanism of evaluation results based on the adaptability between the evaluation results and the temperature control operations", it can be achieved by introducing a feedback adaptive adjustment strategy through the software. Specifically, after each execution of the temperature control treatment measures, the software will automatically record the matching between the evaluation results (such as the ADI value and its corresponding deviation level) and the temperature control treatment measures taken (such as whether to start cooling, load reduction or current interruption), and continuously monitor the temperature change trend of the high-current connector contact area within the short time window after the treatment. If the temperature rise is successfully suppressed after the treatment, the system defines the treatment as a high-adaptability response, otherwise it is defined as low-adaptability. The software will statistically aggregate these response data, and dynamically adjust the calculation weight ratio of the structural thermal response deviation coefficient and the thermal load perception hysteresis index through the time-weighted average or exponential sliding average algorithm, so as to gradually converge to generate an ADI value calculation method that is more in line with the actual thermal risk evolution law.

[0064] The fundamental purpose of this setup is to leverage actual temperature control results to optimize the thermal risk assessment logic. This involves mapping historical processing results back to the parameter modeling mechanism, forming a dynamic, adaptive mechanism with a closed "risk-response-feedback" loop. This allows the software system to continuously refine parameter sensitivity and threshold criteria, thereby improving the accuracy of assessment results relative to actual risk levels, reducing false or delayed triggering, and enhancing the sensitivity and reliability of temperature control. This allows for rapid response and intelligent adjustment to thermal risks even when thermal paths are restricted.

[0065] like Figure 2 The high-current connector based on temperature rise management shown includes a high-current identification module, a thermal conductivity constraint determination module, a thermal characteristic modeling module, a deviation evaluation module, a temperature control decision module, and a response optimization module; The high current identification module detects the current transmission status of the high current connector during operation and determines whether it is continuously carrying high current; The thermal conductivity constraint determination module obtains the structural parameters of the high-current connector when the high-current connector is continuously carrying high current, and determines whether there is a structurally restricted thermal conductivity path between the metal shell of the high-current connector and the contact area; The thermal characteristics modeling module collects thermal status information of the high-current connector during operation when the heat conduction path is restricted. Combined with the internal structure of the high-current connector, it establishes a structural thermal distribution model to characterize the process of heat conduction from the contact area to the metal shell; Deviation assessment module, based on the established structural thermal distribution model and the collected thermal state information, evaluates the degree of thermal information collection deviation under the condition of limited heat conduction path; The temperature control decision module determines whether temperature control should be performed based on the evaluation results and executes the corresponding temperature control measures based on the judgment results; The response optimization module continuously optimizes the generation mechanism of evaluation results based on the adaptation between the evaluation results and the temperature control operation to enhance the dynamic response capability of the temperature control processing.

[0066] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0067] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0068] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0069] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0070] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0071] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0072] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0073] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A high current connector temperature control method based on temperature rise management, characterized in that: The specific steps include: Detect the current transmission status of high-current connectors during operation to determine whether they are continuously carrying high current; When the high-current connector is in continuous high-current operation, obtain the structural parameters of the high-current connector to determine whether there is a restricted heat conduction path between the metal shell of the high-current connector and the contact area; In the presence of a restricted heat conduction path, the thermal state information of the high-current connector during operation is collected. Combined with the internal structural configuration of the high-current connector, a structural thermal distribution model is established to characterize the heat conduction process from the contact area to the metal shell. Based on the established structural thermal distribution model and the collected thermal state information, the degree of thermal information collection deviation is evaluated when the heat conduction path is restricted; Based on the evaluation results, determine whether temperature control should be performed, and implement corresponding temperature control measures based on the judgment results; Based on the compatibility between the evaluation results and the temperature control operations, the generation mechanism of the evaluation results is continuously optimized to enhance the dynamic response capability of the temperature control processing.

2. The high current connector temperature control method based on temperature rise management according to claim 1, characterized in that: When the high-current connector is in continuous high-current operation, obtain the structural parameters of the high-current connector and determine whether there is a restricted heat conduction path between the metal shell of the high-current connector and the contact area. Specifically: When the high-current connector is in continuous high-current operation, the structural parameters of the high-current connector are obtained, including the structural distance between the metal shell and the contact area of ​​the high-current connector, the thermal conductivity of the materials included in the thermal path, and the spatial distribution characteristics of the insulation barrier layer; When the structural distance exceeds the preset critical length of thermal conduction, the thermal path contains a material segment with thermal conductivity lower than the set thermal conductivity value, and there are also continuously arranged insulating barrier layer segments, it is determined that the metal shell of the high-current connector has a structurally restricted thermal path between it and the contact area.

3. The high current connector temperature control method based on temperature rise management according to claim 2, characterized in that: In the presence of a restricted heat conduction path, the thermal state information of the high-current connector during operation is collected. Combined with the internal structural configuration of the high-current connector, a structural thermal distribution model is established to characterize the heat conduction process from the contact area to the metal shell. Specifically: In the case of limited heat conduction paths, collect thermal status information of high-current connectors during operation, including surface temperature data of the metal shell and current-carrying thermal performance parameters generated under operating current; Combined with the internal structural configuration of the high-current connector, the contact area is taken as the starting point of the heat source. The spatial arrangement relationship, material thermal conductivity, structural dimension information and coverage of the insulation barrier layer of each structural segment are extracted in sequence according to the heat conduction path. A corresponding structural thermal distribution model is established to characterize the thermal energy distribution trend, energy attenuation process and spatial position of the obstructed part in the heat conduction path from the contact area to the outside of the metal shell.

4. The high current connector temperature control method based on temperature rise management according to claim 3, characterized in that: Based on the established structural thermal distribution model and the collected thermal state information, the degree of thermal information collection deviation under the condition of limited heat conduction path is evaluated. The specific steps include: Extract the structural heat conduction configuration information from the established structural heat distribution model, extract the external thermal response dynamic information from the collected thermal state information, and perform normalization processing after extraction; Based on the normalized structural heat conduction configuration information and external thermal response dynamic information, the structural thermal response deviation coefficient and thermal load perception hysteresis index are generated respectively. Based on the generated structural thermal response deviation coefficient and thermal load perception hysteresis index, the acquisition deviation index is generated through weighted summation; A preset acquisition deviation index threshold range is determined, and after determination, it is compared with the generated acquisition deviation index, and the degree of thermal information acquisition deviation under the condition of limited heat conduction path is evaluated based on the comparison result.

5. The high current connector temperature control method based on temperature rise management according to claim 4, characterized in that: The logic for obtaining the structural thermal response deviation coefficient is as follows: The structural heat conduction configuration information is extracted from the established structural heat distribution model, specifically including the theoretical temperature value of each node of the heat conduction path and the physical length of the heat conduction path. These two types of data are divided by their corresponding preset maximum values ​​to obtain the normalized theoretical temperature value of each node of the heat conduction path and the physical length of the heat conduction path, and are calibrated as and , represents the normalized heat conduction path The theoretical temperature value of each node, represents the normalized physical length of the heat conduction path, , is a positive integer; the external thermal response dynamic information is extracted from the collected thermal state information, specifically including the sensor measured temperature value at each node of the corresponding heat conduction path, and divided by the corresponding preset maximum value to obtain the normalized sensor measured temperature value at each node of the corresponding heat conduction path, and calibrated as , Represents the normalized corresponding heat conduction path The actual temperature value measured by the sensor at each node; Calculate the structural thermal response deviation coefficient. The specific calculation formula is as follows: Where, is the structural thermal response deviation coefficient.

6. The high current connector temperature control method based on temperature rise management according to claim 5, characterized in that: The logic for obtaining the thermal load perception hysteresis index is as follows: The external thermal response dynamic information is extracted from the collected thermal state information, specifically including two types of data: the theoretical thermal power generated by the large current carrier per unit time and the temperature rise rate of the metal shell surface per unit time. These two types of data are divided by their corresponding preset maximum values ​​to obtain the normalized theoretical thermal power generated by the large current carrier per unit time and the temperature rise rate of the metal shell surface per unit time, and are calibrated as and , It represents the normalized theoretical heat power generated by the large current carrier per unit time. It represents the normalized rate of temperature rise per unit time on the surface of the metal shell; Calculate the thermal load perception hysteresis index. The specific calculation formula is as follows: Where, is the heat load perception hysteresis index.

7. The high current connector temperature control method based on temperature rise management according to claim 6, characterized in that: Based on the deviation coefficient of thermal response of the generated structure and thermal load perception hysteresis index , the acquisition deviation index is generated by weighted summation. The specific calculation formula is as follows: Where, is the acquisition deviation index, and are the structural thermal response deviation coefficients and thermal load perception hysteresis index The non-zero weight coefficient of .

8. The high current connector temperature control method based on temperature rise management according to claim 7, characterized in that: Determine the pre-set acquisition deviation index threshold range , and after determination, the generated acquisition deviation index A comparison was performed and the degree of thermal information collection deviation under the condition of limited heat conduction path was evaluated based on the comparison results. The specific comparison analysis is as follows: like ,The deviation degree of thermal information collection under the condition of ,limited heat conduction path is low deviation degree; like ,The degree of thermal information collection deviation under the condition of ,limited heat conduction path is medium in degree; like ,The degree of thermal information collection deviation under the condition of ,limited heat conduction path is severe deviation.

9. The high current connector temperature control method based on temperature rise management according to claim 8, characterized in that: Based on the evaluation results, determine whether temperature control should be performed and take corresponding temperature control measures based on the judgment results. Specifically: When the evaluation result shows a low deviation, it is determined that no temperature control is required, and the current operating state of the high-current connector remains unchanged; If the evaluation result shows a medium deviation, it is determined that temperature control warning processing is required. The implemented temperature control processing measures include limiting the current intensity within the set pre-downshift range and triggering the temperature rise risk warning instruction; When the evaluation result is a serious deviation, it is determined that forced temperature control must be performed. The temperature control measures implemented include starting the forced cooling device and cutting off the current supply to the high-load channel to reduce the temperature of the contact area and prevent further thermal runaway.

10. A high current connector based on temperature rise management, used to implement the high current connector temperature control method based on temperature rise management as described in any one of claims 1 to 9, characterized in that: It includes high current identification module, thermal conductivity constraint judgment module, thermal characteristic modeling module, deviation evaluation module, temperature control decision module and response optimization module; The high current identification module detects the current transmission status of the high current connector during operation and determines whether it is continuously carrying high current; The thermal conductivity constraint determination module obtains the structural parameters of the high-current connector when the high-current connector is continuously carrying high current, and determines whether there is a structurally restricted thermal conductivity path between the metal shell of the high-current connector and the contact area; The thermal characteristics modeling module collects thermal status information of the high-current connector during operation when the heat conduction path is restricted. Combined with the internal structure of the high-current connector, it establishes a structural thermal distribution model to characterize the process of heat conduction from the contact area to the metal shell; Deviation assessment module, based on the established structural thermal distribution model and the collected thermal state information, evaluates the degree of thermal information collection deviation under the condition of limited heat conduction path; The temperature control decision module determines whether temperature control should be performed based on the evaluation results and executes the corresponding temperature control measures based on the judgment results; The response optimization module continuously optimizes the generation mechanism of evaluation results based on the adaptation between the evaluation results and the temperature control operation to enhance the dynamic response capability of the temperature control processing.

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