Automobile sensor temperature control detection system based on internet of things technology

Abstract

The application discloses an automobile sensor temperature control detection system based on Internet of Things technology and relates to the technical field of automobile sensor temperature control detection, solves the technical problem that the prior art cannot analyze temperature control detection and cannot avoid the deviation of sensor detection caused by low temperature control efficiency, specifically, different types of sensors are subjected to temperature control detection analysis, the running efficiency of sensors at the detection position in the current automobile temperature control area is inferred through environment temperature analysis, deviation of sensor detection caused by low temperature control efficiency is avoided, and therefore, the automobile running detection efficiency can be improved, the detection running stability of sensors at each part can be ensured, and the automobile running detection stability is further enhanced.

Description

Technical Field

[0001] This invention relates to the field of automotive sensor temperature control and detection technology, specifically to an automotive sensor temperature control and detection system based on Internet of Things (IoT) technology. Background Technology

[0002] Automotive sensors are an important component of automotive electronic control systems, used to monitor and transmit various information during vehicle operation. Temperature control detection of automotive sensors is a crucial step in ensuring the normal operation and performance optimization of a vehicle. In automobiles, some sensors are highly sensitive to temperature, and their performance may be affected by temperature changes; therefore, temperature control detection is of paramount importance.

[0003] For example, the patent with announcement number CN113022308A discloses an electric vehicle thermal runaway early warning system, control method and electric vehicle. The optical fiber is set close to the outer surface of the battery module or cell, or the optical fiber is at least partially in contact with the outer surface of the battery module or cell. The input end of the optical fiber is connected to the light source transmitter and the output end of the optical fiber is connected to the light source receiver. It can accurately monitor the cell temperature and provide early warning before the thermal runaway of the electric vehicle spreads, thus protecting personal and property safety.

[0004] However, in the existing technology, automotive sensors cannot be evaluated and analyzed according to different detection tasks of various parts, and the importance of the current sensors cannot be inferred. As a result, it is impossible to combine the analysis of the degree of temperature influence to improve the accuracy of temperature control detection. In addition, it is impossible to analyze temperature control detection, and it is impossible to avoid the deviation of sensor detection caused by inefficient temperature control.

[0005] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0006] The purpose of this invention is to solve the problems mentioned above by proposing an automotive sensor temperature control and detection system based on Internet of Things (IoT) technology.

[0007] The objective of this invention can be achieved through the following technical solution: an automotive sensor temperature control and detection system based on Internet of Things (IoT) technology, comprising a temperature control and detection platform, wherein the temperature control and detection platform has communication connections to:

[0008] The location-based evaluation and analysis unit is used to mark the automotive parts that are subjected to temperature control detection as temperature control areas, acquire the sensors distributed within the temperature control areas and mark the location of each sensor as a detection location, acquire location-based evaluation and analysis information, and substitute it into the formula to obtain the evaluation and analysis coefficient of the sensor corresponding to the detection location within the automotive temperature control area. Based on the comparison of the evaluation and analysis coefficients, the sensors are divided into important high-impact ends and unimportant low-impact ends.

[0009] The temperature control detection and analysis unit is used to collect temperature rise parameters and temperature control parameters, and divide the current temperature control zone operating temperature environment into high-intensity temperature environment and low-intensity temperature environment based on parameter comparison. It also collects high-impact information and non-low-impact information based on different types of operating temperature environments, analyzes the information to generate different types of signals and sends them to the temperature control detection platform.

[0010] The temperature influence analysis unit is used to analyze the temperature influence of the temperature control detection process in the temperature control area.

[0011] As a preferred embodiment of the present invention, the location-based evaluation and analysis information includes the maximum numerical deviation of the same detection parameter at the detection location within the temperature control area under different operating durations during vehicle operation, the fluctuation of the numerical deviation of the corresponding detection parameter at the same detection location within the temperature control area under different ambient temperatures, and the overlap between the cumulative time period during which any detection parameter at the detection location within the temperature control area is not at the set parameter threshold and the vehicle operation and maintenance period.

[0012] If the evaluation analysis coefficient of the sensor corresponding to the detection position within the vehicle's temperature control area exceeds the evaluation analysis coefficient threshold, the corresponding sensor will be marked as an important high-impact end; if the evaluation analysis coefficient of the sensor corresponding to the detection position within the vehicle's temperature control area does not exceed the evaluation analysis coefficient threshold, the corresponding sensor will be marked as a non-important low-impact end.

[0013] In a preferred embodiment of the present invention, the temperature rise parameter and the temperature control parameter are respectively the range of the continuous increase of the peak value of the real-time uncontrolled temperature value in the temperature control zone during the operation of the vehicle, and the deviation frequency of the actual time taken to control the real-time uncontrolled temperature value to the set temperature range during the continuous increase of the peak value and the set time.

[0014] In a preferred embodiment of the present invention, if the temperature rise parameter exceeds the threshold value for the continuous increase span of the peak value, or the temperature control parameter exceeds the threshold value for the fluctuation frequency of the time-consuming deviation, the operating temperature environment of the current temperature control area is set to a high-intensity temperature environment; if the temperature rise parameter does not exceed the threshold value for the continuous increase span of the peak value, and the temperature control parameter does not exceed the threshold value for the fluctuation frequency of the time-consuming deviation, the operating temperature environment of the current temperature control area is set to a low-intensity temperature environment.

[0015] In a preferred embodiment of the present invention, the high-impact information and the low-impact information are respectively the shortening frequency of the adjacent floating interval of the detection parameters of the important high-impact end in the temperature control area during the current vehicle operation, and the peak value of the maximum span of the adjacent detection time corresponding to the detection parameters of the non-important low-impact end in the temperature control area.

[0016] In a preferred embodiment of the present invention, if the high-intensity impact information exceeds the shortening frequency threshold, or the non-low-intensity impact information exceeds the peak value threshold of the maximum floating span, the current temperature control detection and analysis is determined to be abnormal. If the current temperature environment is a high-intensity temperature environment, an environmental alarm signal is generated; if the current temperature environment is a low-intensity temperature environment, an equipment alarm signal is generated.

[0017] If the high-intensity impact information does not exceed the shortening frequency threshold, and the non-low-intensity impact information does not exceed the peak value threshold of the maximum fluctuation span, then the current temperature control detection and analysis is judged to be normal. If the current temperature environment is a high-intensity temperature environment, a safety signal is generated; if the current temperature environment is a low-intensity temperature environment, a warning signal is generated.

[0018] As a preferred embodiment of the present invention, the temperature effect analysis process is as follows:

[0019] The temperature control detection period in the temperature control area is analyzed. The temperature control detection period is taken as the later period, and a period of the same duration as the temperature control detection period is collected and marked as the earlier period. The influence analysis period of the temperature control area is constructed by the two periods. The detection parameter value of any detection position in the temperature control area is used as the reference parameter for the influence analysis.

[0020] In a preferred embodiment of the present invention, the fluctuation trend of the influence analysis reference parameter corresponding to the same detection position in the first and second periods is obtained, and the two fluctuation trends are compared. If the fluctuation trend of the influence analysis reference parameter in the first period and the fluctuation trend of the influence analysis reference parameter in the second period are connected, a normal temperature influence signal is generated, and the temperature control detection platform continues to execute the current temperature control detection.

[0021] If the fluctuation trend of the reference parameter for the impact analysis of the preceding period is not connected to the fluctuation trend of the reference parameter for the impact analysis of the following period, then the temperature impact of the preceding period in the current temperature control area is abnormal. The temperature control detection platform will suspend the temperature control detection of the current temperature control area, while controlling the current vehicle operation and detecting and regulating the real-time temperature environment of the temperature control area.

[0022] As a preferred embodiment of the present invention, the two cases of connected trends are as follows: the two trends are in the same trend, and the floating spans corresponding to the increasing or decreasing trends are in the same range; the two trends are in the same trend floating cycle, and the floating peaks and troughs of the two trends are both in the set range within the reciprocating floating cycle, and the floating spans are also in the same range.

[0023] Compared with the prior art, the beneficial effects of the present invention are:

[0024] 1. In this invention, the sensors in different parts of the car are evaluated and analyzed. Based on the sensors set in each part of the car, the importance of each sensor to the car detection is inferred. At the same time, the different effects of temperature on each sensor can be inferred based on the operation evaluation and analysis, so as to accurately perform temperature control detection.

[0025] 2. In this invention, temperature control detection and analysis are performed on different types of sensors. By analyzing the ambient temperature, the operating efficiency of the sensor at the detection position in the current temperature control area of ​​the car is inferred, avoiding the deviation of sensor detection caused by inefficient temperature control. This can help improve the detection efficiency of the car operation and ensure the detection and operation stability of the sensors in various parts, further enhancing the stability of the car operation and detection.

[0026] 3. In this invention, temperature influence analysis is performed on the temperature control detection process in the temperature control area to infer whether there is a temperature influence on the sensor during the current temperature control detection stage. This avoids affecting the real-time detection efficiency of the sensor during the current cumulative running period, which would cause inaccurate detection in the temperature control area. At the same time, the temperature influence analysis can detect the sensor's operating efficiency in real time and monitor the impact of temperature on the sensor, which is beneficial to the sensor's operating detection efficiency. Attached Figure Description

[0027] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0028] Figure 1 This is a principle block diagram of Embodiment 1 of the present invention;

[0029] Figure 2 This is a principle block diagram of Embodiment 2 of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0032] Example 1: This example uses IoT data collection to perform temperature control detection on automotive sensors to ensure their operational efficiency. Please refer to [link / reference]. Figure 1 As shown, the automotive sensor temperature control and detection system based on Internet of Things technology includes a temperature control and detection platform, wherein the temperature control and detection platform is communicatively connected to a location evaluation and analysis unit, a temperature control and detection analysis unit, and a temperature influence analysis unit.

[0033] The temperature control detection platform generates a location-based evaluation and analysis signal and sends it to the location-based evaluation and analysis unit. After receiving the location-based evaluation and analysis signal, the location-based evaluation and analysis unit evaluates and analyzes the automotive sensors in different parts. Based on the sensor settings in each part of the vehicle, it infers the importance of each sensor to the vehicle detection. At the same time, it can infer the different effects of temperature on each sensor based on the operational evaluation and analysis, so as to accurately perform temperature control detection.

[0034] The vehicle parts subjected to temperature control testing are marked as temperature control areas. Sensors distributed within the temperature control areas are acquired, and the locations of each sensor are marked as detection positions. The maximum numerical deviation of the same detection parameter at the detection position within the temperature control area is collected under different operating durations during vehicle operation. At the same time, the fluctuation of the numerical deviation of the corresponding detection parameter at the same detection position within the temperature control area under different ambient temperatures is also acquired. The maximum numerical deviation of the same detection parameter at the detection position within the temperature control area under different operating durations during vehicle operation and the fluctuation of the numerical deviation of the corresponding detection parameter at the same detection position within the temperature control area under different ambient temperatures are marked as SPC and PCF, respectively.

[0035] The system collects the cumulative time period during which any detection parameter at a temperature control location within the vehicle's operating area is not at the set parameter threshold, and the overlap time between this period and the vehicle's maintenance and repair period. The overlap time between this cumulative time period and the vehicle's maintenance and repair period is then marked as CDS.

[0036] The collected parameters are uniformly labeled as location-based evaluation and analysis information, and substituted into the formula to obtain the evaluation and analysis coefficient XS of the sensor corresponding to the detection location within the vehicle's temperature control area. The formula is as follows:

[0037] Among them, bhg1, bhg2 and bhg3 are respectively the maximum numerical deviation of the same detection parameter at the detection location, the fluctuation of the numerical deviation of the corresponding detection parameter at the same detection location, and the preset ratio coefficient of the overlap between the cumulative time period and the vehicle operation and maintenance time period, which are used to perform dimensionless processing on the collected parameters.

[0038] The evaluation analysis coefficient XS of the sensor corresponding to the detection position within the vehicle's temperature control area is compared with the evaluation analysis coefficient threshold:

[0039] If the evaluation analysis coefficient XS of the sensor corresponding to the detection position in the vehicle temperature control area exceeds the evaluation analysis coefficient threshold, the sensor evaluation analysis of the corresponding detection position in the vehicle temperature control area is determined to be abnormal, and the corresponding sensor is marked as an important high-impact end.

[0040] If the evaluation analysis coefficient XS of the sensor corresponding to the detection position in the vehicle temperature control area does not exceed the evaluation analysis coefficient threshold, it is determined that the sensor evaluation analysis of the corresponding detection position in the vehicle temperature control area is normal, and the corresponding sensor is marked as a non-important low-impact end.

[0041] After classifying each detection location into two types, the corresponding type is sent to the temperature control detection platform. At the same time, a temperature control detection analysis signal is generated and sent to the temperature control detection analysis unit. After receiving the temperature control detection analysis signal, the temperature control detection analysis unit performs temperature control detection analysis on different types of sensors. By analyzing the ambient temperature, it infers the sensor operating efficiency at the detection location in the current vehicle temperature control area, avoiding sensor detection deviations caused by inefficient temperature control. Therefore, it can help improve the vehicle operation detection efficiency, ensure the detection and operation stability of sensors in various parts, and further enhance the vehicle operation detection stability.

[0042] The system acquires temperature values ​​exceeding the set temperature range threshold within the temperature control area and marks these temperatures as the temperature to be controlled. It also collects the span of the real-time peak increase of the temperature to be controlled within the temperature control area during vehicle operation, and the deviation frequency of the actual time taken to bring the real-time temperature to the set temperature range during the peak increase. These values ​​are then marked as temperature rise parameters and temperature control parameters, respectively, and compared with the threshold values ​​for the peak increase span and the deviation frequency of the time taken to bring the real-time temperature to the set temperature range.

[0043] If the peak value of the real-time temperature to be controlled in the temperature control zone continues to increase and the range exceeds the threshold value for the continuous increase of the peak value, or if the actual time taken to control the real-time temperature to be controlled within the set temperature range during the continuous increase of the peak value exceeds the set time deviation frequency threshold value, then the operating temperature environment of the current temperature control zone will be set to a high-intensity temperature environment.

[0044] If the peak value of the real-time temperature to be controlled in the temperature control zone during the operation of the vehicle does not exceed the threshold value for the continuous increase of the peak value during the continuous increase of the peak value, and the deviation frequency between the actual time taken to control the real-time temperature to be controlled within the set temperature range and the set time during the continuous increase of the peak value does not exceed the time deviation frequency threshold value, then the operating temperature environment of the current temperature control zone will be set to a low-intensity temperature environment.

[0045] The shortening frequency of adjacent floating intervals of detection parameters at important high-impact ends within the temperature control zone during current vehicle operation is obtained. Simultaneously, the maximum span peak value of adjacent floating intervals of detection parameters at non-important low-impact ends within the temperature control zone is obtained. The shortening frequency of adjacent floating intervals of detection parameters at important high-impact ends within the temperature control zone and the maximum span peak value of adjacent floating intervals of detection parameters at non-important low-impact ends within the temperature control zone are marked as high-impact information and non-low-impact information, respectively, and compared with shortening frequency thresholds and maximum floating interval peak value thresholds, respectively.

[0046] If, during the current vehicle operation, the frequency of shortening of adjacent fluctuation intervals of detection parameters at critical high-impact points within the temperature control area exceeds a shortening frequency threshold, or if the maximum span peak value of adjacent fluctuations of detection parameters at non-critical low-impact points within the temperature control area exceeds a maximum span peak value threshold, then the current temperature control detection analysis is deemed abnormal. If the current temperature environment is a high-intensity temperature environment, an environmental alarm signal is generated and sent to the temperature control detection platform. Upon receiving the environmental alarm signal, the temperature control detection platform controls the ambient temperature of the sensor at the current detection location and, if necessary, adjusts the vehicle's operating time. If the current temperature environment is a low-intensity temperature environment, an equipment alarm signal is generated and sent to the temperature control detection platform. Upon receiving the equipment alarm signal, the temperature control detection platform performs performance testing on the sensor at the current detection location and puts it into testing use after passing the test.

[0047] If, during the current vehicle operation, the shortening frequency of adjacent fluctuation intervals of the detection parameters at important high-impact points within the temperature control area does not exceed the shortening frequency threshold, and the maximum span peak value of adjacent fluctuations of the detection parameters at non-important low-impact points within the temperature control area does not exceed the maximum span peak value threshold, then the current temperature control detection analysis is considered normal. If the current temperature environment is a high-intensity temperature environment, a safety signal is generated and sent to the temperature control detection platform; if the current temperature environment is a low-intensity temperature environment, a warning signal is generated and sent to the temperature control detection platform. Upon receiving the warning signal, the temperature control detection platform implements temperature environment control in the temperature control area to issue a warning. Based on the real-time temperature fluctuation trend combined with the temperature control efficiency fluctuation trend, it simultaneously analyzes and performs targeted environmental control based on the real-time analysis results.

[0048] After the temperature control detection platform completes temperature control detection and analysis and receives safety signals, it generates a temperature influence analysis signal and sends it to the temperature influence analysis unit. Upon receiving the temperature influence analysis signal, the temperature influence analysis unit performs temperature influence analysis on the temperature control detection process in the temperature control area, infers whether there is a temperature influence on the sensor during the current temperature control detection stage, avoids affecting the real-time detection efficiency of the sensor during the current cumulative running period, and prevents inaccurate detection in the temperature control area. At the same time, the temperature influence analysis can detect the sensor's operating efficiency in real time and monitor the impact of temperature on the sensor, which is beneficial to the sensor's operating detection efficiency.

[0049] The temperature control detection period in the temperature control area is analyzed. The temperature control detection period is taken as the later period, and a period of the same duration as the temperature control detection period is collected and marked as the earlier period. The influence analysis period of the temperature control area is constructed by the two periods. The detection parameter value of any detection position in the temperature control area is used as the reference parameter for the influence analysis.

[0050] The fluctuation trend of the reference parameter for the influence analysis of the same detection position in the preceding and following time periods is obtained, and the two fluctuation trends are compared. If the fluctuation trend of the reference parameter for the influence analysis of the preceding time period is a connected trend, then the temperature influence of the current temperature control area is normal. A normal temperature influence signal is generated and sent to the temperature control detection platform, and the temperature control detection platform continues to perform the current temperature control detection.

[0051] Connected trends refer to two trends that are in the same trend and whose corresponding floating spans are within the same range, whether they are increasing or decreasing. This also includes two trends that are in the same trend floating cycle, where the peak and trough values ​​of the two trends are within a set range and the floating spans are also within the same range. Both of these situations are considered connected trends.

[0052] If the fluctuation trend of the reference parameter for the impact analysis of the preceding period is not connected to the fluctuation trend of the reference parameter for the impact analysis of the following period, then the temperature impact of the preceding period in the current temperature control area is abnormal. The temperature control detection in the current temperature control area is suspended, and the current vehicle operation is controlled while the real-time temperature environment of the temperature control area is detected and regulated.

[0053] Example 2: The previous example used automotive sensors for temperature control detection. This example, building upon the previous one, predicts the temperature control detection cycle to further improve temperature control efficiency. Please refer to [link / reference]. Figure 2 As shown, the temperature control detection platform has a detection cycle prediction unit connected to its communication network.

[0054] The temperature control detection platform generates a detection cycle prediction signal and sends it to the detection cycle prediction unit. After receiving the detection cycle prediction signal, the detection cycle prediction unit predicts the temperature control detection cycle of the temperature control area and infers whether the current temperature control detection cycle meets the temperature control detection efficiency. This avoids the situation where temperature control detection anomalies are all outside the temperature control detection cycle, causing a delay in the detection time of temperature-affected faults, making it impossible to perform temperature control detection in a timely manner, and reducing the temperature control execution efficiency.

[0055] The method obtains the percentage of times when the peak fluctuation of the detection parameter increases versus times when the detection parameter remains unchanged at any detection location within the current detection cycle. It also obtains the ratio of the duration of the rise in the detection parameter acquisition error rate to the duration of the decrease in the same error rate at any detection location within the current detection cycle. Finally, it compares this percentage, along with the ratio of the duration of the rise in the detection parameter acquisition error rate to the duration of the decrease in the same error rate at any detection location within the current detection cycle, with the threshold ranges for the percentage of times and the threshold range for the duration ratio, respectively.

[0056] If, within the current detection cycle, the ratio of the number of times when the peak fluctuation of the detection parameter at any detection location in the temperature control area increases to the number of times when the detection parameter does not fluctuate is not within the threshold range, or if, within the current detection cycle, the ratio of the duration of the increase in the error rate of the detection parameter at any detection location in the temperature control area to the duration of the decrease in the same error rate is not within the threshold range, then the current detection cycle is determined to be abnormal. A cycle deviation signal is generated and sent to the temperature control detection platform. After receiving the cycle deviation signal, if the temperature control detection platform receives the signal and more than one parameter exceeds the corresponding range in either the percentage of times or the duration ratio, then the corresponding detection cycle is shortened to increase the detection frequency; otherwise, the corresponding detection cycle is extended to control detection costs while meeting detection requirements.

[0057] If the percentage of times when the peak value of the detection parameter at any detection location in the temperature control area increases is within the threshold range of the percentage of times the detection parameter does not fluctuate within the current detection cycle, and the ratio of the duration of the rise in the acquisition error rate of the detection parameter at any detection location in the temperature control area to the duration of the fall in the same error rate is within the threshold range of the duration ratio, then the current detection cycle is determined to be normal, a cycle qualified signal is generated, and the cycle qualified signal is sent to the temperature control detection platform.

[0058] In use, the present invention involves a location-based evaluation and analysis unit that marks the vehicle parts subject to temperature control detection as temperature control areas, acquires the sensors distributed within these areas, marks the locations of each sensor as detection positions, obtains location-based evaluation and analysis information, and substitutes this information into a formula to obtain the evaluation and analysis coefficients for the sensors corresponding to the detection positions within the vehicle's temperature control area. Based on the comparison of these evaluation and analysis coefficients, the sensors are categorized into important high-impact ends and unimportant low-impact ends. The temperature control detection and analysis unit collects temperature rise parameters and temperature control parameters, and based on parameter comparison, categorizes the current operating temperature environment of the temperature control area into high-intensity temperature environments and low-intensity temperature environments. It also collects important high-impact information and unimportant low-impact information based on different types of operating temperature environments, analyzes this information to generate different types of signals, and sends them to the temperature control detection platform. The temperature impact analysis unit performs temperature impact analysis on the temperature control detection process within the temperature control area.

[0059] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

[0060] The above formulas are all derived from software simulations using a large amount of data, and are selected based on values ​​that are close to the actual values. The coefficients in the formulas are set by those skilled in the art based on the actual situation; for example: Formula Multiple sets of sample data were collected by those skilled in the art, and corresponding purification optimization coefficients were set for each set of sample data. The set purification optimization coefficients and the collected sample data were substituted into the formulas, and any two formulas formed a system of two linear equations. The calculated coefficients were screened and averaged to obtain values ​​of 2.49, 2.21, and 2.1 for bhg1, bhg2, and bhg3, respectively. The size of the coefficients is a specific value obtained by quantifying each parameter to facilitate subsequent comparison. The size of the coefficients depends on the amount of sample data and the corresponding evaluation and analysis coefficients initially set by those skilled in the art for each set of sample data. As long as the proportional relationship between the parameters and the quantified values ​​is not affected, it is acceptable.

Claims

1. An automotive sensor-based temperature control and detection system based on Internet of Things (IoT) technology, characterized in that, This includes a temperature control detection platform, whose communication connections include: The location-based evaluation and analysis unit is used to mark the automotive parts that are subjected to temperature control detection as temperature control areas, acquire the sensors distributed within the temperature control areas and mark the location of each sensor as a detection location, acquire location-based evaluation and analysis information, and substitute it into the formula to obtain the evaluation and analysis coefficient of the sensor corresponding to the detection location within the automotive temperature control area. Based on the comparison of the evaluation and analysis coefficients, the sensors are divided into important high-impact ends and unimportant low-impact ends. The temperature control detection and analysis unit is used to collect temperature rise parameters and temperature control parameters, and divide the current temperature control zone operating temperature environment into high-intensity temperature environment and low-intensity temperature environment based on parameter comparison. It also collects high-impact information and non-low-impact information based on different types of operating temperature environments, analyzes the information to generate different types of signals and sends them to the temperature control detection platform. The temperature influence analysis unit is used to perform temperature influence analysis on the temperature control detection process in the temperature control area. The location-based assessment and analysis information includes the maximum numerical deviation of the same detection parameter at the detection location within the temperature control area under different operating durations during vehicle operation, the fluctuation of the numerical deviation of the corresponding detection parameter at the same detection location within the temperature control area under different ambient temperatures, and the overlap between the cumulative time period during which any detection parameter at the detection location within the temperature control area is not at the set parameter threshold and the vehicle operation and maintenance period. If the evaluation analysis coefficient of the sensor corresponding to the detection position within the vehicle's temperature control area exceeds the evaluation analysis coefficient threshold, the corresponding sensor will be marked as an important high-impact end; if the evaluation analysis coefficient of the sensor corresponding to the detection position within the vehicle's temperature control area does not exceed the evaluation analysis coefficient threshold, the corresponding sensor will be marked as a non-important low-impact end. The temperature rise parameters and temperature control parameters collected are the range of the peak value of the real-time uncontrolled temperature in the temperature control zone during the operation of the vehicle, and the deviation frequency of the actual time taken to control the real-time uncontrolled temperature to the set temperature range during the continuous increase of the peak value. If the temperature rise parameter exceeds the threshold for the continuous increase span of the peak value, or the temperature control parameter exceeds the threshold for the fluctuation frequency of the time-consuming deviation, the operating temperature environment of the current temperature control zone will be set to a high-intensity temperature environment; if the temperature rise parameter does not exceed the threshold for the continuous increase span of the peak value, and the temperature control parameter does not exceed the threshold for the fluctuation frequency of the time-consuming deviation, the operating temperature environment of the current temperature control zone will be set to a low-intensity temperature environment.

2. The automotive sensor temperature control and detection system based on Internet of Things technology according to claim 1, characterized in that, The high-impact information and the low-impact information are respectively the shortening frequency of adjacent fluctuation intervals of the detection parameters at the important high-impact end in the temperature control area during the current vehicle operation, and the peak value of the maximum span of adjacent detection times corresponding to the detection parameters at the non-important low-impact end in the temperature control area.

3. The automotive sensor temperature control and detection system based on Internet of Things technology according to claim 2, characterized in that, If the high-intensity impact information exceeds the shortening frequency threshold, or the non-low-intensity impact information exceeds the peak value threshold of the maximum floating span, the current temperature control detection and analysis is judged to be abnormal. If the current temperature environment is a high-intensity temperature environment, an environmental alarm signal is generated; if the current temperature environment is a low-intensity temperature environment, an equipment alarm signal is generated. If the high-intensity impact information does not exceed the shortening frequency threshold, and the non-low-intensity impact information does not exceed the peak value threshold of the maximum fluctuation span, then the current temperature control detection and analysis is judged to be normal. If the current temperature environment is a high-intensity temperature environment, a safety signal is generated; if the current temperature environment is a low-intensity temperature environment, a warning signal is generated.

4. The automotive sensor temperature control and detection system based on Internet of Things technology according to claim 1, characterized in that, The temperature effect analysis process is as follows: The temperature control detection period in the temperature control area was analyzed. The temperature control detection period was taken as the later period, and a period of the same duration as the temperature control detection period was collected and marked as the earlier period. The impact analysis period of the temperature control area was constructed by using two time periods; The detection parameter values ​​at any detection location within the temperature control zone are used as reference parameters for the influence analysis.

5. The automotive sensor temperature control and detection system based on Internet of Things technology according to claim 4, characterized in that, The influence analysis reference parameter fluctuation trend of the same detection position in the preceding and following time periods is obtained, and the two fluctuation trends are compared. If the influence analysis reference parameter fluctuation trend of the preceding and following time periods is a connected trend, a normal temperature influence signal is generated, and the temperature control detection platform continues to execute the current temperature control detection. If the fluctuation trend of the reference parameter for the impact analysis of the preceding period is not connected to the fluctuation trend of the reference parameter for the impact analysis of the following period, then the temperature impact of the preceding period in the current temperature control area is abnormal. The temperature control detection platform will suspend the temperature control detection of the current temperature control area, while controlling the current vehicle operation and detecting and regulating the real-time temperature environment of the temperature control area.

6. The automotive sensor temperature control and detection system based on Internet of Things technology according to claim 5, characterized in that, The two scenarios for connected trends are as follows: 1) The two trends are in the same trend, and the corresponding floating spans of the increasing or decreasing trends are within the same range; 2) The two trends are in the same trend floating cycle, and the floating peaks and troughs of the two trends are within the set range within the cyclical floating cycle, and the floating spans are also within the same range.

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