Vehicle thermal management diagnosis method, device, equipment and medium

Abstract

The invention relates to the technical field of automobile thermal management, in particular to a vehicle thermal management diagnosis method, device and equipment and a medium. According to the method, the primary diagnosis value of the thermal management assembly in the current preset period is determined according to the collected thermal management index information, thermal management diagnosis is performed on the thermal management assembly according to the primary diagnosis value of the current preset period, and the diagnosis type of the thermal management assembly is obtained, so that the thermal management diagnosis abnormal assembly is determined; the thermal management diagnosis value of the vehicle is calculated according to the thermal management influence relation between the thermal management diagnosis abnormal components and the corresponding components, the thermal management components in the whole thermal management system are comprehensively considered, the precision of the thermal management diagnosis value is improved, the thermal management diagnosis level of the vehicle is determined according to the thermal management diagnosis value, and the vehicle thermal management diagnosis efficiency is improved. The thermal management diagnosis level of the vehicle is quantitatively evaluated, and a driver can conveniently know the severity of the thermal management problem of the vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of automotive thermal management, and particularly to a vehicle thermal management diagnosis method, device, equipment and medium. Background Art

[0002] With the rapid development of modern automotive technologies, the automotive thermal management system, as a key component to ensure the efficient and safe operation of vehicles, has become increasingly prominent in terms of its complexity and importance. The automotive thermal management system covers multiple key components such as battery packs, motors, electronic control systems, air conditioning systems, and reducer cooling systems. These components work together to maintain the temperature of the vehicle interior and key components within an appropriate range, thereby ensuring the power performance, economy, reliability, and comfort of the vehicle.

[0003] In recent years, with the rapid development of sensor technology and data processing technology, new possibilities have been provided for the intelligent diagnosis of automotive thermal management systems. By integrating various types of sensors, various parameters during the operation of the automotive thermal management system, such as temperature, pressure, and flow rate, can be collected in real time, providing rich data support for fault diagnosis. However, most of these technologies are limited to the diagnosis of single components or local systems, lacking the ability to comprehensively and deeply diagnose the entire thermal management system, resulting in relatively low diagnostic accuracy for the automotive thermal management system. Therefore, in the process of diagnosing the automotive thermal management system, how to improve the diagnostic accuracy has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the embodiments of the present invention provide a vehicle thermal management diagnosis method, device, equipment and medium, aiming to solve the problem of low diagnostic accuracy of the thermal management system during the diagnosis of the automotive thermal management system.

[0005] In a first aspect, the embodiments of the present invention provide a vehicle thermal management diagnosis method, including: For any thermal management component in the vehicle, collect the thermal management index information of each thermal management index of the thermal management component in the current preset period, and determine the primary diagnosis value of the thermal management component in the current preset period according to the thermal management index information of each thermal management index; Perform thermal management diagnosis on the thermal management component according to the primary diagnosis value to obtain the diagnosis type of the thermal management component, traverse all thermal management components, and obtain the diagnosis types corresponding to all thermal management components. The diagnosis type includes thermal management diagnosis abnormality; Take the thermal management component corresponding to the thermal management diagnosis abnormality as the thermal management diagnosis abnormal component, calculate the thermal management diagnosis value of the vehicle according to the thermal management diagnosis abnormal component and the preset thermal management relationship diagram, and determine the thermal management diagnosis level of the vehicle according to the thermal management diagnosis value.

[0006] In a second aspect, an embodiment of the present invention provides a vehicle thermal management diagnosis device, including: A primary thermal management diagnosis module, configured to collect thermal management index information of each thermal management index of any thermal management component in the vehicle during a current preset period, and determine a primary diagnosis value of the thermal management component during the current preset period according to the thermal management index information of each thermal management index; A thermal management component diagnosis module, configured to perform a thermal management diagnosis on the thermal management component according to the primary diagnosis value to obtain a diagnosis type of the thermal management component, traverse all thermal management components, and obtain the diagnosis types corresponding to all thermal management components, where the diagnosis type includes a thermal management diagnosis anomaly; A thermal management level diagnosis module, configured to use the thermal management component corresponding to the diagnosis type of thermal management diagnosis anomaly as a thermal management diagnosis anomaly component, calculate a thermal management diagnosis value of the vehicle according to the thermal management diagnosis anomaly component and a preset thermal management relationship diagram, and determine a thermal management diagnosis level of the vehicle according to the thermal management diagnosis value.

[0007] In a third aspect, an embodiment of the present invention provides a computer device, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the vehicle thermal management diagnosis method described in the first aspect is implemented.

[0008] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the vehicle thermal management diagnosis method described in the first aspect is implemented.

[0009] The beneficial effects of the present invention compared with the prior art are as follows: In the present invention, according to the collected thermal management index information, a primary diagnosis value of the thermal management component during the current preset period is determined. According to the primary diagnosis value during the current preset period, a thermal management diagnosis is performed on the thermal management component to obtain a diagnosis type of the thermal management component, so as to determine a thermal management diagnosis anomaly component. According to the thermal management diagnosis anomaly component and the thermal management influence relationship between corresponding components, a thermal management diagnosis value of the vehicle is calculated, comprehensively considering each thermal management component in the entire thermal management system, improving the accuracy of the thermal management diagnosis value. According to the thermal management diagnosis value, a thermal management diagnosis level of the vehicle is determined, quantitatively evaluating the thermal management diagnosis level of the vehicle, and facilitating the driver to understand the severity of the vehicle's thermal management problem. Description of the Drawings

[0010] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments of the present invention. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0011] Figure 1 It is a schematic flowchart of a vehicle thermal management diagnosis method provided in Embodiment 1 of the present invention; Figure 2 It is a structural block diagram of a vehicle thermal management diagnosis device provided in Embodiment 2 of the present invention; Figure 3 It is a schematic structural diagram of a computer device provided in Embodiment 3 of the present invention. Detailed implementation manners

[0012] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0013] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, systems, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0014] It should be understood that when used in the specification of the present invention and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0015] It should also be understood that the term "and / or" used in the specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0016] As used in the specification of the present invention and the appended claims, the term "if" may be construed as "when", "once", "in response to determining", or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be construed as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" depending on the context.

[0017] In addition, in the description of the specification of the present invention and the appended claims, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0018] The reference to "one embodiment" or "some embodiments" etc. described in the specification of the present invention means that a specific feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present invention. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0019] It should be understood that the magnitudes of the sequence numbers of the steps in the following embodiments do not mean the order of execution is prior or subsequent. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0020] In order to illustrate the technical solution of the present invention, the following specific embodiments are used for illustration.

[0021] See Figure 1 , which is a schematic flow chart of a vehicle thermal management diagnosis method provided by Embodiment 1 of the present invention. As Figure 1 shown, the vehicle thermal management diagnosis method may include the following steps.

[0022] S101: For any thermal management component in the vehicle, collect the thermal management index information of each thermal management index of the thermal management component in the current preset period, and determine the primary diagnosis value of the thermal management component in the current preset period according to the thermal management index information of each thermal management index.

[0023] In step S101, the thermal management component is a core technical module in new energy vehicles and industrial equipment for optimizing heat transfer and maintaining the operating temperature of components. Its design directly affects the performance, safety, and lifespan of the equipment. The preset period is a pre-set diagnostic period, the thermal management index is a key parameter used to quantify the thermal management component, different thermal management components include different thermal management indexes, the thermal management index information is the parameter value of the corresponding thermal management index, and the primary diagnostic value is the quantified value after diagnosing the thermal management component.

[0024] In this embodiment, the thermal management components in the vehicle include but are not limited to battery packs, motors, electronic control systems, air conditioning systems, reducer cooling systems, etc. For any thermal management component in the vehicle, the thermal management index information of each thermal management index of the thermal management component is collected in the current preset period. Among them, different thermal management components include different thermal management indexes. Taking the battery pack as an example, the thermal management indexes of the battery pack include but are not limited to the battery pack temperature index, the battery pack operating status index, and the battery pack cooling medium index. Taking the motor as an example, the thermal management indexes of the motor include but are not limited to the motor temperature index, the motor operating status index, and the motor cooling medium index. The thermal management index information of each thermal management index is collected through corresponding sensors.

[0025] It should be noted that the thermal management index information of each thermal management index in the current preset period can be the thermal management index information collected once in the current preset period, or it can be the thermal management index information obtained after processing the thermal management index information collected multiple times in the current preset period. This embodiment does not make a limitation.

[0026] According to the thermal management index information of each thermal management index, the primary diagnostic value of the thermal management component in the current preset period is determined. Among them, in this embodiment, when determining the primary diagnostic value of the thermal management component in the current preset period, the thermal management index information of each thermal management index is quantified to obtain a quantified value, where the quantified value is used to characterize the abnormal situation of the thermal management index in the current preset period.

[0027] It should be noted that when quantifying the thermal management index information of each thermal management index, it is quantified according to the normal situation of the thermal management index information. If the thermal management index information represents the normality of the thermal management index, the thermal management index information is quantified to a smaller value. If the thermal management index information represents the abnormality of the thermal management index, the thermal management index information is quantified to a larger value. That is, the larger the quantified value, the more abnormal the thermal management index is considered, and the smaller the quantified value, the more normal the thermal management index is considered.

[0028] For the battery pack working state index among the thermal management indexes of the battery pack, when quantifying the thermal management index information of the battery pack working state index, if the thermal management index information of the battery pack working state index is normal, the thermal management index information of the battery pack working state index is quantified to a smaller value; if the thermal management index information of the battery pack working state index is abnormal, the thermal management index information of the battery pack working state index is quantified to a larger value. Other methods can also be used for quantification, which is not limited in this embodiment.

[0029] After quantifying all the thermal management index information, perform normalization processing on the quantified values to obtain the normalized result. According to the normalized result, calculate the mean value of the thermal management index information of all thermal management indexes in the current preset period, and determine the mean value as the primary diagnosis value of the thermal management component in the current preset period.

[0030] In this embodiment, according to the thermal management index information of each thermal management index, determine the primary diagnosis value of the thermal management component in the current preset period. When diagnosing the thermal management component, take into account each thermal management index to improve the accuracy of diagnosing the thermal management component.

[0031] Optionally, determining the primary diagnosis value of the thermal management component in the current preset period according to the thermal management index information of each thermal management index includes: Divide the current preset period into N time periods, where N is an integer greater than zero; Obtain the thermal management index information corresponding to each time period of each thermal management index in the current preset period; According to the thermal management index information of each thermal management index in each time period, calculate the thermal management analysis value of the thermal management component corresponding to the time period; According to the thermal management analysis values of each time period, calculate the primary diagnosis value of the thermal management component in the current preset period.

[0032] In this embodiment, divide the current preset period into N time periods, where the duration of each time period is equal. According to the thermal management index information of each thermal management index of the thermal management component in the current preset period, determine the thermal management index information corresponding to each time period of each thermal management index in the current preset period, that is, collect the corresponding thermal management index information once for each time period.

[0033] According to the thermal management index information of each thermal management index in each time period, calculate the thermal management analysis value of the thermal management component corresponding to the time period, where the thermal management analysis value is the thermal management diagnosis value obtained by the thermal management component after comprehensively considering the thermal management index information of all thermal management indexes in each time period.

[0034] In this embodiment, the thermal management index information corresponding to all thermal management indexes in each time period is quantified to obtain a quantified time period value, where the quantified time period value is used to characterize the abnormal situation of the thermal management index in this time period.

[0035] It should be noted that when quantifying the thermal management index information of each thermal management index, quantification is performed according to the normal situation of the thermal management index information. If the thermal management index information represents the normality of the thermal management index, the thermal management index information is quantified to a smaller value. If the thermal management index information represents the abnormality of the thermal management index, the thermal management index information is quantified to a larger value. That is, the larger the quantified value, the more abnormal the thermal management index is considered, and the smaller the quantified value, the more normal the thermal management index is considered. That is, the larger the quantified time period value, the more abnormal the thermal management index is considered, and the smaller the quantified time period value, the more normal the thermal management index is considered.

[0036] For example, for the temperature index in the thermal management index of the battery pack, when quantifying the thermal management index information of the temperature index, when the thermal management index information of the battery pack temperature index is within the normal temperature range, the thermal management index information of the battery pack temperature index is quantified to a smaller value. When the thermal management index information of the battery pack temperature index is not within the normal temperature range, the thermal management index information of the battery pack temperature index is quantified to a larger value. Other methods can also be used for quantification, which is not limited in this embodiment.

[0037] The quantified time period values obtained after quantifying all thermal management index information are normalized to obtain a normalized result. According to the normalized result, the mean value of the thermal management index information of all thermal management indexes in the corresponding time period is calculated, and the corresponding mean value is determined as the thermal management analysis value of the thermal management component in the corresponding time period. The larger the thermal management analysis value, the more abnormal the heat pipe component is considered, and the smaller the thermal management analysis value, the more normal the heat pipe component is considered.

[0038] In this embodiment, according to the thermal management analysis value of each time period and the preset thermal management analysis threshold, the time period with the thermal management analysis value greater than the thermal management analysis threshold is an analysis special time period, where the analysis special time period is the time period when the corresponding thermal management component has an abnormality. The mean value of the thermal management analysis values in all analysis special time periods is calculated, and the corresponding mean value is determined as the primary diagnosis value of the thermal management component in the current preset cycle.

[0039] In this embodiment, the current preset period is divided into N time periods, the thermal management analysis value of the thermal management component in each time period is calculated, and according to the thermal management analysis value of each time period, the special analysis time periods are determined. The average value of the thermal management analysis values in all the special analysis time periods is calculated, and the thermal management analysis values in the normal time periods in the current preset period are not considered, so as to avoid the averaging of the thermal management analysis values in the normal time periods on the thermal management analysis values in the special analysis time periods, and improve the accuracy of the calculation of the primary diagnosis value.

[0040] Optionally, according to the thermal management index information of each thermal management index in each time period, the thermal management analysis value of the thermal management component in the corresponding time period is calculated, including: For any time period, according to the thermal management index information of each thermal management index in the corresponding time period and the preset thermal management index model, the thermal analysis value of each thermal management index is determined; According to the thermal analysis value of each thermal management index and the preset analysis threshold, the index type of each thermal management index is determined, and the index type includes out-of-bounds thermal index and in-bounds thermal index; According to the thermal analysis value of the thermal management index with the index type of out-of-bounds thermal index and the thermal analysis value of the thermal management index with the index type of in-bounds thermal index, the thermal management analysis value of the thermal management component in the corresponding time period is calculated.

[0041] In this embodiment, for any time period, according to the thermal management index information of each thermal management index in the corresponding time period and the preset thermal management index model, the thermal analysis value of each thermal management index is determined. Among them, each thermal management index corresponds to a thermal management index model, and the preset thermal management index model is a pre-trained neural network model. For any thermal management index, the training process of the neural network model is as follows: construct an initial neural network model and the time-period thermal management index information in multiple time periods corresponding to the thermal management index, and assign a thermal analysis value to each time-period thermal management index information as a label. Among them, the thermal analysis value is within a preset range. The larger the value of the thermal analysis value, the more abnormal the time-period thermal management index information of the thermal management index in the corresponding time period, and the smaller the value of the thermal analysis value, the more normal the time-period thermal management index information of the thermal management index in the corresponding time period. The time-period thermal management index information in multiple time periods is used as training data, and the training data is divided into a training set, a validation set and a test set. The initial neural network model is cross-trained according to the training set and the validation set to obtain a trained thermal management index model.

[0042] It should be noted that for different thermal management indicators, the construction method of the initial neural network model is the same. For example, for the temperature indicator of the battery pack, an initial neural network model is constructed. Temperature information of the temperature indicator in multiple time periods is collected, and a thermal analysis value is assigned to the temperature information. The value range of the thermal analysis value can be (1.01 - 1.99). The larger the thermal analysis value, the more abnormal the temperature information of the temperature indicator in that time period, and the smaller the thermal analysis value, the more normal the temperature information of the temperature indicator in that time period. The temperature information in multiple time periods is used as training data. 60% of the training data is used as the training set, 20% as the validation set, and 20% as the test set. The initial neural network model is cross-trained to obtain a trained thermal management indicator model corresponding to the battery pack temperature indicator. Similarly, thermal management indicator models corresponding to other thermal management indicators can be obtained.

[0043] After obtaining the trained thermal management indicator model, the thermal management indicator information corresponding to the time period of the thermal management indicator is input into the thermal management indicator model, and the corresponding thermal analysis value of the corresponding management indicator in that time period is output.

[0044] According to the thermal analysis value of each thermal management indicator and the preset analysis threshold, the thermal management indicator with a thermal analysis value greater than or equal to the preset analysis threshold is determined as an out-of-bounds thermal indicator, and the thermal management indicator with a value less than the preset analysis threshold is determined as an in-bounds thermal indicator. Among them, the preset analysis threshold can be set according to experience. All thermal management indicators are traversed in turn to obtain all out-of-bounds thermal indicators and all in-bounds thermal indicators. Calculate the mean value of the corresponding thermal analysis values among all out-of-bounds thermal indicators, and the mean value of the corresponding thermal analysis values among all in-bounds thermal indicators. Calculate the difference between the mean value of the corresponding thermal analysis values among all out-of-bounds thermal indicators and the mean value of the corresponding thermal analysis values among all in-bounds thermal indicators, and determine the corresponding difference as the analysis deviation value. Count the number of out-of-bounds thermal indicators and the number of in-bounds thermal indicators. Calculate the thermal management analysis value of the thermal management component corresponding to the time period according to the analysis deviation value, the number of out-of-bounds thermal indicators, and the number of in-bounds thermal indicators. The calculation formula is as follows: Among them, is the thermal management analysis value of the thermal management component corresponding to the time period, is the number of out-of-bounds thermal indicators, is the number of in-bounds thermal indicators, is the analysis deviation value.

[0045] In this embodiment, according to the thermal analysis values of each thermal management index, the thermal management indexes are divided into out-of-bounds thermal indexes and in-bounds thermal indexes. Among them, the out-of-bounds thermal indexes are thermal management indexes tending to be abnormal, and the in-bounds thermal indexes are thermal management indexes tending to be normal. According to the analysis deviation value, the number of out-of-bounds thermal indexes, and the number of in-bounds thermal indexes, the thermal management analysis value of the thermal management component in the corresponding time period is calculated, which characterizes the influence of the number of thermal management indexes tending to be abnormal and the number of thermal management indexes tending to be normal on the thermal management analysis value of the thermal management component. When the number of thermal management indexes tending to be normal increases, the thermal management analysis value decreases. When the number of thermal management indexes tending to be abnormal increases, the thermal management analysis value also increases, improving the calculation accuracy of the thermal management analysis value.

[0046] Optionally, according to the thermal management analysis value of each time period, the primary diagnosis value of the thermal management component corresponding to the current preset cycle is calculated, including: According to the thermal management analysis value of each time period, the average value of the thermal management analysis value corresponding to the current preset cycle is calculated; According to the thermal management analysis value of each time period and the preset thermal management analysis threshold, the time period when the thermal management analysis value is greater than the thermal management analysis threshold is determined as the analysis special time period; All the analysis special time periods are obtained, and according to the number of adjacent analysis special time periods, the number of non-adjacent analysis special time periods, and the average value of the thermal management analysis value, the primary diagnosis value of the thermal management component corresponding to the current preset cycle is calculated.

[0047] In this embodiment, according to the thermal management analysis value of each time period, the average value of the thermal management analysis value corresponding to the current preset cycle is calculated. The time period when the thermal management analysis value is greater than the thermal management analysis threshold is the analysis special time period. All the analysis special time periods within the current preset cycle are determined, and the analysis special time periods are sorted according to the corresponding time to obtain the sorting result. According to the sorting result, the number of adjacent analysis special time periods and the number of non-adjacent analysis special time periods are determined, that is, starting from the smallest in terms of time size, the first analysis special time period, the second analysis special time period, the third analysis special time period, etc. in the current preset cycle are determined. It is judged whether the first analysis special time period and the second analysis special time period are adjacent. If they are adjacent, the number of adjacent analysis special time periods is incremented by 1. If they are not adjacent, the number of non-adjacent analysis special time periods is incremented by 1. Then it is judged whether the second analysis special time period and the third analysis special time period are adjacent. If they are adjacent, the number of adjacent analysis special time periods is incremented by 1. If they are not adjacent, the number of non-adjacent analysis special time periods is incremented by 1, until it is judged whether the penultimate analysis special time period and the last analysis special time period are adjacent, and the final number of adjacent analysis special time periods and the number of non-adjacent analysis special time periods are obtained.

[0048] According to the number of adjacent parsing special time periods and the number of non - adjacent parsing special time periods, as well as the average value of the thermal management parsing value, the primary diagnosis value of the thermal management component corresponding to the current preset cycle is calculated. The calculation formula is as follows: Among them, is the primary diagnosis value of the thermal management component corresponding to the current preset cycle, is the average value of the thermal management parsing value, is the number of adjacent parsing special time periods, is the number of non - adjacent parsing special time periods, is the coefficient of adjacent parsing special time periods, is the coefficient of non - adjacent parsing special time periods, and are obtained based on experience. For example, takes the value of 1.62, takes the value of 1.37. and can also take other values, which are not limited in this embodiment.

[0049] In this embodiment, the parsing special time period, that is, the time period when the thermal management component tends to be abnormal, is determined. According to the number of consecutive and non - consecutive parsing special time periods, the primary diagnosis value of the current preset cycle is calculated, the number of consecutive and non - consecutive parsing special time periods is counted, the change trend of the thermal management component tending to be abnormal is judged, and the influence of the change trend of the thermal management component tending to be abnormal on the primary diagnosis value is considered to improve the accuracy of the primary diagnosis value.

[0050] S102: Perform thermal management diagnosis on the thermal management component according to the primary diagnosis value to obtain the diagnosis type of the thermal management component. Traverse all thermal management components to obtain the diagnosis types corresponding to all thermal management components. The diagnosis types include thermal management diagnosis abnormal.

[0051] In step S102, performing thermal management diagnosis on the thermal management component means judging whether the thermal management component is abnormal. The diagnosis types include thermal management diagnosis abnormal.

[0052] In this embodiment, according to the primary diagnosis value, perform thermal management diagnosis on the thermal management component to obtain the diagnosis type of the thermal management component. Among them, the larger the primary diagnosis value, the more abnormal the thermal management component is, and the smaller the primary diagnosis value, the more normal the thermal management component is. Therefore, a diagnosis threshold can be set. When the primary diagnosis value is greater than the diagnosis threshold, it is considered that the stage result of the thermal management component corresponding to the primary diagnosis value is thermal management diagnosis abnormal. Among them, the diagnosis threshold can be set according to experience and is not limited in this embodiment. Traverse all thermal management components to obtain the diagnosis types corresponding to all thermal management components.

[0053] In this embodiment, according to the primary diagnosis value, thermal management diagnosis is performed on the thermal management component to obtain the diagnosis type of the thermal management component, so as to identify the thermal management component with an abnormal thermal management diagnosis type, and then determine the thermal management diagnosis level of the vehicle based on the thermal management component with an abnormal thermal management diagnosis type.

[0054] Optionally, performing thermal management diagnosis on the thermal management component according to the primary diagnosis value to obtain the diagnosis type of the thermal management component includes: According to the primary diagnosis value of the current preset period and the preset diagnosis value range, if the primary diagnosis value is greater than or equal to the maximum value of the diagnosis value range, it is determined that the diagnosis type of the thermal management component is an abnormal thermal management diagnosis; If the primary diagnosis value is less than the maximum value of the diagnosis value range and greater than the minimum value of the diagnosis value range, it is determined that the diagnosis type of the thermal management component is a fuzzy thermal management diagnosis.

[0055] In this embodiment, the diagnosis type also includes a fuzzy thermal management diagnosis. The diagnosis type of the thermal management component corresponding to the primary diagnosis value greater than or equal to the maximum value of the diagnosis value range is determined as an abnormal thermal management diagnosis, and the diagnosis type of the thermal management component corresponding to the primary diagnosis value less than the maximum value of the diagnosis value range and greater than the minimum value of the diagnosis value range is determined as a fuzzy thermal management diagnosis. The diagnosis type of the thermal management component corresponding to the primary diagnosis value less than or equal to the minimum value of the diagnosis value range is determined as a normal thermal management diagnosis. The diagnosis value range is a range preset according to experience, and this embodiment does not make any limitations.

[0056] In this embodiment, the diagnosis type is refined by adding a fuzzy thermal management diagnosis type, so as to perform a secondary judgment on the thermal management component, avoid misdiagnosing a normal thermal management diagnosis as an abnormal thermal management diagnosis and misdiagnosing an abnormal thermal management diagnosis as a normal thermal management diagnosis, and improve the diagnosis accuracy of the thermal management component.

[0057] Optionally, after determining that the diagnosis type of the thermal management component is a fuzzy thermal management diagnosis, it further includes: Obtaining the primary diagnosis value of each of the K preset periods before the current preset period; Calculating the ultimate diagnosis value of the thermal management component in the current preset period according to the primary diagnosis value of each of the K preset periods; According to the ultimate diagnosis value and the preset ultimate diagnosis threshold, if the ultimate diagnosis value is greater than or equal to the ultimate diagnosis threshold, it is determined that the diagnosis type of the thermal management component is an abnormal thermal management diagnosis; If the ultimate diagnosis value is less than the ultimate diagnosis threshold, it is determined that the diagnosis type of the thermal management component is a normal thermal management diagnosis.

[0058] In this embodiment, after determining that the diagnostic type of the thermal management component is fuzzy thermal management diagnosis, a secondary diagnosis is performed on the thermal management component to determine whether the diagnostic type of the thermal management component is abnormal thermal management diagnosis. The primary diagnostic values of each of the K preset cycles before the current preset cycle are obtained, where K is an integer greater than zero. According to the primary diagnostic values of each of the K preset cycles, the ultimate diagnostic value of the thermal management component in the current preset cycle is calculated. When calculating the ultimate diagnostic value, the adjacent preset cycles of the K preset cycles are combined to obtain K - 1 preset cycle combinations. For example, the first preset cycle is combined with the second preset cycle, the second preset cycle is combined with the third preset cycle, the third preset cycle is combined with the fourth preset cycle, until the combination of the (K - 1)th preset cycle and the Kth preset cycle is completed. The mean value of the primary diagnostic values in each preset cycle combination is calculated, that is, the primary diagnostic values in the corresponding preset cycles in each preset cycle combination are added and then divided by 2 to obtain the mean value of the primary diagnostic values in each preset cycle combination. The mean values of all preset cycle combinations are added and then divided by the number of preset cycle combinations to obtain the mean value corresponding to all preset cycle combinations, and the mean value corresponding to all preset cycle combinations is determined as the ultimate diagnostic value of the current preset cycle.

[0059] When the ultimate diagnostic value is greater than or equal to the ultimate diagnostic threshold, the diagnostic type of the corresponding thermal management component is determined as abnormal thermal management diagnosis. When the ultimate diagnostic value is less than the ultimate diagnostic threshold, the diagnostic type of the corresponding thermal management component is determined as normal thermal management diagnosis. The size of the ultimate diagnostic threshold is set according to experience and is not limited in this embodiment.

[0060] In this embodiment, a secondary diagnosis is performed on the thermal management component corresponding to the fuzzy thermal management diagnosis. The diagnosis is based on the primary diagnostic values of each of the previous K preset cycles of the current preset cycle, which increases the diagnostic basis and improves the diagnostic accuracy of the thermal management component with the fuzzy thermal management diagnosis.

[0061] Optionally, calculating the ultimate diagnostic value of the thermal management component in the current preset cycle according to the primary diagnostic values of each of the K preset cycles includes: Combining the adjacent preset cycles of the K preset cycles to obtain K - 1 preset cycle combinations; Calculating the primary diagnostic group value corresponding to each preset cycle combination according to the corresponding primary diagnostic values in each preset cycle combination; Calculating the ultimate diagnostic value of the thermal management component in the current preset cycle according to the primary diagnostic group value corresponding to each preset cycle combination.

[0062] In this embodiment, adjacent preset cycles among K preset cycles are combined to obtain K - 1 preset cycle combinations. For example, the first preset cycle is combined with the second preset cycle, the second preset cycle is combined with the third preset cycle, the third preset cycle is combined with the fourth preset cycle, and so on until the (K - 1)th preset cycle is combined with the Kth preset cycle.

[0063] According to the corresponding primary diagnostic values in each preset cycle combination, the primary diagnostic group value corresponding to each preset cycle combination is calculated. Here, the primary diagnostic group value is the diagnostic value obtained after processing the corresponding primary diagnostic values in the preset cycle combination. When calculating the primary diagnostic group value, the sum of the primary diagnostic values included in each preset cycle combination can be calculated to obtain the primary diagnostic combination value, and then the absolute value of the difference between the primary diagnostic values included in each preset cycle combination is calculated to obtain the primary diagnostic difference value. The primary diagnostic combination value and the primary diagnostic difference value are added together to obtain the primary diagnostic group value corresponding to the preset cycle combination.

[0064] When calculating the ultimate diagnostic value of the thermal management component in the current preset cycle according to the primary diagnostic group value corresponding to each preset cycle combination, the average value of the primary diagnostic group values in all preset cycle combinations can be calculated. That is, after adding up the primary diagnostic group values in all preset cycle combinations, divide by the number of preset cycle combinations to obtain the average value of the primary diagnostic group values. The average value of the primary diagnostic group values is determined as the ultimate diagnostic value.

[0065] In this embodiment, when calculating the ultimate diagnostic value, first calculate the primary diagnostic group value corresponding to each preset cycle combination. When calculating the primary diagnostic group value, the difference between the primary diagnostic values included in each preset cycle combination is added. The greater the difference, the greater the increase in the corresponding primary diagnostic group value based on the original primary diagnostic value, highlighting the difference in the primary diagnostic values between adjacent preset cycles and considering the influence of the difference in the primary diagnostic values between adjacent preset cycles on the ultimate diagnostic value, thereby improving the calculation accuracy of the ultimate diagnostic value.

[0066] S103: Take the thermal management component corresponding to the thermal management diagnosis abnormality as the thermal management diagnosis abnormal component. According to the thermal management diagnosis abnormal component and the preset thermal management relationship diagram, calculate the thermal management diagnostic value of the vehicle, and determine the thermal management diagnostic level of the vehicle according to the thermal management diagnostic value.

[0067] In step S103, the thermal management relationship diagram includes all the thermal management components of the vehicle and shows the thermal management influence relationships between the thermal management components in the form of a relationship diagram. According to the thermally managed diagnostic abnormal component and the preset thermal management relationship diagram, the thermal management diagnostic value of the vehicle is calculated. The thermal management diagnostic value is the diagnostic value that synthesizes the diagnostic results of all the thermal management components in the entire vehicle, and the thermal management diagnostic level reflects the severity of the thermal management problem.

[0068] In this embodiment, a preset thermal management relationship diagram is obtained. The thermal management relationship diagram includes all the thermal management components of the vehicle and shows the thermal management influence relationships between the thermal management components in the form of a relationship diagram. If there is a thermal management influence relationship between two thermal management components, the two thermal management components are associated in the thermal management relationship diagram. If there is no thermal management influence relationship between two thermal management components, the two thermal management components are not associated in the thermal management relationship diagram. For example, there is no thermal management influence relationship between the air conditioning system and the reducer cooling system, so the air conditioning system and the reducer cooling system are not associated in the thermal management relationship diagram. There is a thermal management influence relationship between the electronic control system and the motor, so the electronic control system and the motor are associated in the thermal management relationship diagram.

[0069] The thermal management component corresponding to the diagnosis type of thermally managed diagnostic abnormal is used as the thermally managed diagnostic abnormal component. According to the thermal management relationship diagram, the thermally managed diagnostic abnormal components are compared pairwise to determine whether there is a management influence relationship between any two thermally managed diagnostic abnormal components, and the first quantity of the thermally managed diagnostic abnormal components with a thermal management influence relationship between any two and the second quantity of the thermally managed diagnostic abnormal components without a thermal management influence relationship between any two are determined. For example, if there are three thermally managed diagnostic abnormal components, there is a thermal management influence relationship between the first thermally managed diagnostic abnormal component and the second thermally managed diagnostic abnormal component, and the first quantity is incremented by 1. There is a thermal management influence relationship between the first thermally managed diagnostic abnormal component and the third thermally managed diagnostic abnormal component, and the first quantity is incremented by 1. There is no thermal management influence relationship between the second thermally managed diagnostic abnormal component and the third thermally managed diagnostic abnormal component, and the second quantity is incremented by 1. The initial values of the first quantity and the second quantity are 0, and finally the value of the first quantity is 2 and the value of the second quantity is 1.

[0070] According to the first quantity and the second quantity, the thermal management diagnostic value of the vehicle is calculated, and the calculation formula is as follows: Wherein, is the thermal management diagnostic value, is the first quantity, is the second quantity.

[0071] Determine the thermal management diagnosis level of the vehicle according to the thermal management diagnosis value. Obtain the thermal management diagnosis value intervals corresponding to different thermal management diagnosis levels, determine the thermal management diagnosis value interval where the thermal management diagnosis value is located, and thus determine the thermal management diagnosis level of the vehicle. For example, the thermal management diagnosis value intervals corresponding to different thermal management diagnosis levels are respectively (0, f1], (f1, f2], …, (fc-1, fc], where the thermal management diagnosis value interval of (0, f1] corresponds to the first thermal management diagnosis level, the thermal management diagnosis value interval of (f1, f2] corresponds to the second thermal management diagnosis level, and the thermal management diagnosis value interval of (fc-1, fc] corresponds to the c-th thermal management diagnosis level. Determine the thermal management diagnosis value interval where the thermal management diagnosis value is located according to the thermal management diagnosis value, and determine the thermal management diagnosis level of the vehicle according to the corresponding thermal management diagnosis value interval.

[0072] In this embodiment, according to the thermal management diagnosis abnormal components and the preset thermal management relationship diagram, calculate the thermal management diagnosis value of the vehicle, taking into account the association relationship between the thermal management diagnosis abnormal components, and improve the calculation accuracy of the thermal management diagnosis value. Quantify the thermal management diagnosis level to facilitate the driver to understand the severity of the vehicle's thermal management problem.

[0073] In the present invention, according to the collected thermal management index information, determine the primary diagnosis value of the thermal management component in the current preset cycle, perform thermal management diagnosis on the thermal management component according to the primary diagnosis value in the current preset cycle, obtain the diagnosis type of the thermal management component, and thus determine the thermal management diagnosis abnormal components. Calculate the thermal management diagnosis value of the vehicle according to the thermal management diagnosis abnormal components and the thermal management influence relationship between the corresponding components. The various thermal management components in the entire thermal management system are comprehensively considered, improving the accuracy of the thermal management diagnosis value. Determine the thermal management diagnosis level of the vehicle according to the thermal management diagnosis value, quantify and evaluate the thermal management diagnosis level of the vehicle, and facilitate the driver to understand the severity of the vehicle's thermal management problem.

[0074] See Figure 2 , Figure 2 FIG. is the structural block diagram of a vehicle thermal management diagnosis device provided in Embodiment 2 of the present invention. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown. See Figure 2 The vehicle thermal management diagnosis device 20 includes a thermal management primary diagnosis module 21, a thermal management component diagnosis module 22, and a thermal management level diagnosis module 23.

[0075] The thermal management primary diagnosis module 21 is used to collect the thermal management index information of each thermal management index of any thermal management component in the vehicle in the current preset cycle, and determine the primary diagnosis value of the thermal management component in the current preset cycle according to the thermal management index information of each thermal management index.

[0076] The thermal management component diagnosis module 22 is configured to perform thermal management diagnosis on the thermal management components according to the primary diagnosis values, obtain the diagnosis types of the thermal management components, traverse all the thermal management components, and obtain the diagnosis types corresponding to all the thermal management components. The diagnosis types include abnormal thermal management diagnosis.

[0077] The thermal management level diagnosis module 23 is configured to use the thermal management components corresponding to the abnormal thermal management diagnosis as the thermal management diagnosis abnormal components, calculate the thermal management diagnosis value of the vehicle according to the thermal management diagnosis abnormal components and a preset thermal management relationship diagram, and determine the thermal management diagnosis level of the vehicle according to the thermal management diagnosis value.

[0078] Optionally, the above detection module 21 includes: A division unit configured to divide the current preset period into N time periods, where N is an integer greater than zero; A determination unit configured to determine the thermal management index information corresponding to each time period of each thermal management index in the current preset period.

[0079] A first calculation unit configured to calculate the thermal management analysis value of the thermal management components corresponding to the corresponding time period according to the thermal management index information of each thermal management index in each time period.

[0080] A second calculation unit configured to calculate the primary diagnosis value of the thermal management components in the current preset period according to the thermal management analysis values of each time period.

[0081] Optionally, the above first calculation unit includes: A first determination subunit configured to, for any time period, determine the thermal analysis value of each thermal management index according to the thermal management index information corresponding to each time period of each thermal management index and a preset thermal management index model.

[0082] A second determination subunit configured to determine the index type of each thermal management index according to the thermal analysis value of each thermal management index and a preset analysis threshold. The index types include out-of-bounds thermal indexes and in-bounds thermal indexes.

[0083] A first calculation subunit configured to calculate the thermal management analysis value of the thermal management components corresponding to the corresponding time period according to the thermal analysis value of the out-of-bounds thermal index type and the thermal analysis value of the in-bounds thermal index type.

[0084] Optionally, the above second calculation unit includes: A second calculation subunit configured to calculate the mean value of the thermal management analysis values corresponding to the current preset period according to the thermal management analysis values of each time period.

[0085] A third determination subunit, configured to determine, according to the thermal management analysis value in each time period and a preset thermal management analysis threshold, that the time period in which the thermal management analysis value is greater than the thermal management analysis threshold is an analysis special period.

[0086] A third calculation subunit, configured to obtain all the analysis special periods, and calculate a primary diagnosis value of the thermal management component corresponding to the current preset period according to the number of adjacent analysis special periods and the number of non-adjacent analysis special periods, and the average value of the thermal management analysis values.

[0087] Optionally, the above-mentioned thermal management component diagnosis module 22 includes: A first judgment unit, configured to determine that the diagnosis type of the thermal management component is abnormal thermal management diagnosis if the primary diagnosis value in the current preset period is greater than or equal to the maximum value of the preset diagnosis value range according to the primary diagnosis value in the current preset period and the preset diagnosis value range.

[0088] A second judgment unit, configured to determine that the diagnosis type of the thermal management component is fuzzy thermal management diagnosis if the primary diagnosis value is less than the maximum value of the diagnosis value range and greater than the minimum value of the diagnosis value range.

[0089] Optionally, the above-mentioned thermal management component diagnosis module 22 further includes: An acquisition unit, configured to acquire the primary diagnosis value of each preset period in the K preset periods before the current preset period, where K is an integer greater than zero.

[0090] A third calculation unit, configured to calculate an ultimate diagnosis value of the thermal management component in the current preset period according to the primary diagnosis value of each preset period in the K preset periods.

[0091] A third judgment unit, configured to determine that the diagnosis type of the thermal management component is abnormal thermal management diagnosis if the ultimate diagnosis value is greater than or equal to the preset ultimate diagnosis threshold according to the ultimate diagnosis value and the preset ultimate diagnosis threshold.

[0092] Optionally, the above-mentioned third calculation unit includes: A combination subunit, configured to combine adjacent preset periods of the K preset periods to obtain K-1 preset period combinations.

[0093] A fourth calculation subunit, configured to calculate a primary diagnosis group value corresponding to each preset period combination according to the primary diagnosis value corresponding to each preset period combination.

[0094] A fifth calculation subunit, configured to calculate an ultimate diagnosis value of the thermal management component in the current preset period according to the primary diagnosis group value corresponding to each preset period combination.

[0095] It should be noted that for the content such as information interaction and execution process among the above modules, since it is based on the same concept as the method embodiment of the present application, for its specific functions and the technical effects brought, reference can be specifically made to the method embodiment part, and details will not be repeated here.

[0096] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 3 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the thermal management index information of each thermal management index of the thermal management component in each preset cycle. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a vehicle thermal management diagnosis method.

[0097] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the vehicle thermal management diagnosis method in the above embodiment, such as Figure 1 the functions of the vehicle thermal management diagnosis method shown, or when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the vehicle thermal management diagnosis device, such as Figure 2 the functions of the vehicle thermal management diagnosis device shown. To avoid repetition, details will not be repeated here.

[0098] In one embodiment, a computer-readable storage medium is provided. A computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, it implements the vehicle thermal management diagnosis method in the above embodiment, such as Figure 1 the functions of a vehicle thermal management diagnosis method shown. To avoid repetition, details will not be repeated here. Or when the computer program is executed by the processor, it implements the functions of each module / unit in this embodiment of the above vehicle thermal management diagnosis device, such as Figure 2 the functions of each module in a vehicle thermal management diagnosis device shown. To avoid repetition, details will not be repeated here.

[0099] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0100] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A vehicle thermal management diagnosis method, characterized in that, Including: For any thermal management component in a vehicle, collect the thermal management index information of each thermal management index of the thermal management component in the current preset cycle, and determine the primary diagnosis value of the thermal management component in the current preset cycle according to the thermal management index information of each thermal management index; Perform thermal management diagnosis on the thermal management component according to the primary diagnosis value to obtain the diagnosis type of the thermal management component. Traverse all thermal management components to obtain the diagnosis types corresponding to all thermal management components. The diagnosis type includes thermal management diagnosis anomaly; Take the thermal management component corresponding to the thermal management diagnosis anomaly as the thermal management diagnosis anomaly component. According to the thermal management diagnosis anomaly component and the preset thermal management relationship diagram, calculate the thermal management diagnosis value of the vehicle, and determine the thermal management diagnosis level of the vehicle according to the thermal management diagnosis value.

2. The vehicle thermal management diagnosis method according to claim 1, characterized in that, The step of determining the primary diagnosis value of the thermal management component in the current preset cycle according to the thermal management index information of each thermal management index includes: Divide the current preset cycle into N time periods, where N is an integer greater than zero; Determine the thermal management index information corresponding to each time period of each thermal management index in the current preset cycle; Calculate the thermal management analysis value of the thermal management component corresponding to the corresponding time period according to the thermal management index information of each thermal management index in each time period; Calculate the primary diagnosis value of the thermal management component in the current preset cycle according to the thermal management analysis values of each time period.

3. The vehicle thermal management diagnosis method according to claim 2, wherein The step of calculating the thermal management analysis value of the thermal management component corresponding to the corresponding time period according to the thermal management index information of each thermal management index in each time period includes: For any time period, determine the thermal analysis value of each thermal management index according to the thermal management index information corresponding to each time period of each thermal management index and the preset thermal management index model; Determine the index type of each thermal management index according to the thermal analysis value of each thermal management index and the preset analysis threshold. The index type includes out-of-bounds thermal index and in-bounds thermal index; Calculate the thermal management analysis value of the thermal management component corresponding to the corresponding time period according to the thermal analysis value of the thermal management index with the out-of-bounds thermal index type and the thermal analysis value of the thermal management index with the in-bounds thermal index type.

4. The vehicle thermal management diagnosis method according to claim 2, wherein, The step of calculating the primary diagnosis value of the thermal management component in the corresponding current preset cycle according to the thermal management analysis values of each time period includes: Calculate the mean value of the thermal management analysis values corresponding to the current preset cycle according to the thermal management analysis values of each time period; Determine the time period when the thermal management analysis value is greater than the preset thermal management analysis threshold as the analysis special time period according to the thermal management analysis values of each time period and the preset thermal management analysis threshold; Obtain all the analysis special time periods, and calculate the primary diagnosis value of the thermal management component in the corresponding current preset cycle according to the number of adjacent analysis special time periods and the number of non-adjacent analysis special time periods, and the mean value of the thermal management analysis values.

5. The vehicle thermal management diagnosis method according to any one of claims 1-4, characterized in that, The diagnosis type further includes thermal management diagnosis ambiguity; Performing thermal management diagnosis on the thermal management component according to the primary diagnosis value to obtain the diagnosis type of the thermal management component includes: According to the primary diagnostic value of the current preset cycle and the preset diagnostic value range, if the primary diagnostic value is greater than or equal to the maximum value of the diagnostic value range, it is determined that the diagnostic type of the thermal management component is thermal management diagnostic anomaly; If the primary diagnostic value is less than the maximum value of the diagnostic value range and greater than the minimum value of the diagnostic value range, it is determined that the diagnostic type of the thermal management component is thermal management diagnostic ambiguity.

6. The vehicle thermal management diagnosis method according to claim 5, characterized in that, After determining that the diagnostic type of the thermal management component is thermal management diagnostic ambiguity, it further includes: Obtaining the primary diagnostic value of each of the K preset cycles before the current preset cycle, where K is an integer greater than zero; Calculating the ultimate diagnostic value of the thermal management component in the current preset cycle according to the primary diagnostic values of each of the K preset cycles; According to the ultimate diagnostic value and the preset ultimate diagnostic threshold, if the ultimate diagnostic value is greater than or equal to the ultimate diagnostic threshold, it is determined that the diagnostic type of the thermal management component is thermal management diagnostic anomaly.

7. The vehicle thermal management diagnosis method according to claim 6, characterized in that, The calculating the ultimate diagnostic value of the thermal management component in the current preset cycle according to the primary diagnostic values of each of the K preset cycles includes: Combining adjacent preset cycles among the K preset cycles to obtain K - 1 preset cycle combinations; Calculating the primary diagnostic group value corresponding to each preset cycle combination according to the corresponding primary diagnostic value in each preset cycle combination; Calculating the ultimate diagnostic value of the thermal management component in the current preset cycle according to the primary diagnostic group value corresponding to each preset cycle combination.

8. A vehicle thermal management diagnostic device, characterized in that, It includes: A thermal management primary diagnostic module, configured to collect thermal management index information of each thermal management index of any thermal management component in the vehicle in the current preset cycle, and determine the primary diagnostic value of the thermal management component in the current preset cycle according to the thermal management index information of each thermal management index; A thermal management component diagnostic module, configured to perform thermal management diagnosis on the thermal management component according to the primary diagnostic value to obtain the diagnostic type of the thermal management component, traverse all thermal management components to obtain the diagnostic types corresponding to all thermal management components, and the diagnostic type includes thermal management diagnostic anomaly; A thermal management level diagnostic module, configured to use the thermal management component corresponding to the thermal management diagnostic anomaly as a thermal management diagnostic anomaly component, calculate the thermal management diagnostic value of the vehicle according to the thermal management diagnostic anomaly component and the preset thermal management relationship diagram, and determine the thermal management diagnostic level of the vehicle according to the thermal management diagnostic value.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the vehicle thermal management diagnostic method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the vehicle thermal management diagnostic method according to any one of claims 1 to 7.

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