New energy automobile driving system global thermal management method

Abstract

The invention relates to the technical field of automobile thermal management, in particular to a new energy automobile driving system global thermal management method, which comprises the following steps of: 1, determining heating concentration point positions in a new energy automobile driving system, and arranging a temperature sensor at each heating concentration point position; 2, regularly determining whether a thermal management participation step needs to be started or not; 3, after the heat management participation step is started, the heat management sequence of all the point locations to be subjected to heat management is determined; 4, according to the thermal management sequence of the point locations to be subjected to thermal management, thermal management is carried out on the first point location to be subjected to thermal management, the thermal management priority of each point location to be subjected to thermal management is guaranteed on the basis that thermal safety comprehensive coverage is achieved, and a thermal management optimization strategy of the point locations to be subjected to thermal management is customized; the method aims at solving the problem of abnormal heating of a core point location to be subjected to heat management and synchronously optimizing the abnormal heating conditions of other point locations to be subjected to heat management to the greatest extent.

Description

Technical Field

[0001] The present invention relates to the field of automotive thermal management technology, and more specifically, to a global thermal management method for a new energy vehicle drive system. Background Art

[0002] Existing thermal management solutions for new energy vehicles typically employ a widespread deployment of temperature sensors throughout the drive system to effectively monitor and manage drive system temperatures. For example, these sensors are deployed in numerous locations within key components such as the battery pack, motor, and electronic control module, ensuring comprehensive temperature information is collected. This information is then used to determine whether thermal management measures should be initiated and how to implement appropriate thermal management strategies.

[0003] However, this traditional layout method has significant drawbacks. Firstly, from a cost perspective, the purchase, installation, and subsequent maintenance costs of a large number of temperature sensors are extremely high, which undoubtedly increases the production cost of new energy vehicles. Secondly, the placement of numerous temperature sensors in the drive system consumes a significant amount of space, further congesting the already compact interior of the vehicle's drive system. This not only poses challenges to the overall structural design of the vehicle, increasing wiring difficulty and assembly complexity, but also, in some extreme operating conditions, space constraints may affect the normal operation of the sensors, thereby affecting the thermal management system's ability to accurately obtain and judge temperature information, reducing the reliability and effectiveness of thermal management.

[0004] In addition, this widely distributed thermal management method often lacks in-depth integration and analysis of temperature information at various points in the drive system. It often simply makes local thermal management decisions based on the temperature values fed back by each sensor. It is difficult to comprehensively consider the thermal correlation between various parts and the complex thermal changes under different working conditions from a system level. As a result, the thermal management strategy is not accurate and efficient enough, and is prone to problems such as local overheating or waste of heat dissipation resources. It is impossible to achieve global optimized thermal management of the new energy vehicle drive system, affecting the overall performance and safety of the vehicle.

[0005] In view of the above-mentioned deficiencies in existing thermal management solutions for new energy vehicle drive systems, the present invention aims to provide a new global thermal management method for new energy vehicle drive systems. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a global thermal management method for a new energy vehicle drive system.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The full-area thermal management method for new energy vehicle drive systems has the following steps:

[0009] Step 1: Determine the heat concentration points in the new energy vehicle drive system and place a temperature sensor at each heat concentration point;

[0010] Step 2: Regularly determine whether thermal management participation steps need to be initiated;

[0011] Step 3: After starting the thermal management participation step, determine the thermal management order of all points to be thermally managed;

[0012] Step 4: According to the thermal management order of the points to be thermally managed, perform thermal management on the point to be thermally managed that is ranked first.

[0013] Furthermore, it is determined regularly whether the thermal management participation step needs to be initiated: the fever evaluation value of each fever concentration point is regularly determined, and a fever zone evaluation threshold is set. When the fever evaluation value of the fever concentration point is ≥ the fever zone evaluation threshold, the corresponding fever concentration point is marked as a point to be thermally managed, and then a comprehensive fever split analysis value is obtained, and a comprehensive fever split analysis threshold is set. When the comprehensive fever split analysis value is ≥ the comprehensive fever split analysis threshold, it is determined to initiate the thermal management participation step.

[0014] Comprehensive fever split analysis value, acquisition process: the fever point values of all fever concentration points are summed up to obtain the comprehensive fever split analysis value.

[0015] Furthermore, the fever evaluation score of a fever concentration point is regularly determined by the following process: selecting a fever concentration point, obtaining all temperature data of the fever concentration point in the previous cycle, performing feature extraction on all temperature data, extracting temperature features, building a point analysis model for the fever concentration point, importing the temperature features into the point analysis model of the fever concentration point, and then obtaining the fever evaluation score of the fever concentration point.

[0016] Furthermore, the thermal management order of all points to be thermally managed is determined by the following process: obtaining the thermal management core value of each point to be thermally managed, arranging all points to be thermally managed in the order of the thermal management core values, and generating the thermal management order of all points to be thermally managed according to the arrangement.

[0017] Furthermore, the core value of heat management of the point to be heat managed: select a point to be heat managed, obtain the heat evaluation score of the point to be heat managed, compare the point to be heat managed with all other points to be heat managed in pairs, obtain the distance between the two compared points to be heat managed, set the boundary influence distance, when the distance between the two points to be heat managed is less than the boundary influence distance, calculate the heat dynamic connection value of the two points to be heat managed, calculate the sum of all the heat dynamic connection values and take the average to obtain the comprehensive heat dynamic connection value, and calculate the core value of heat management of the point to be heat managed through the heat evaluation score and the comprehensive heat dynamic connection value of the point to be heat managed.

[0018] Furthermore, the dynamic connection value of the heat generation of the two points to be heat-managed is determined by the following process: the two points to be heat-managed are marked as hot zone N and hot zone M respectively, the temperature characteristics corresponding to each period in the L periods before hot zone N are obtained, and the temperature characteristics corresponding to each period in the L periods before hot zone M are simultaneously obtained, the temperature characteristics of hot zone N and the temperature characteristics of hot zone M in the same period are matched into a hot zone feature comparison set, a hot zone feature comparison model is built, and the hot zone feature comparison set corresponding to each period is imported into the hot zone feature comparison model, and then the hot zone heat generation synchronization value corresponding to each period is obtained, each period is marked with a serial number in sequence, and a rectangular coordinate system is constructed with the serial number of the period as the X-axis and the hot zone heat generation synchronization value as the Y-axis, and a short line segment comprehensive slope and a closed figure are obtained according to the rectangular coordinate system, and the dynamic connection value of the heat generation of the two points to be heat-managed is calculated according to the comprehensive slope of the short line segment and the area of the closed figure.

[0019] Furthermore, a comprehensive slope of a short line segment and a closed figure are obtained according to the rectangular coordinate system: the serial number corresponding to each period and the heating synchronization value of the hot zone are marked in the rectangular coordinate system in the form of a coordinate point, L coordinate points are marked, and adjacent coordinate points are connected to obtain L-1 short line segments, and the slope of each short line segment is obtained. The slopes of all short line segments are summed to calculate the comprehensive slope of the short line segments, and the L-1 short line segments are combined into a heating synchronization curve. The two endpoints of the heating synchronization curve are arranged to be perpendicular segments to the X-axis, and the heating synchronization curve, the two perpendicular segments and the X-axis form a closed figure.

[0020] Furthermore, thermal management is performed on the first-ranked point to be managed for heat: a drive system thermal management model is constructed, the first-ranked point to be managed for heat is marked as the primary management point, the operating parameters of each key component in the new energy vehicle drive system are obtained, the temperature characteristics of the primary management point and the remaining points to be managed for heat and the operating parameters of each key component are imported into the drive system thermal management model, the target temperature characteristics of the primary management point are determined, the target temperature characteristics of the primary management point are imported into the drive system thermal management model, the drive system thermal management model is controlled to perform multiple simulation managements, the comprehensive thermal split analysis value of the drive system thermal management model under each simulation management is determined, the management strategy corresponding to the simulation management with the smallest comprehensive thermal split analysis value is marked as the thermal management participation strategy, and the thermal management participation strategy is executed to regulate the key components in the new energy vehicle drive system.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The method of the present invention monitors the temperature of concentrated heat points in the new energy vehicle drive system all the time and conducts in-depth multi-dimensional analysis, accurately and quantitatively analyzes whether it is necessary to start the thermal management participation step, and meets the full-domain thermal management of the new energy vehicle drive system. After starting the thermal management participation step, further analysis is performed on each point to be managed thermally. Combined with the scene correlation and independent time and space between the points to be managed thermally, the core degree of heat generation of the points to be managed thermally is deeply analyzed. On the basis of achieving comprehensive coverage of thermal safety, the thermal management priority of each point to be managed thermally is guaranteed, and the thermal management optimization strategy of the points to be managed thermally is customized, aiming to solve the abnormal heating of the core points to be managed thermally while simultaneously optimizing the abnormal heating conditions of the remaining points to be managed thermally to the greatest extent, thereby comprehensively improving the overall efficiency and quality of thermal management. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of the method of the present invention;

[0024] Figure 2 Flowchart for executing thermal management for the points to be thermally managed;

[0025] Figure 3 Flowchart for determining the thermal management sequence. DETAILED DESCRIPTION

[0026] Reference Figures 1 to 3 , the global thermal management method of the new energy vehicle drive system, the steps are as follows:

[0027] Step 1: Determine the heat concentration points in the new energy vehicle drive system (in the production process of the new energy vehicle drive system, the heat concentration points in the drive system can be determined based on the simulation analysis, structural layout characteristics and thermal characteristics of materials / processes in the design stage), and place a temperature sensor at each heat concentration point.

[0028] Step 2: Regularly determine whether it is necessary to start the thermal management participation step: regularly determine the fever evaluation value of each fever concentration point, set the fever zone evaluation threshold, when the fever evaluation value of the fever concentration point ≥ the fever zone evaluation threshold, mark the corresponding fever concentration point as a point to be thermally managed; when the fever evaluation value of the fever concentration point is less than the fever zone evaluation threshold, do not mark it, and then obtain the comprehensive fever split analysis value, set the comprehensive fever split analysis threshold, when the comprehensive fever split analysis value ≥ the comprehensive fever split analysis threshold, determine to start the thermal management participation step, when the comprehensive fever split analysis value < the comprehensive fever split analysis threshold, do not start the thermal management participation step;

[0029] Comprehensive fever split analysis value, acquisition process: the fever point values of all fever concentration points are calculated and the comprehensive fever split analysis value is obtained;

[0030] The fever evaluation score of a fever concentration point is determined regularly: a fever concentration point is selected, all temperature data of the fever concentration point in the previous cycle is obtained (obtained from the temperature sensor corresponding to the fever concentration point), all temperature data are extracted, temperature features are extracted, a point analysis model for the fever concentration point is built, and the temperature features are imported into the point analysis model of the fever concentration point to obtain the fever evaluation score of the fever concentration point;

[0031] In the method of the present invention, each fever concentration point is set to correspond to an independently trained deep learning model, and each deep learning model grows into a corresponding point analysis model through independent training. In the specific implementation method, the construction process of the point analysis model is disclosed by taking the fever concentration point A as an example: a deep learning model is built to obtain the temperature characteristics of s fever concentration points A (a large amount of temperature data related to the fever concentration point A is collected and simulated, and these data cover the temperature performance of the fever concentration point A under different working conditions and different time nodes), and the temperature characteristics of the fever concentration point A are used as basic data to train the built deep learning model. During the training process, we assigned a fever score to each temperature feature of fever hotspot A, ranging from 0 to 10. It's important to note that the fever score has a clear meaning: a larger value indicates a more abnormal fever at the corresponding fever hotspot A, visually reflecting the deviation of fever levels at fever hotspot A from normal levels. We then partitioned the collected temperature features of the s fever hotspots A into training, validation, and test sets according to a specific ratio of 70%:15%:15%. This partitioning approach facilitates comprehensive and scientific model training, validation, and final performance testing, ensuring that the model accurately assesses fever at fever hotspot A based on the input temperature features. After the training is complete, the deep learning model is repeatedly trained on the training set to learn and grasp the inherent correlation between temperature features and fever score. During the training process, the validation set is used to timely verify the model's performance during the training phase. Based on the verification results, the model parameters are adjusted promptly, and the model structure is optimized to achieve greater accuracy and stability. Once the model's performance on the training and validation sets meets expectations, the test set is used for a final performance test to verify the model's generalization and accuracy on data not previously trained. After this rigorous training, validation, and testing process, when all model indicators meet the requirements, a point analysis model specifically designed for analyzing fever concentration point A is successfully constructed.

[0032] Step 3: After starting the thermal management participation step, determine the thermal management order of all points to be thermally managed;

[0033] The thermal management order of all points to be thermally managed is determined by: obtaining the thermal management core value of each point to be thermally managed, arranging all points to be thermally managed in the order of the thermal management core values, and generating the thermal management order of all points to be thermally managed according to the arrangement;

[0034] Core value of heat management of the point to be managed: Select a point to be managed, obtain the heat evaluation score Spayp of the point to be managed, compare the point to be managed with all other points to be managed (e.g., if point A is selected, and the other points to be managed include point B and point C, then point A is compared with point B, and point A is compared with point C), obtain the distance between the two compared points to be managed, set the boundary influence distance (the boundary influence distance is the preset distance), and when two points to be managed are If the distance between the points is less than the boundary influence distance, the heat dynamic connection value of the two points to be thermally managed is calculated. If the distance between the two points to be thermally managed is greater than or equal to the fuzzy influence distance, the heat dynamic connection value of the two points to be thermally managed is not calculated. All heat dynamic connection values are summed and averaged to obtain the comprehensive heat dynamic connection value Conth. The heat management emergency value Ymqgy is calculated by Ymqgy = Spayp*cs2 + Conth*cs3, where cs2 is the second coefficient and cs3 is the third coefficient. The value of the second coefficient is 2.01, and the value of the third coefficient is 2.79.

[0035] The dynamic contact value of the heat of two points to be managed by heat is determined by the following process: the two points to be managed by heat are marked as hot zone N and hot zone M respectively, the temperature characteristics corresponding to each cycle in the L cycles before hot zone N are obtained, and the temperature characteristics corresponding to each cycle in the L cycles before hot zone M are obtained simultaneously. The temperature characteristics of hot zone N and the temperature characteristics of hot zone M in the same cycle are matched into a hot zone feature comparison set, a hot zone feature comparison model is built, and the hot zone feature comparison set corresponding to each cycle is imported into the hot zone feature comparison model, and then the hot zone heat synchronization value corresponding to each cycle is obtained. The serial number of each cycle is marked in sequence, and the serial number of the cycle is used. As the X-axis, the hot zone heating synchronization value is used as the Y-axis to construct a rectangular coordinate system, and the serial number corresponding to each cycle and the hot zone heating synchronization value are marked in the rectangular coordinate system in the form of a coordinate point. L coordinate points are marked, and adjacent coordinate points are connected to obtain L-1 short line segments. The slope of each short line segment is obtained, and the slopes of all short line segments are summed to calculate the comprehensive slope Xvg of the short line segments. The L-1 short line segments are combined into a heating synchronization curve, and the two end points of the heating synchronization curve are arranged to be perpendicular to the X-axis. The area of the closed figure composed of the heating synchronization curve, the two perpendicular line segments and the X-axis is marked as Arces. The heat dynamic contact value Fb{M, N} of the two points to be heat-managed is calculated, where cs1 is the first coefficient, and the value of the first coefficient can be 0.98;

[0036] In the method of the present invention, the hot zone feature comparison model is also independently trained and built by the deep learning model. The building process is as follows: build a deep learning model, obtain d hot zone feature comparison sets, use the hot zone feature comparison sets as basic data, and train the built deep learning model. In this process, we assign a hot zone heating synchronization value to each hot zone feature comparison set. The value range of the hot zone heating synchronization value is set between 0 and 2.5. It should be emphasized that the size of the hot zone heating synchronization value has a clear meaning. The larger the value, the closer the temperature characteristics of the two hot zones in the hot zone feature comparison set are, which can intuitively reflect whether the heating conditions of the two hot zones in the hot zone feature comparison set are similar. Then, we divide the collected d hot zone feature comparison sets into training set, validation set and test set according to a specific ratio. The specific division ratio is determined to be 70%:20%:10%. The training process is not repeated. Finally, the hot zone feature comparison model is successfully built.

[0037] Step 4: Perform thermal management on the first-ranked point to be thermally managed according to the thermal management order of the points to be thermally managed (after thermal management is completed on the first-ranked point to be thermally managed, perform thermal management on the next-ranked point to be thermally managed);

[0038] Perform thermal management on the first-ranked point to be managed by heat: Build a thermal management model for the drive system, mark the first-ranked point to be managed by heat as the primary management point, obtain the operating parameters of each key component in the new energy vehicle drive system (key components include batteries, motors, electronic control components, etc. These key components play a core role in the full-domain thermal management of new energy vehicles), import the temperature characteristics of the primary management point and the remaining points to be managed by heat, and the operating parameters of each key component into the thermal management model of the drive system, determine the target temperature characteristics of the primary management point (the target temperature characteristics of the primary management point are pre-set temperature characteristics, that is, the temperature characteristics under normal circumstances), and import the target temperature characteristics of the primary management point into the thermal management model of the drive system In the process, the thermal management model of the drive system is controlled to perform multiple simulation managements (simulation management is to adjust the temperature characteristics of the primary management point toward the target temperature characteristics by regulating the sub-models of the key components in the thermal management model of the drive system. Each simulation management corresponds to a management strategy). The comprehensive heat split analysis value of the thermal management model of the drive system under each simulation management is determined (although each simulation management can adjust the temperature characteristics of the primary management point to the target temperature characteristics, the adjustment degree of the remaining points to be thermally managed is not consistent). The management strategy corresponding to the simulation management with the smallest comprehensive heat split analysis value is marked as the thermal management participation strategy. The thermal management participation strategy is executed to regulate the key components in the drive system of the new energy vehicle.

[0039] Drive system thermal management model, construction process: Extract the three-dimensional model of the drive system from CAD design drawings (such as CATIA / UG files), including the battery pack (including battery cells / liquid cooling plate), motor (stator / rotor / housing), electronic control module (IGBT / capacitor / heat dissipation substrate), etc., retain the accuracy to 0.1mm, simplify non-critical structures (such as bolts / snaps), retain the core heat conduction path (such as the contact surface between the battery cell and the liquid cooling plate, the IGBT and the water cooling plate fitting surface, preset typical working condition boundary conditions, and create sub-models of each key component in the simulation software. Taking the sub-model of the battery pack as an example, the sub-model of the battery pack includes battery cell modeling and liquid cooling system modeling: Battery cell modeling, a single battery cell is simplified as a hexahedral heat source, and a built-in heat generation formula (Ohmic heat + polarization heat); a phase change material (PCM) layer is added between the battery cells, with a melting point of 30°C, latent heat of 180kJ / kg, and contact thermal resistance of 0.2°C·mm2 / W; liquid cooling system: the flow channel is defined as a B-spline curve, the inlet is set to a mass flow rate (2L / min), a temperature of 25°C, and the outlet is a pressure boundary (0Pa); a coupling boundary is set between the contact surface of the liquid cooling plate and the battery cell, with a thermal conductivity of 15W / m·K (including a silicone grease layer), and the simulation software is corrected in a closed loop from simulation to actual measurement. Finally, a thermal management model of the drive system is built.

[0040] The above method monitors the temperature of the concentrated heat points in the new energy vehicle drive system all the time and conducts in-depth multi-dimensional analysis, accurately and quantitatively analyzes whether it is necessary to start the thermal management participation step to meet the full-domain thermal management of the new energy vehicle drive system. After starting the thermal management participation step, further analysis is performed on each heat management point. Combined with the scene correlation and independent time and space between the heat management points, the heat core degree of the heat management points is deeply analyzed. On the basis of achieving comprehensive coverage of thermal safety, the thermal management priority of each heat management point is guaranteed, and the thermal management optimization strategy of the heat management points is customized. The purpose is to solve the abnormal heating of the core heat management points while optimizing the abnormal heating of the remaining heat management points to the greatest extent, thereby comprehensively improving the overall efficiency and quality of thermal management.

[0041] The above formulas are all dimensionless and numerically calculated, and the preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0042] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0043] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0044] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0045] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0046] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0047] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0048] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A global thermal management method for a new energy vehicle drive system, characterized in that: Here are the steps: Step 1: Determine the heat concentration points in the new energy vehicle drive system and place a temperature sensor at each heat concentration point; Step 2: Regularly determine whether thermal management participation steps need to be initiated; Step 3: After starting the thermal management participation step, determine the thermal management order of all points to be thermally managed; Step 4: According to the thermal management order of the points to be thermally managed, perform thermal management on the point to be thermally managed that is ranked first.

2. The global thermal management method for a new energy vehicle drive system according to claim 1, characterized in that: Regularly determine whether it is necessary to start the thermal management participation step: regularly determine the fever evaluation value of each fever concentration point, set the fever zone evaluation threshold, and when the fever evaluation value of the fever concentration point ≥ the fever zone evaluation threshold, mark the corresponding fever concentration point as a point to be thermally managed, and then obtain the comprehensive fever split analysis value, set the comprehensive fever split analysis threshold, and when the comprehensive fever split analysis value ≥ the comprehensive fever split analysis threshold, determine to start the thermal management participation step; Comprehensive fever split analysis value, acquisition process: the fever point values of all fever concentration points are summed up to obtain the comprehensive fever split analysis value.

3. The global thermal management method for a new energy vehicle drive system according to claim 2, characterized in that: The fever evaluation score of a fever concentration point is determined regularly: select a fever concentration point, obtain all temperature data of the fever concentration point in the previous cycle, perform feature extraction on all temperature data, extract temperature features, build a point analysis model for the fever concentration point, import the temperature features into the point analysis model of the fever concentration point, and then obtain the fever evaluation score of the fever concentration point.

4. The global thermal management method for a new energy vehicle drive system according to claim 1, characterized in that: The thermal management order of all points to be thermally managed is determined by: obtaining the thermal management core value of each point to be thermally managed, arranging all points to be thermally managed in the order of the thermal management core values, and generating the thermal management order of all points to be thermally managed according to the arrangement.

5. The global thermal management method for a new energy vehicle drive system according to claim 1, characterized in that: The core value of heat management of the point to be managed by heat: select a point to be managed by heat, obtain the heat evaluation score of the point to be managed by heat, compare the point to be managed by heat with all other points to be managed by heat, obtain the distance between the two compared points to be managed by heat, set the boundary influence distance, when the distance between the two points to be managed by heat is less than the boundary influence distance, calculate the heat dynamic connection value of the two points to be managed by heat, calculate the sum of all the heat dynamic connection values and take the average to obtain the comprehensive heat dynamic connection value, and calculate the heat management core value of the point to be managed by heat through the heat evaluation score of the point to be managed by heat and the comprehensive heat dynamic connection value.

6. The global thermal management method for a new energy vehicle drive system according to claim 5, characterized in that: The determination process of the heat dynamic connection value of two points to be heat-managed is as follows: mark the two points to be heat-managed as hot zone N and hot zone M respectively, obtain the temperature characteristics corresponding to each cycle in the L cycles before hot zone N, and simultaneously obtain the temperature characteristics corresponding to each cycle in the L cycles before hot zone M, match the temperature characteristics of hot zone N and the temperature characteristics of hot zone M in the same cycle into a hot zone feature comparison set, build a hot zone feature comparison model, import the hot zone feature comparison set corresponding to each cycle into the hot zone feature comparison model, and then obtain the hot zone heat synchronization value corresponding to each cycle, mark each cycle in sequence, and construct a rectangular coordinate system with the cycle sequence number as the X-axis and the hot zone heat synchronization value as the Y-axis, obtain a short line segment comprehensive slope and a closed figure according to the rectangular coordinate system, and calculate the heat dynamic connection value of the two points to be heat-managed according to the short line segment comprehensive slope and the area of the closed figure.

7. The global thermal management method for a new energy vehicle drive system according to claim 6, characterized in that: Obtain a comprehensive slope of a short line segment and a closed figure according to the rectangular coordinate system: mark the serial number corresponding to each period and the heating synchronization value of the hot zone in the form of a coordinate point in the rectangular coordinate system, mark L coordinate points, connect adjacent coordinate points to obtain L-1 short line segments, obtain the slope of each short line segment, sum the slopes of all short line segments, calculate the comprehensive slope of the short line segments, combine the L-1 short line segments into a heating synchronization curve, arrange the two endpoints of the heating synchronization curve to be perpendicular to the X-axis, and form a closed figure with the heating synchronization curve, the two perpendicular line segments and the X-axis.

8. The global thermal management method for a new energy vehicle drive system according to claim 1, characterized in that: Perform thermal management on the first-ranked point to be managed for heat: build a drive system thermal management model, mark the first-ranked point to be managed for heat as the primary management point, obtain the operating parameters of each key component in the new energy vehicle drive system, import the temperature characteristics of the primary management point and the remaining points to be managed for heat, and the operating parameters of each key component into the drive system thermal management model, determine the target temperature characteristics of the primary management point, import the target temperature characteristics of the primary management point into the drive system thermal management model, control the drive system thermal management model to perform multiple simulation managements, determine the comprehensive thermal split analysis value of the drive system thermal management model under each simulation management, mark the management strategy corresponding to the simulation management with the smallest comprehensive thermal split analysis value as the thermal management participation strategy, and execute the thermal management participation strategy to regulate the key components in the new energy vehicle drive system.

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