Heat damage condition data calculation method, device, electronic equipment and storage medium

Abstract

The present application relates to the field of data extraction and calculation technology, and in particular to a method, device, electronic device, and storage medium for calculating thermal damage condition data. The method comprises: obtaining raw driving data of multiple sample vehicles in multiple preset environments, establishing a signal intermediate table based on the raw driving data; screening multiple target vehicles that meet preset conditions based on the signal intermediate table, and obtaining the initial longitude and latitude of each target vehicle each day; partitioning the signal intermediate table according to preset business dates based on the initial longitude and latitude of each target vehicle each day, and obtaining thermal damage condition data for multiple target vehicles based on the partitioning results. This solves the problem that current vehicle thermal damage testing methods, which are difficult to cover in all environments due to large differences in factors such as geography, optimize the thermal damage test, reduce the test intensity, are closer to users, avoid development redundancy, reduce development costs, and have a wider range of adaptability.

Description

Technical Field

[0001] The present application relates to the field of data extraction and calculation technology, and in particular to a method, device, electronic device and storage medium for calculating heat damage working condition data. Background Art

[0002] The heat damage test is an important vehicle performance test process in the development of the entire vehicle. It mainly assesses the temperature resistance of electronic components, plastic parts, sound insulation cotton and other parts near the heat source in the cabin under the vehicle's operating conditions, to ensure that these components will not shorten their service life due to exceeding the operating temperature, or cause problems such as component burnout and spontaneous combustion, which are extremely harmful.

[0003] Among them, the heat damage caused by components can be analyzed from the perspective of heat source. The reasons are as follows: (1) Radiant heat dominates. Components affected by radiant heat have almost no cooling air flowing over their surfaces or have only a very low flow rate; (2) Convective heat dominates. Components affected by convective heat have a high speed and temperature of hot air flowing over their surfaces; (3) Combined effects of radiant heat and convective heat. In the engine compartment, the heat damage caused by most components is due to the simultaneous influence of radiation and convection, with the two having an equal proportion.

[0004] Therefore, most automakers have developed their own thermal damage testing methods based on specific vehicle usage scenarios, and these methods vary widely. However, due to my country's vast territory and the significant differences in climate conditions and geographical factors across regions, existing thermal damage testing methods struggle to cover all environments. Furthermore, due to a lack of user data and distribution of high-load operating conditions, they cannot accurately match thermal damage test conditions (slope, speed, torque, etc.), resulting in the risk of insufficient or excessive thermal damage verification. Summary of the Invention

[0005] The present application provides a method, device, electronic device and storage medium for calculating thermal damage operating condition data, which solves the problem that current vehicle thermal damage testing methods are difficult to cover all environmental tests due to large differences in factors such as geography. It optimizes thermal damage tests, reduces test intensity, is closer to users, avoids development redundancy, reduces development costs, and has a wider range of adaptability.

[0006] The first aspect of the present application provides a method for calculating heat damage working condition data, including the following steps: obtaining original driving data of multiple sample vehicles in multiple preset environments, and establishing a signal intermediate table based on the original driving data; based on the signal intermediate table, screening out multiple target vehicles that meet preset conditions, and obtaining the first longitude and latitude of each target vehicle every day; based on the first longitude and latitude of each target vehicle every day, partitioning the signal intermediate table according to preset business dates, and obtaining the heat damage working condition data of the multiple target vehicles according to the partitioning results.

[0007] Based on the above technical means, the problem that the current vehicle thermal damage test method is difficult to cover all environmental tests due to large differences in factors such as geography has been solved. The thermal damage test has been optimized, the test intensity has been reduced, it is closer to users, development redundancy has been avoided, development costs have been reduced, and the adaptability range is wider.

[0008] Furthermore, the raw driving data includes at least one of vehicle model, driving time, geographic location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type.

[0009] According to the above technical means, by obtaining the original driving data of the vehicle, the obtained heat damage data is made more accurate.

[0010] Furthermore, based on the signal intermediate table, multiple target vehicles that meet the preset conditions are screened out, including: screening out the maximum value of the cumulative driving time that meets the preset conditions from the signal intermediate table; based on the maximum value of the cumulative driving time of the preset conditions, sorting the original driving data in the signal intermediate table according to a preset sorting strategy, and taking the first preset number of vehicles in the sorting results as the multiple target vehicles.

[0011] According to the above technical means, by obtaining the maximum value of the vehicle's cumulative driving time, the test intensity and test cost are reduced, the running performance is optimized, and the time labeling in the outer layer is more accurate.

[0012] Furthermore, the method of filtering out the maximum value of the cumulative driving time that meets the preset conditions from the signal intermediate table includes: obtaining the vehicle speed signal from the signal intermediate table; marking the continuous rows and the end rows of the time period based on the time difference and time continuity of the vehicle speed signal, and calculating the moving average of the vehicle speed based on the continuous rows and the end rows of the time period; marking the moving average in the preset vehicle speed range, and obtaining the end time based on the timestamp corresponding to the marking result, obtaining the start time based on the preset lead function and the end time, and obtaining the maximum value of the cumulative driving time that meets the preset conditions based on the start time and the end time.

[0013] According to the above technical means, by calculating the moving average, the efficiency of data extraction is improved and the accuracy of heat damage data is ensured.

[0014] Further, the multiple preset environments include first to fourth preset environments, wherein the first preset scenario is that the speed of the sample vehicle is greater than the first preset speed; the second preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than or equal to the first preset slope value, and the slope value of the sample vehicle is less than or equal to the second preset slope value, wherein the third preset speed is less than the first preset speed; the third preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than the second preset slope value; the fourth preset scenario is that the speed of the sample vehicle is less than or equal to the fourth preset speed, and the slope value of the sample vehicle is greater than the third preset slope value, wherein the fourth preset speed is less than the second preset speed, and the third preset slope value is greater than or equal to the second preset slope value.

[0015] According to the above technical means, by limiting the driving environment of the vehicle, the obtained heat damage data can be made more accurate.

[0016] Furthermore, after obtaining the thermal damage working condition data of the multiple target vehicles according to the partitioning results, it also includes: generating improvement suggestions for each target vehicle according to the thermal damage working condition data of the multiple target vehicles; and sending the improvement suggestions for each target vehicle to a preset mobile terminal.

[0017] The above technical means can facilitate developers to improve the thermal damage conditions of vehicles.

[0018] The second aspect of the present application provides a device for calculating heat damage working condition data, including: a first acquisition module, used to obtain original driving data of multiple sample vehicles in multiple preset environments, and establish a signal intermediate table based on the original driving data; a screening module, used to screen out multiple target vehicles that meet preset conditions based on the signal intermediate table, and obtain the first longitude and latitude of each target vehicle every day; a second acquisition module, used to partition the signal intermediate table according to preset business dates based on the first longitude and latitude of each target vehicle every day, and obtain the heat damage working condition data of the multiple target vehicles according to the partitioning results.

[0019] Furthermore, the raw driving data includes at least one of vehicle model, driving time, geographic location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type.

[0020] Furthermore, the screening module is also used to: screen out the maximum value of the cumulative driving time that meets the preset conditions from the signal intermediate table; based on the maximum value of the cumulative driving time of the preset conditions, sort the original driving data in the signal intermediate table according to a preset sorting strategy, and use the first preset number of vehicles in the sorting results as the multiple target vehicles.

[0021] Furthermore, the maximum value of the cumulative driving time that meets the preset conditions is filtered out from the signal intermediate table, and the filtering module is also used to: obtain the vehicle speed signal from the signal intermediate table; mark the continuous rows and the end rows of the time period based on the time difference and time continuity of the vehicle speed signal, and calculate the moving average of the vehicle speed based on the continuous rows and the end rows of the time period; mark the moving average in the preset vehicle speed range, and obtain the end time according to the timestamp corresponding to the marking result, obtain the start time based on the preset lead function and the end time, and obtain the maximum value of the cumulative driving time that meets the preset conditions according to the start time and the end time.

[0022] Further, the multiple preset environments include first to fourth preset environments, wherein the first preset scenario is that the speed of the sample vehicle is greater than the first preset speed; the second preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than or equal to the first preset slope value, and the slope value of the sample vehicle is less than or equal to the second preset slope value, wherein the third preset speed is less than the first preset speed; the third preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than the second preset slope value; the fourth preset scenario is that the speed of the sample vehicle is less than or equal to the fourth preset speed, and the slope value of the sample vehicle is greater than the third preset slope value, wherein the fourth preset speed is less than the second preset speed, and the third preset slope value is greater than or equal to the second preset slope value.

[0023] Furthermore, after obtaining the thermal damage working condition data of the multiple target vehicles according to the partitioning results, the second acquisition module is also used to: generate improvement suggestions for each target vehicle according to the thermal damage working condition data of the multiple target vehicles; and send the improvement suggestions for each target vehicle to a preset mobile terminal.

[0024] A third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating thermal damage operating condition data as described in the above embodiment.

[0025] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the method for calculating thermal damage operating condition data as described in the above embodiment.

[0026] This application obtains raw driving data from multiple sample vehicles in multiple preset environments, establishes a signal intermediate table based on the raw driving data, screens out multiple target vehicles that meet preset conditions, and obtains the initial latitude and longitude of each target vehicle each day. Based on the initial latitude and longitude of each target vehicle each day, the signal intermediate table is partitioned according to preset business dates, and the partitioning results are used to obtain thermal damage condition data for multiple target vehicles. This solves the problem that current vehicle thermal damage testing methods, which are difficult to cover in all environments due to large differences in factors such as geography, optimizes thermal damage testing, reduces test intensity, is more user-friendly, avoids development redundancy, reduces development costs, and has a wider range of adaptability.

[0027] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0029] Figure 1 This is a flow chart of a method for calculating heat damage condition data according to an embodiment of the present application;

[0030] Figure 2 Flowchart of a method for calculating heat damage condition data according to one embodiment of the present application;

[0031] Figure 3 1 is a block diagram of a device for calculating heat damage working condition data according to an embodiment of the present application;

[0032] Figure 4 Schematic diagram of the structure of an electronic device according to an embodiment of the present application.

[0033] Explanation of the reference numerals: 10 - heat damage working condition data calculation device, 100 - first acquisition module, 200 - screening module, 300 - second acquisition module, 401 - memory, 402 - processor, 403 - communication interface. DETAILED DESCRIPTION

[0034] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0035] The following describes, with reference to the accompanying drawings, a method, device, electronic device, and storage medium for calculating thermal damage condition data according to an embodiment of the present application. To address the problem mentioned in the background art above that current vehicle thermal damage testing methods are difficult to cover in all environments due to significant differences in factors such as geography, the present application provides a method for calculating thermal damage condition data. In this method, raw driving data of multiple sample vehicles in multiple preset environments is obtained, and a signal intermediate table is established based on the raw driving data. Multiple target vehicles that meet preset conditions are screened, and the initial longitude and latitude of each target vehicle are obtained daily. Based on the initial longitude and latitude of each target vehicle daily, the signal intermediate table is partitioned according to preset business dates, and thermal damage condition data for multiple target vehicles is obtained based on the partitioning results. This solves the problem that current vehicle thermal damage testing methods are difficult to cover in all environments due to significant differences in factors such as geography. This method provides a distribution of user driving characteristics under different operating conditions, optimizes thermal damage testing, reduces test intensity, is more user-friendly, avoids development redundancy, reduces development costs, and has a wider range of adaptability.

[0036] Among them, the embodiment of the present application is completed through the Hive SQL tool. Hive is a data warehouse infrastructure based on Apache Hadoop. It is a data warehouse-based application tool used to process structured data in Hadoop. It is built on top of Hadoop and operates on data through SQL, allowing users to easily perform timely queries, summaries and data analysis. Hive SQL, namely HiveQL, is a SQL dialect provided by Hive. The Hive query operation process strictly adheres to the Hadoop MapReduce job execution model. Hive converts the user's Hive SQL statement into a MapReduce job through the interpreter and submits it to the Hadoop cluster. Hadoop monitors the job execution process and then returns the job execution results to the user. Compared with Impala, Hql is more accurate, faster and more suitable for big data research and development.

[0037] Specifically, Figure 1 This is a flow chart of a method for calculating heat damage condition data provided in an embodiment of the present application.

[0038] like Figure 1 As shown, the heat damage condition data calculation method includes the following steps:

[0039] In step S101 , original driving data of a plurality of sample vehicles in a plurality of preset environments are obtained, and a signal intermediate table is established based on the original driving data.

[0040] In some embodiments, the raw driving data includes at least one of vehicle model, driving time, geographic location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type.

[0041] Among them, before obtaining the original driving data of multiple preset environments, the embodiment of the present application needs to determine the test route of the sample vehicle. It can select one road in each characteristic area as the test route, or it can select multiple roads in each characteristic area as the test route. The selection rules are flexibly specified according to needs. The road conditions in the test include temperature, humidity, altitude and slope. In actual situations, roads are composed of multiple sections. In order to ensure the accuracy of road condition collection, for roads in the same characteristic area, the embodiment of the present application collects the temperature, humidity, altitude and slope of each section. The vehicle driving environment includes vehicle speed, acceleration and deceleration, slope and driving time. The vehicle status includes vehicle load and the status of on-board electrical appliances. Among them, the vehicle climbing condition includes low-speed climbing condition and high-speed climbing condition. The vehicle uniform speed driving condition includes uniform speed driving condition on highways and uniform speed driving condition on suburban roads.

[0042] Further, in some embodiments, the multiple preset environments include first to fourth preset environments, wherein the first preset scenario is that the speed of the sample vehicle is greater than the first preset speed; the second preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than or equal to the first preset slope value, and the slope value of the sample vehicle is less than or equal to the second preset slope value, wherein the third preset speed is less than the first preset speed; the third preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than the second preset slope value; the fourth preset scenario is that the speed of the sample vehicle is less than or equal to the fourth preset speed, and the slope value of the sample vehicle is greater than the third preset slope value, wherein the fourth preset speed is less than the second preset speed, and the third preset slope value is greater than or equal to the second preset slope value.

[0043] It should be understood that when the sample vehicle is in a high-speed operating condition (i.e., the first preset scenario), at this time, the speed of the sample vehicle is greater than the first preset speed, i.e., V ≥ 140 km / h. The raw driving data obtained in the embodiment of the present application includes the vehicle model, driving time, geographical location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque, and road type of the sample vehicle;

[0044] When the sample vehicle is in high-speed climbing condition 1 (i.e., the second preset scenario), at this time, the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than or equal to the first preset slope value, that is, 90≤V≤120km / h and the slope 1%≤ΔP≤5%, the vehicle model, driving time, geographical location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type of the sample vehicle are obtained;

[0045] When the sample vehicle is in high-speed climbing condition 2 (i.e., the third preset scenario), at this time, the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than the second preset slope value, that is, 90≤V≤120km / h and the slope ΔP>5%, the vehicle model, driving time, geographical location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque, and road type of the sample vehicle are obtained;

[0046] When the sample vehicle is in a low-speed climbing condition (i.e., the fourth preset scenario), at this time, the speed of the sample vehicle is less than or equal to the fourth preset speed, and the slope value of the sample vehicle is greater than the third preset slope value, that is, V≤70km / h and the slope ΔP≥7%, the vehicle model, driving time, geographical location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type of the sample vehicle are obtained.

[0047] Furthermore, the embodiment of the present application establishes a signal intermediate table tmax_ESP_VehicleSpeed_5_2 based on the original driving data, and creates a sample vehicle VIN code, login time, login timestamp, vehicle entry time, vehicle entry timestamp, maximum duration, and partition date field through the table creation statement create table.

[0048] In step S102, based on the signal intermediate table, multiple target vehicles that meet the preset conditions are screened out, and the first latitude and longitude of each target vehicle per day are obtained.

[0049] Furthermore, in some embodiments, based on the signal intermediate table, multiple target vehicles that meet preset conditions are screened out, including: screening out the maximum value of the cumulative driving time that meets the preset conditions from the signal intermediate table; based on the maximum value of the cumulative driving time of the preset conditions, sorting the original driving data in the signal intermediate table according to a preset sorting strategy, and taking the first preset number of vehicles in the sorting results as multiple target vehicles.

[0050] Specifically, the embodiment of the present application filters out the maximum value (i.e., Tmax) of the cumulative driving time T of all vehicles that meet the preset conditions in each sample month from the signal intermediate table, and sorts the original driving number according to the preset sorting strategy (i.e., descending order) according to the Tmax size of all sample vehicles of the statistical model, and obtains the original driving data of the first preset number of vehicles of the model (i.e., the first 1,000 vehicles) sorted by time series (aligned by seconds) during the period.

[0051] Where T is defined as follows:

[0052] T: In the i-th time period (determined according to the following algorithm), the time signal value corresponding to the beginning of the section is Ti-1, and the time signal value corresponding to the end of the section is Ti

[0053] For any road section, if T0 = Tm - Tn = 300 seconds and the average vehicle speed in the section is ≥ 140 km / h;

[0054] T1 = Tm+1 - Tn+1 = 300, and the average speed in the section is ≥ 140 km / h;

[0055] T2 = Tm + 2 - Tn + 2 = 300, and the average speed in the section is ≥ 140 km / h;

[0056] Ti = Tm + i - Tn + i = 300, and the average speed of vehicles in the road section is ≥ 140 km / h;

[0057] Ti+1=Tm+i+1-Tn+i+1=300, and the average speed in the section is ≥140km / h;

[0058] Then the continuous driving time T=Tm+i-Tn

[0059] The starting point of the next statistical section starts from Tm+i (ie, the next statistical section is Tm+i to Tm+i+300).

[0060] Among them, in some embodiments, the maximum value of the cumulative driving time that meets the preset conditions is screened out from the signal intermediate table, including: obtaining the vehicle speed signal from the signal intermediate table; marking the continuous rows and the end rows of the time period based on the time difference and time continuity of the vehicle speed signal, and calculating the moving average of the vehicle speed based on the continuous rows and the end rows of the time period; marking the moving average in the preset vehicle speed range, and obtaining the end time according to the timestamp corresponding to the marking result, obtaining the start time based on the preset lead function and the end time, and obtaining the maximum value of the cumulative driving time that meets the preset conditions according to the start time and the end time.

[0061] Specifically, if Figure 2As shown, the embodiment of the present application obtains the vehicle speed signal from the ODS raw signal intermediate table. The lead() window analysis function shifts down one row to obtain lead_time, obtains the previous time, and calculates the time difference of the vehicle speed signal. A certain number of rows, for example 5000, are further selected to determine time continuity. If the difference between the previous time and the current time is less than or equal to 50 seconds and greater than or equal to 0, it is marked as y; otherwise, it is marked as n. The result is named cnt_time, and the vehicle speed is taken as 0-360 km / h. Further, the lag analysis window function is used to shift the timestamp ant_time upward to obtain lag_cnt_time, and the situation when cnt_time = y and lag_cnt_time is also y is obtained. The continuous rows and the end rows of the time period are marked, and the end row of the continuous time period and the second-to-last row are taken to shift the moving average of the vehicle speed forward by 4 rows. The rows with the moving average speed between 90-120 (that is, the preset vehicle speed range) are marked, and the timestamp is taken as the end time, marked as tag0, and the preset lead function is used to move the timestamp forward to obtain the previous time, marked as tag2, and recorded as the start time. The difference between the upward shifted end time and the start time is obtained to obtain the maximum time Tmax, and the obtained Tmax time difference is sorted in descending order for each vehicle to obtain the maximum duration of each vehicle, and 1,000 vehicles that meet the conditions are randomly selected as target vehicles.

[0062] In step S103, based on the first longitude and latitude of each target vehicle every day, the signal intermediate table is partitioned according to the preset business date, and the thermal damage working condition data of multiple target vehicles are obtained according to the partition results.

[0063] It should be understood that the embodiment of the present application associates the Tmax table with the latitude and longitude signal table through the day partition field and the VIN code to obtain the first latitude and longitude of each target vehicle every day, and establishes a "demand signal extraction" table to record "VIN code", "vehicle series", "login time", "vehicle entry time", "vehicle exit time", "signal name", and "signal value", and partitions them according to the business date, and obtains the thermal damage working condition data of multiple target vehicles based on the partition results.

[0064] Furthermore, in some embodiments, after obtaining the thermal damage working condition data of multiple target vehicles according to the partitioning results, it also includes: generating improvement suggestions for each target vehicle according to the thermal damage working condition data of the multiple target vehicles; and sending the improvement suggestions for each target vehicle to a preset mobile terminal.

[0065] The preset mobile terminal may be a mobile phone, a tablet, a computer or other display device with a display function.

[0066] It can be understood that after the embodiment of the present application obtains the thermal damage operating condition data of multiple target vehicles, it generates the causes of thermal damage and improvement suggestions for each target vehicle based on the thermal damage operating condition data of multiple target vehicles, and sends the improvement suggestions to the preset mobile terminal of the relevant maintenance personnel, so as to facilitate the relevant technical personnel to improve the vehicle based on the improvement suggestions and the causes of thermal damage.

[0067] According to the thermal damage condition data calculation method proposed in the embodiments of the present application, raw driving data of multiple sample vehicles in multiple preset environments is obtained. A signal intermediate table is established based on the raw driving data, multiple target vehicles that meet preset conditions are screened, and the initial longitude and latitude of each target vehicle are obtained each day. Based on the initial longitude and latitude of each target vehicle each day, the signal intermediate table is partitioned according to preset business dates, and the thermal damage condition data of the multiple target vehicles is obtained based on the partitioning results. This solves the problem that current vehicle thermal damage testing methods, which have difficulty covering all environments due to large differences in factors such as geography, provide a distribution of user driving characteristics under different operating conditions, optimize thermal damage testing, reduce test intensity, are more user-friendly, avoid development redundancy, reduce development costs, and have a wider range of adaptability.

[0068] Next, a heat damage operating condition data calculation device proposed in an embodiment of the present application will be described with reference to the accompanying drawings.

[0069] Figure 3 It is a block diagram of a device for calculating heat damage working condition data according to an embodiment of the present application.

[0070] like Figure 3 As shown, the heat damage working condition data calculation device 10 includes: a first acquisition module 100, a screening module 200 and a second acquisition module 300.

[0071] Among them, the first acquisition module 100 is used to obtain the original driving data of multiple sample vehicles in multiple preset environments, and establish a signal intermediate table based on the original driving data; the screening module 200 is used to screen out multiple target vehicles that meet the preset conditions based on the signal intermediate table, and obtain the first longitude and latitude of each target vehicle every day; the second acquisition module 300 is used to partition the signal intermediate table according to the preset business date based on the first longitude and latitude of each target vehicle every day, and obtain the thermal damage working condition data of multiple target vehicles according to the partitioning results.

[0072] Furthermore, in some embodiments, the raw driving data includes at least one of vehicle model, driving time, geographic location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type.

[0073] Furthermore, in some embodiments, the screening module 200 is also used to: screen out the maximum value of the cumulative driving time that meets the preset conditions from the signal intermediate table; sort the original driving data in the signal intermediate table according to a preset sorting strategy based on the maximum value of the cumulative driving time that meets the preset conditions, and use the first preset number of vehicles in the sorting results as multiple target vehicles.

[0074] Furthermore, in some embodiments, the maximum value of the cumulative driving time that meets the preset conditions is filtered out from the signal intermediate table, and the filtering module 200 is also used to: obtain the vehicle speed signal from the signal intermediate table; mark the continuous rows and the end rows of the time period based on the time difference and time continuity of the vehicle speed signal, and calculate the moving average of the vehicle speed based on the continuous rows and the end rows of the time period; mark the moving average in the preset vehicle speed range, and obtain the end time according to the timestamp corresponding to the marking result, obtain the start time based on the preset lead function and the end time, and obtain the maximum value of the cumulative driving time that meets the preset conditions according to the start time and the end time.

[0075] Further, in some embodiments, the multiple preset environments include first to fourth preset environments, wherein the first preset scenario is that the speed of the sample vehicle is greater than the first preset speed; the second preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than or equal to the first preset slope value, and the slope value of the sample vehicle is less than or equal to the second preset slope value, wherein the third preset speed is less than the first preset speed; the third preset scenario is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than the second preset slope value; the fourth preset scenario is that the speed of the sample vehicle is less than or equal to the fourth preset speed, and the slope value of the sample vehicle is greater than the third preset slope value, wherein the fourth preset speed is less than the second preset speed, and the third preset slope value is greater than or equal to the second preset slope value.

[0076] Furthermore, in some embodiments, after obtaining thermal damage condition data for multiple target vehicles based on the partitioning results, the second acquisition module 300 is further configured to: generate improvement recommendations for each target vehicle based on the thermal damage condition data for the multiple target vehicles; and transmit the improvement recommendations for each target vehicle to a predetermined mobile terminal. This solves the problem that current vehicle thermal damage testing methods, which are difficult to cover in all environments due to significant variations in geography and other factors, provide a distribution of user driving characteristics under different operating conditions, optimize thermal damage testing, reduce test intensity, and provide greater user responsiveness, avoid development redundancy, lower development costs, and achieve wider adaptability.

[0077] It should be noted that the above explanation of the embodiment of the heat damage working condition data calculation method is also applicable to the heat damage working condition data calculation device of this embodiment, and will not be repeated here.

[0078] The thermal damage condition data calculation device proposed in the embodiments of the present application obtains raw driving data from multiple sample vehicles in multiple preset environments. Based on the raw driving data, a signal intermediate table is established, multiple target vehicles that meet preset conditions are screened, and the initial longitude and latitude of each target vehicle are obtained each day. Based on the initial longitude and latitude of each target vehicle each day, the signal intermediate table is partitioned according to preset business dates, and the thermal damage condition data for the multiple target vehicles is obtained based on the partitioning results. This solves the problem that current vehicle thermal damage testing methods, which are difficult to cover in all environments due to significant differences in geography and other factors, optimize thermal damage testing, reduce test intensity, become more user-friendly, avoid development redundancy, reduce development costs, and achieve a wider range of adaptability.

[0079] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0080] Memory 401 , processor 402 , and computer programs stored in the memory 401 and executable on the processor 402 .

[0081] When the processor 402 executes the program, the heat damage working condition data calculation method provided in the above embodiment is implemented.

[0082] Furthermore, the electronic device further includes:

[0083] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0084] The memory 401 is used to store computer programs that can be run on the processor 402 .

[0085] The memory 401 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0086] If the memory 401, the processor 402, and the communication interface 403 are implemented independently, the communication interface 403, the memory 401, and the processor 402 can be connected to each other via a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0087] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0088] The processor 402 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0089] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for calculating thermal damage condition data.

[0090] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0091] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0092] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0093] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0094] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0095] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for calculating heat damage working condition data, characterized in that: The following steps are involved: Acquire raw driving data of multiple sample vehicles in multiple preset environments, and establish a signal intermediate table based on the raw driving data; Based on the signal intermediate table, multiple target vehicles that meet preset conditions are screened out, and the initial latitude and longitude of each target vehicle per day is obtained; as well as Based on the first longitude and latitude of each target vehicle every day, the signal intermediate table is partitioned according to a preset business date, and the thermal damage working condition data of the multiple target vehicles are obtained according to the partition result; The method of screening out a plurality of target vehicles that meet preset conditions based on the signal intermediate table includes: Filtering out the maximum value of the accumulated driving time that meets the preset conditions from the signal intermediate table; The step of filtering out the maximum value of the accumulated driving time that meets the preset conditions from the intermediate signal table includes: Obtaining a vehicle speed signal from the signal intermediate table; marking the continuous lines and the time period end lines based on the time difference and time continuity of the vehicle speed signal, and calculating a moving average of the vehicle speed based on the continuous lines and the time period end lines; The moving average value in the preset vehicle speed range is marked, and the end time is obtained according to the timestamp corresponding to the marking result, the start time is obtained based on the preset lead function and the end time, and the maximum value of the cumulative driving time that meets the preset conditions is obtained according to the start time and the end time.

2. The method according to claim 1, characterized in that The raw driving data includes at least one of vehicle model, driving time, geographic location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type.

3. The method according to claim 1 or 2, characterized in that The method of screening out a plurality of target vehicles that meet preset conditions based on the signal intermediate table further includes: Based on the maximum value of the accumulated driving time of the preset condition, the original driving data in the signal intermediate table is sorted according to a preset sorting strategy, and the first preset number of vehicles in the sorting result are used as the multiple target vehicles.

4. The method according to claim 1, wherein The plurality of preset environments include first to fourth preset environments, wherein: The first preset environment is that the speed of the sample vehicle is greater than the first preset speed; The second preset environment is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than or equal to the first preset slope value, and the slope value of the sample vehicle is less than or equal to the second preset slope value, wherein the third preset speed is less than the first preset speed; The third preset environment is that the speed of the sample vehicle is greater than or equal to the second preset speed, the speed of the sample vehicle is less than or equal to the third preset speed, and the slope value of the sample vehicle is greater than the second preset slope value; The fourth preset environment is that the speed of the sample vehicle is less than or equal to the fourth preset speed, and the slope value of the sample vehicle is greater than the third preset slope value, wherein the fourth preset speed is less than the second preset speed, and the third preset slope value is greater than or equal to the second preset slope value.

5. The method according to claim 1, wherein After obtaining the thermal damage working condition data of the plurality of target vehicles according to the partitioning result, the method further includes: generating improvement suggestions for each target vehicle based on the thermal damage working condition data of the plurality of target vehicles; Sending the improvement suggestions for each target vehicle to a preset mobile terminal.

6. A device for calculating heat damage condition data, characterized in that: include: A first acquisition module is used to acquire original driving data of multiple sample vehicles in multiple preset environments, and to establish a signal intermediate table based on the original driving data; A screening module is used to screen out multiple target vehicles that meet preset conditions based on the signal intermediate table, and obtain the initial longitude and latitude of each target vehicle every day; as well as A second acquisition module is configured to partition the signal intermediate table according to a preset business date based on the first longitude and latitude of each target vehicle every day, and obtain the thermal damage working condition data of the multiple target vehicles according to the partitioning result; The method of screening out a plurality of target vehicles that meet preset conditions based on the signal intermediate table includes: Filtering out the maximum value of the accumulated driving time that meets the preset conditions from the signal intermediate table; The step of filtering out the maximum value of the accumulated driving time that meets the preset conditions from the intermediate signal table includes: Obtaining a vehicle speed signal from the signal intermediate table; marking the continuous lines and the time period end lines based on the time difference and time continuity of the vehicle speed signal, and calculating a moving average of the vehicle speed based on the continuous lines and the time period end lines; The moving average value in the preset vehicle speed range is marked, and the end time is obtained according to the timestamp corresponding to the marking result, the start time is obtained based on the preset lead function and the end time, and the maximum value of the cumulative driving time that meets the preset conditions is obtained according to the start time and the end time.

7. The device according to claim 6, characterized in that The raw driving data includes at least one of vehicle model, driving time, geographic location, ambient temperature, engine coolant temperature, engine intake temperature, mileage, driving speed, driving gear, speed, torque and road type.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating heat damage operating condition data according to any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for calculating heat damage operating condition data according to any one of claims 1 to 5.

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