A vehicle working condition data acquisition method and device

Abstract

The application provides a vehicle working condition data acquisition method and device, comprising: dividing Internet of Vehicles data into multiple data segments, each data segment corresponding to a work cycle; dividing the data segments into multiple road profile segments and determining the work cycle to which the road profile segment belongs to obtain work cycle information including the multiple road profile segments; obtaining the road slope of each road profile segment; and based on the road slope of each road profile segment and a preset vehicle dynamics equation, obtaining the vehicle load of the road profile segment, wherein the vehicle working condition data includes the work cycle information, the road slope and the vehicle load, so as to improve the integrity of the vehicle working condition data as much as possible without additional sensor devices.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of vehicles, and particularly relates to a vehicle working condition data acquisition method and device. BACKGROUND

[0002] In market economy analysis, power performance analysis, user driving habit analysis and product development process in the field of vehicles, vehicle working condition data is crucial. Vehicle working condition data includes work cycle information, vehicle load, road slope, average vehicle speed, vehicle speed standard deviation, and average altitude. How to identify vehicle working condition data is a difficult problem to be solved at present. SUMMARY

[0003] Therefore, the present application aims to provide a vehicle working condition data acquisition method for acquiring work cycle information, road slope and vehicle load in vehicle working condition data, so as to improve the integrity of vehicle working condition data without increasing cost. The technical solution is as follows:

[0004] In the first aspect, the present application provides a vehicle working condition data acquisition method, which comprises:

[0005] Dividing the Internet of Vehicles data into multiple data segments, each data segment corresponding to a work cycle;

[0006] Dividing the data segments into multiple road profile segments, and determining the work cycle to which the road profile segments belong, so as to obtain work cycle information including multiple road profile segments;

[0007] Obtaining the road slope of each road profile segment;

[0008] Based on the road slope of each road profile segment and a preset vehicle dynamics equation, obtaining the vehicle load of the road profile segment, wherein the vehicle working condition data comprises the work cycle information, the road slope and the vehicle load.

[0009] Optionally, the obtaining of the vehicle load based on the road slope of each road profile segment and the preset vehicle dynamics equation comprises:

[0010] Determining a stable working condition point in the road profile segment, wherein the stable working condition point is a working condition point with stable acceleration and uniform speed;

[0011] Based on the vehicle speed, torque and rotating speed in the stable working condition point, calculating the average acceleration, average torque, average value of the rotating speed and vehicle speed ratio of the stable working condition point, wherein the Internet of Vehicles data comprises the vehicle speed, torque and rotating speed;

[0012] obtaining vehicle load of the stable working condition point based on average acceleration, average torque, average value of the ratio of speed and rotation speed, the road slope and the preset vehicle dynamics equation, the vehicle load of the stable working condition point being the undetermined vehicle load of the road spectrum segment;

[0013] obtaining the vehicle load of the road spectrum segment based on the undetermined vehicle load of a plurality of road spectrum segments.

[0014] Optionally, the determining the stable working condition point in the road spectrum segment comprises:

[0015] determining the first segment as an acceleration stable working condition point when the atmospheric pressure in the first segment does not change, the acceleration in the first segment is greater than a first acceleration threshold and the acceleration deviation is less than a first acceleration deviation threshold, the torque in the first segment is greater than a first torque value and the torque deviation is less than a first torque deviation threshold, the accelerator pedal opening degree in the first segment is greater than a first opening degree threshold, and the deviation of the ratio of speed and rotation speed in the first segment is less than a first deviation threshold, the first segment being a road segment in a preset time period in the road spectrum segment, the Internet of Vehicles data comprising atmospheric pressure and accelerator pedal opening degree;

[0016] determining the first segment as a constant speed stable working condition point when the atmospheric pressure in the first segment does not change, the speed deviation in the first segment is greater than a first speed deviation threshold, the accelerator pedal opening degree in the first segment is greater than a second opening degree threshold, the torque deviation in the first segment is less than a second torque deviation threshold, and the deviation of the ratio of speed and rotation speed in the first segment is less than a second deviation threshold, the stable working condition point comprising the acceleration stable working condition point and the constant speed stable working condition point.

[0017] Optionally, the preset vehicle dynamics equation is related to acceleration, torque, ratio of speed and rotation speed, gravitational acceleration, road slope, speed, moment of inertia, transmission system efficiency, air resistance coefficient, vehicle wind area and rolling friction resistance coefficient.

[0018] Optionally, the obtaining the vehicle load of the road spectrum segment based on the undetermined vehicle load of a plurality of road spectrum segments comprises:

[0019] eliminating abnormal undetermined vehicle load from the undetermined vehicle load of a plurality of road spectrum segments;

[0020] obtaining the vehicle load of the road spectrum segment based on the remaining undetermined vehicle load in the undetermined vehicle load of a plurality of road spectrum segments;

[0021] The removing of the abnormal pending vehicle load comprises: calculating a standard deviation of all the pending vehicle loads, and removing the pending vehicle load greater than a preset multiple of the standard deviation; or sorting all the pending vehicle loads in ascending order of values, calculating N quantiles of all the pending vehicle loads, and removing the pending vehicle load lower than 1 / N quantile point but higher than (N-1 / N) quantile point, N being a natural number greater than 1.

[0022] Optionally, the method further comprises: obtaining the vehicle load of the data segment based on the vehicle load of the road spectrum segment.

[0023] If the vehicle loads of two adjacent data segments are the same, the two adjacent data segments are merged into one data segment.

[0024] Optionally, the splitting of the Internet of Vehicles data into multiple data segments comprises:

[0025] Determining a work cycle split start point and a work cycle split end point in the Internet of Vehicles data.

[0026] If the work cycle split end points are not interspersed in the multiple work cycle split start points, the multiple work cycle split start points are merged into one work cycle split start point.

[0027] If the work cycle split start points are not interspersed in the multiple work cycle split end points, the multiple work cycle split end points are merged into one work cycle split end point.

[0028] Splitting the Internet of Vehicles data into multiple data segments based on the work cycle split start point and the work cycle split end point.

[0029] Optionally, the determining of the work cycle split start point and the work cycle split end point in the Internet of Vehicles data comprises:

[0030] If the vehicle speed at a current time is equal to a first vehicle speed but the vehicle speed at a next time is greater than the first vehicle speed, the duration in which the vehicle speed is greater than the first vehicle speed in a first preset time period at the current time is greater than a first duration, and the duration in which the rotation speed is less than a first rotation speed in the first preset time period at the current time is less than a second duration, it is determined that the current time is a work cycle split start point.

[0031] If the vehicle speed at a current time is equal to a second vehicle speed but the vehicle speed at a previous time is greater than the second vehicle speed, the duration in which the vehicle speed is greater than the second vehicle speed in a first preset time period at the current time is greater than a third duration or the duration in which the rotation speed is less than a second rotation speed is greater than a fourth duration, it is determined that the current time is a work cycle split end point.

[0032] In the second preset time period at the current time, the average vehicle speed is equal to the third vehicle speed, the average torque is greater than the preset torque, and the average rotation speed is greater than the preset rotation speed, and it is determined that the current time is the end point of the work cycle division.

[0033] Optionally, the dividing the data segment into a plurality of road spectrum segments comprises:

[0034] Obtaining a plurality of atmospheric pressure change points in the data segment;

[0035] If the product of the atmospheric pressure change value of the current atmospheric pressure change point and the atmospheric pressure change value of the previous atmospheric pressure change point is less than a preset pressure change value, the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the previous atmospheric pressure change point is greater than a first mileage difference, or the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the next atmospheric pressure change point is greater than a second mileage difference, the current atmospheric pressure change point is determined as a segment division point.

[0036] Based on the work cycle division start point of the data segment and the segment division point, the data segment is divided into a plurality of road spectrum segments.

[0037] In a second aspect, the present application provides a vehicle working condition data acquisition device, the device comprises:

[0038] A division unit is configured to divide the Internet of Vehicles data into a plurality of data segments, each data segment corresponding to a work cycle, and to divide the data segment into a plurality of road spectrum segments and determine the work cycle to which the road spectrum segment belongs, so as to obtain work cycle information comprising a plurality of road spectrum segments;

[0039] A slope acquisition unit is configured to obtain the road slope of each road spectrum segment;

[0040] A load acquisition unit is configured to obtain the vehicle load of each road spectrum segment based on the road slope of each road spectrum segment and a preset vehicle dynamics equation, and the vehicle working condition data comprises the work cycle information, the road slope and the vehicle load.

[0041] In a third aspect, the present application provides a vehicle working condition data acquisition device, which comprises a processor and a memory, and the memory stores a program which, when executed by the processor, implements the vehicle working condition data acquisition method described above.

[0042] In a fourth aspect, the present application provides a storage medium, which stores a computer program which, when executed by a processor, implements the vehicle working condition data acquisition method described above.

[0043] Compared with the prior art, the above technical solutions provided by the present application have the following advantages:

[0044] The vehicle working condition data acquisition method can acquire the working cycle information, vehicle load and road slope by using the Internet of Vehicles data, so as to improve the completeness of the vehicle working condition data as much as possible without additional sensor devices. In addition, the calculation of the vehicle load is improved, so that the acceleration and torque can be accurately aligned, the error of the acceleration is reduced, and the calculation error of the vehicle load is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0046] Figure 1 is a flowchart of the vehicle working condition data acquisition method provided by the embodiments of the present application;

[0047] Figure 2 is a schematic diagram of the road spectrum segment start point, road spectrum segment end point and atmospheric pressure change point provided by the embodiments of the present application;

[0048] Figure 3 is a schematic diagram of the road spectrum segment start point and road spectrum segment end point provided by the embodiments of the present application;

[0049] Figure 4 is a flowchart of obtaining the vehicle load provided by the embodiments of the present application;

[0050] Figure 5 is another flowchart of the vehicle working condition data acquisition method provided by the embodiments of the present application;

[0051] Figure 6 is a structural schematic diagram of the vehicle working condition data acquisition device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0053] Vehicle working condition data includes work cycle information, vehicle load, road slope, average vehicle speed, vehicle speed standard deviation and average altitude, which plays a crucial role in market economy analysis, power performance analysis, user driving habit analysis and product development process in the field of vehicles. The work cycle information includes a plurality of road profile data in a work scene; the vehicle load is the total mass of the vehicle including the goods, which can also be called the vehicle weight; the road slope records the road slope, which is the percentage of the elevation difference between two points and the mileage difference between the two points. The calculation formula can be road slope = (elevation difference / horizontal distance)*100%, and the horizontal distance represents the mileage difference, and the two points can be two places passed through in the vehicle driving process. Among them, the average vehicle speed, vehicle speed standard deviation and average altitude can be obtained from the Internet of Vehicles data, and the urgent problem to be solved is how to obtain the work cycle, vehicle load and road slope in the vehicle working condition data.

[0054] There are two methods at present: one method is to install a sensor device in the vehicle to obtain vehicle working condition data through the sensor device, which needs to additionally install a sensor device, increases the cost, and the sensor device can only collect the road slope, resulting in incomplete vehicle working condition data; the other way is to obtain vehicle working condition data through data method, which obtains vehicle working condition data including vehicle load and road slope, and the vehicle working condition data is incomplete. In addition, this method uses vehicle speed to extract short cycle segments, and the short cycle segment is a running segment from 0 to 0 of the vehicle speed, and the running time is relatively short, and a work cycle information contains a plurality of short cycle segments (short cycle segments can be called road profile segments). Therefore, this method cannot obtain the work cycle information in the vehicle working condition data. In addition, when obtaining the vehicle load, the method can calculate the vehicle load based on acceleration and other parameters and using vehicle dynamics equation, wherein the acceleration is obtained by using the vehicle speed in the Internet of Vehicles data to calculate and filter an initial acceleration, and the initial acceleration is aligned with the torque of the engine to obtain the acceleration applied to the vehicle dynamics equation. However, due to the limitation of the sampling frequency of the torque, the initial acceleration is difficult to align with the torque, resulting in a large error of the acceleration, thereby causing a large error in the calculation of the vehicle load, which limits the use of the method.

[0055] To this end, the embodiment of the present application provides a vehicle working condition data acquisition method, by which vehicle working condition data is acquired by using Internet of Vehicles data, the acquired vehicle working condition data includes work cycle information, vehicle load and road slope, so as to improve the integrity of the vehicle working condition data as much as possible without additional installation of sensor devices. The Internet of Vehicles data can include engine speed (referred to as speed), engine torque (referred to as torque), vehicle speed, mileage, atmospheric pressure, throttle pedal opening, etc. The Internet of Vehicles data can be collected by a national VI remote terminal, the sampling frequency of the national VI remote terminal can be greater than or equal to 1 Hz (Hertz), the terminal can collect engine related data stream and OBD (On-Board-Diagnose) diagnostic information in real time and upload to the national platform, and the Internet of Vehicles data is downloaded from the national platform when the vehicle working condition data is acquired.

[0056] The vehicle working condition data acquisition method provided by the embodiment of the present application will be described below with reference to the accompanying drawings, Figure 1 A flow of the vehicle working condition data acquisition method provided by the embodiment of the present application is shown, which can include the following steps:

[0057] 101, the Internet of Vehicles data is divided into multiple data segments, each data segment corresponding to a work cycle. It can be understood that: a work cycle indicates a work scene, such as a transportation scene and a loading and unloading scene, etc. The work data in the vehicle working process under different work cycles is recorded in the Internet of Vehicles data, such as the work data at each work time, including vehicle speed, speed, torque, atmospheric pressure, mileage, throttle pedal opening, etc. These work data can be recorded in the Internet of Vehicles data, that is, the Internet of Vehicles data can include vehicle speed, speed, torque, atmospheric pressure, mileage, throttle pedal opening, etc.

[0058] The work data under different work cycles is different, such as the vehicle speed under the transportation scene and the vehicle speed under the loading and unloading scene are different. Therefore, based on the work data included in the Internet of Vehicles data, the data segments corresponding to different work cycles in the Internet of Vehicles data are determined, and the division of the Internet of Vehicles data is completed.

[0059] 102, the data segments are divided into multiple road spectrum segments, and the work cycle to which the road spectrum segment belongs is determined, so as to obtain the work cycle information including multiple road spectrum segments. Among them, because the data segment corresponds to a work cycle, after obtaining the road spectrum segment in the data segment, the work cycle corresponding to the data segment is taken as the work cycle to which the road spectrum segment belongs. The work cycle to which the road spectrum segment belongs can indicate the work scene corresponding to the road spectrum segment, that is, the road spectrum segment under which work scene, by dividing the data segment, multiple road spectrum segments belonging to the same work cycle are obtained, so as to obtain the work cycle information, which includes multiple road spectrum segments belonging to the same work cycle.

[0060] In some examples, the road spectrum segment is obtained by segmenting the data segment based on the segment segmentation points in the data segment. The segment segmentation points can be obtained based on atmospheric pressure and mileage, such as by setting the judgment conditions for the segment segmentation points. The segment segmentation points are obtained when the atmospheric pressure and mileage meet the judgment conditions.

[0061] First, we define three types of feature points: the start point of a road segment, the end point of a road segment, and the point of atmospheric pressure change. If the current time equals the start time of a road segment, then the current time is the start point of the road segment; if the current time equals the end time of a road segment, then the current time is the end point of the road segment. If the difference between the atmospheric pressure at the current time and the atmospheric pressure at the previous time is not equal to 0, i.e., dEnvp(t) ! = 0, where dEnvp(t) = Envp(t) – Envp(t-1), where Envp(t) is the atmospheric pressure at time t, Envp(t-1) is the atmospheric pressure at time t-1, and time t-1 is the time preceding time t.

[0062] The diagrams showing the start and end points of the road spectrum segment and the points of atmospheric pressure change are as follows: Figure 2 As shown, the horizontal axis represents time, in seconds (not limited in this embodiment), and the right vertical axis represents the atmospheric pressure difference, in hPa (hPa). Points where the atmospheric pressure difference is not equal to 0 represent points of atmospheric pressure change. The left vertical axis represents atmospheric pressure, in hPa. Correspondingly, the process of dividing the data segment into multiple road spectrum segments is as follows:

[0063] 1. To obtain multiple atmospheric pressure change points in a data segment, you can use dEnvp(t)! = 0 to obtain the atmospheric pressure change points.

[0064] 2. If the product of the atmospheric pressure change value at the current atmospheric pressure change point and the atmospheric pressure change value at the previous atmospheric pressure change point is less than the preset pressure change value, the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the previous atmospheric pressure change point is greater than the first mileage difference, or the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the next atmospheric pressure change point is greater than the second mileage difference, then the current atmospheric pressure change point is determined as a segmentation point.

[0065] For example, the criteria for determining segmentation points include: 1) pre_delt_dst(T) > threshold 1 or nxt_delt_dst(t) > threshold 2. Where pre_delt_dst(T) = abs(dst(T) - dst(T-1)), nxt_delt_dst(T) = abs(dst(T) – dst(T+1)), dst(T) is the mileage corresponding to the current atmospheric pressure change point, pre_delt_dst(T) is the mileage corresponding to the previous atmospheric pressure change point, nxt_delt_dst(T) is the mileage corresponding to the next atmospheric pressure change point, T indicates that the current atmospheric pressure change point is at time T, T-1 indicates that the previous atmospheric pressure change point is at time T-1, and T+1 indicates that the previous atmospheric pressure change point is at time T+1. Threshold 1 is an example of the first mileage difference, and threshold 2 is an example of the second mileage difference. Threshold 1 and threshold 2 can be the same or different. The settings of threshold 1 and threshold 2 are related to the accuracy of atmospheric pressure. The lower the accuracy of atmospheric pressure, the higher the values ​​of threshold 1 and threshold 2; the higher the accuracy of atmospheric pressure, the lower the values ​​of threshold 1 and threshold 2. 2) f(T)*f(T-1)<0, where f(T) is the atmospheric pressure change value at the current atmospheric pressure change point, and f(T-1) is the atmospheric pressure change value at the previous atmospheric pressure change point. When the above two judgment conditions are met, the current atmospheric pressure change point is determined as the segment segmentation point.

[0066] 3. Based on the start point and segmentation point of the data segment's operation cycle, the data segment is divided into multiple road spectrum segments. For example, if the segmentation point is the start point of the operation cycle, then this segmentation point is also the start point of the road spectrum segment. The next segmentation point is both the end point and the start point of the next road spectrum segment. Thus, the data segmentation is completed using the start and end points of the road spectrum segments. Figure 3 As shown, the start and end points of the road spectrum segment are obtained through steps 2 and 3, and these points are used to segment the data segments. Figure 3 coordinates and Figure 2 The coordinates are the same, so this will not be elaborated further. Figure 2 The main approach involves using operational data (specifically atmospheric pressure) from road spectrum segments to identify atmospheric pressure variation points. After obtaining these points, operational data at these atmospheric pressure variation points is selected from the operational data of the road spectrum segments. The operational data at these atmospheric pressure variation points is then processed according to... Figure 3 The diagram shows how segmentation points are obtained using operational data (specifically, atmospheric pressure and mileage) from points of change in atmospheric pressure. Please refer to the above explanation for details.

[0067] 103、Obtain the road slope of each road profile segment. The road slope of a road profile segment can be obtained based on the atmospheric pressure and mileage of the end point of the road profile segment, the atmospheric pressure and mileage of the start point of the road profile segment. As a feasible way, the road profile segment is obtained based on the following formula:

[0068] wherein, End envp is the atmospheric pressure of the end point of the road profile segment Start envp is the atmospheric pressure of the start point of the road profile segment, End dst is the mileage of the end point of the road profile segment, Start dst is the mileage of the start point of the road profile segment, the unit of atmospheric pressure is hundred pascal, and the unit of mileage is meter.

[0069] 104、Based on the road slope of each road profile segment and the preset vehicle dynamics equation, obtain the vehicle load of the road profile segment, and the vehicle working condition data includes operation cycle information, road slope and vehicle load. One way is to input the road slope of the road profile segment into the preset vehicle dynamics equation, and the preset vehicle dynamics equation outputs the vehicle load of the road profile segment.

[0070] In some examples, the preset vehicle dynamics equation is related to acceleration, torque, speed and speed ratio, gravity acceleration, road slope, vehicle speed, moment of inertia, transmission system efficiency, air resistance coefficient, vehicle wind area and rolling friction resistance coefficient. Among them, the moment of inertia, transmission system efficiency, air resistance coefficient, vehicle wind area and rolling friction resistance coefficient can be selected according to the vehicle type corresponding to the Internet of vehicles data, and these parameters can adopt default values. Acceleration, torque, speed and speed ratio, vehicle speed can be obtained based on the Internet of vehicles data. The derivation process of the preset vehicle dynamics equation is given below:

[0071] According to vehicle theory, when the transmission system is engaged, the relationship between speed and vehicle speed is wherein, u is the vehicle speed (unit: km / h), R is the tire radius (unit: m), n is the engine speed (unit: revolutions / min), i t is the total speed ratio of the transmission system.

[0072] The vehicle longitudinal dynamics formula is δma=F t -F w -F f -F s . Among them, δ is the moment of inertia, m is the vehicle weight, that is, the vehicle load (unit: kg), a is the acceleration (unit: m / s 2 ), F t is the driving force transmitted to the wheel by the engine, F w is the air resistance, F f is the rolling friction resistance, and F sis the slope resistance.

[0073] wherein T is the torque (unit: Nm), i t is the total transmission ratio, η t is the transmission efficiency, R is the tire radius (unit: m).

[0074] wherein C is the air resistance coefficient, A is the vehicle frontal area (unit: m 2 ), u is the vehicle speed (unit: km / h).

[0075] F f = mgf cos a, wherein m is the vehicle weight (unit: kg), g is the gravitational acceleration (unit: 9.8 m / s 2 ), f is the rolling friction resistance coefficient, and a is the road slope.

[0076] F s = mg sin a, wherein m is the vehicle weight (unit: kg), g is the gravitational acceleration (unit: 9.8 m / s 2 ), and a is the road slope.

[0077] By combining the above formulas, the preset vehicle dynamics equation can be obtained, as shown below:

[0078]

[0079] Using the preset vehicle dynamics equation, the vehicle load can be obtained, and there is no need to calculate the total transmission ratio and the tire radius of the whole vehicle. Only the torque, the speed, and the vehicle speed obtained from the Internet of Vehicles data are needed. The acceleration can be calculated from the vehicle speed, and the calculation formula is: the acceleration at the current time = (the vehicle speed at the current time - the vehicle speed at the last time) / 3.6.

[0080] Through the above vehicle working condition data acquisition method, the operation cycle information, the vehicle load, and the road slope can be obtained by using the Internet of Vehicles data, so as to improve the integrity of the vehicle working condition data as much as possible without additional sensor devices.

[0081] In the process of obtaining the vehicle load by using the preset vehicle dynamics equation, the acceleration needs to be input into the preset vehicle dynamics equation. If the acceleration needs to be aligned with the torque, the acceleration error is large due to the limitation of the sampling frequency of the torque, so as to cause a large calculation error of the vehicle load. To solve the problem, the vehicle working condition data acquisition method provided in the embodiments of the present application can improve the calculation of the vehicle load, so that the acceleration and the torque can be accurately aligned, the error of the acceleration is reduced, and the calculation error of the vehicle load is reduced.

[0082] As Figure 4As shown, it shows an optional flow to obtain the vehicle load, which can include the following steps:

[0083] 201, determine a stable working condition point in the road spectrum segment, the stable working condition point is an acceleration stable and constant speed stable working condition point. That is, through the stable working condition point, the road section with stable acceleration (small acceleration change) and stable constant speed (small vehicle speed change) in the road spectrum segment is found, that is, the stable working condition point can correspond to the road section with small engine working condition data change in the road spectrum segment, the engine working condition data including vehicle speed, acceleration and torque, etc.

[0084] In some examples, the stable working condition point includes an acceleration stable working condition point and a constant speed stable working condition point, the acceleration stable working condition point is a working condition point with small acceleration change, if the acceleration change in a preset time period in the road spectrum segment is small, the road section in the preset time period is the acceleration stable working condition point; for the road condition in the preset time period, it can be judged whether the vehicle speed change is small, if the vehicle speed change is small, the road section in the preset time period is the constant speed stable working condition point.

[0085] A feasible way to determine the stable working condition point is: if the atmospheric pressure in the first segment of the road spectrum segment does not change, the acceleration in the first segment is greater than the first acceleration threshold value and the acceleration deviation is less than the first acceleration deviation threshold value, the torque in the first segment is greater than the first torque value and the torque deviation is less than the first torque deviation threshold value, the accelerator pedal opening degree in the first segment is greater than the first opening degree threshold value, and the deviation of the speed and vehicle speed ratio in the first segment is less than the first deviation threshold value, it is determined that the first segment is an acceleration stable working condition point, and the first segment is a road section in a preset time period in the road spectrum segment.

[0086] If the atmospheric pressure in the first segment does not change, the vehicle speed deviation in the first segment is greater than the first vehicle speed deviation threshold value, the accelerator pedal opening degree in the first segment is greater than the second opening degree threshold value, the torque deviation in the first segment is less than the second torque deviation threshold value, and the deviation of the speed and vehicle speed ratio in the first segment is less than the second deviation threshold value, it is determined that the first segment is a constant speed stable working condition point.

[0087] That is, the definitions of the acceleration stable working condition point and the constant speed stable working condition point are as follows:

[0088] Acceleration stable working condition point: a) atmospheric pressure does not change (i.e. no change in altitude, in a flat road section, excluding the influence of road slope) for a continuous period of time; b) acceleration is greater than threshold 1 (an example of a first acceleration threshold) and acceleration deviation is less than threshold 2 (an example of a first acceleration deviation threshold) for a continuous period of time; c) torque is greater than threshold 3 (an example of a first torque value) and torque deviation is less than threshold 4 (an example of a first torque deviation threshold) for a continuous period of time; d) accelerator pedal opening is greater than threshold 5 (an example of a first opening threshold) for a continuous period of time; e) there is no drive train shock, i.e. (speed / vehicle speed) deviation is less than threshold 6 (an example of a first deviation threshold), for a continuous period of time; when these conditions are met, the road section (i.e. the first segment) for the continuous period of time is an acceleration stable working condition point, and the values of the thresholds are not limited.

[0089] Constant speed stable working condition point: a) atmospheric pressure does not change (i.e. no change in altitude, in a flat road section, excluding the influence of road slope) for a continuous period of time; b) vehicle speed deviation is less than threshold 7 (an example of a first vehicle speed deviation threshold) for a continuous period of time; c) accelerator pedal opening is greater than threshold 8 (an example of a second opening threshold) for a continuous period of time; d) torque deviation is less than threshold 9 (an example of a second torque deviation threshold) for a continuous period of time; e) there is no drive train shock, i.e. (speed / vehicle speed) deviation is less than threshold 10 (an example of a second deviation threshold), for a continuous period of time; when these conditions are met, the road section (i.e. the first segment) for the continuous period of time is a constant speed stable working condition point, and the values of the thresholds are not limited.

[0090] 202. Based on the vehicle speed, torque and speed in the stable working condition point, the average acceleration, average torque, average speed and average speed ratio of the stable working condition point are calculated.

[0091] 203. Based on the average acceleration, average torque, average speed and average speed ratio of the stable working condition point, road slope and a preset vehicle dynamics equation, the vehicle load of the stable working condition point is obtained, which is the to-be-determined vehicle load of the road spectrum segment.

[0092] For example, the continuous time period from time t to time n is the acceleration stable operating point and the uniform speed stable operating point, then the average torque is obtained by using all the torques from time t to time n, the average value of the speed and the vehicle speed ratio is obtained by using all the speeds and all the vehicle speeds from time t to time n, and the acceleration at each time from time t to time n is obtained by using the vehicle speed from time t to time n, and then the average acceleration is obtained by using all the accelerations from time t to time n. The average acceleration, the average torque, and the average value of the speed and the vehicle speed ratio are used as the acceleration, the torque, and the speed and the vehicle speed ratio respectively, and the three values are input into the preset vehicle dynamics equation to obtain the vehicle load of the stable operating point.

[0093] The average acceleration and the average torque are parameters in the same road section, and the average acceleration and the average torque can be accurately aligned to improve the accuracy of the average acceleration and the average torque applied to the preset vehicle dynamics equation, thereby improving the accuracy of the vehicle load of the stable operating point. In a road spectrum segment, multiple stable operating points can be extracted, and thus the vehicle load of multiple stable operating points can be obtained in a road spectrum segment.

[0094] 204. Based on the to-be-determined vehicle loads of the multiple road spectrum segments, the vehicle load of the road spectrum segment is obtained. For example, the vehicle load of the road spectrum segment is the average value of all the to-be-determined vehicle loads. In some examples, there may be abnormal values in all the to-be-determined vehicle loads. In order to improve the vehicle load of the road spectrum segment, the abnormal to-be-determined vehicle loads can be removed from the to-be-determined vehicle loads of the multiple road spectrum segments, and then the vehicle load of the road spectrum segment is obtained based on the remaining to-be-determined vehicle loads of the multiple road spectrum segments, for example, the average value of the remaining to-be-determined vehicle loads is the vehicle load of the road spectrum segment.

[0095] The embodiment can use a statistical method to detect and remove abnormal to-be-determined vehicle loads. One way is to calculate the standard deviation of all the to-be-determined vehicle loads, and if the to-be-determined vehicle load is greater than the preset multiple of the standard deviation, for example, the to-be-determined vehicle load is greater than 3 times the standard deviation, then the to-be-determined vehicle load is removed. Another way is to sort all the to-be-determined vehicle loads in ascending order of value, calculate the N quantile of all the to-be-determined vehicle loads, and remove the to-be-determined vehicle loads below the 1 / N quantile point but above the (N-1 / N) quantile point, where N is a natural number greater than 1.

[0096] Through the above Figure 4 The flow shown in the figure can accurately align the acceleration and the torque, reduce the error of the acceleration, and thus reduce the calculation error of the vehicle load.

[0097] Figure 5 Another flow of the vehicle operating condition data acquisition method provided by the embodiment of the application is shown, which can include the following steps:

[0098] 301-304: Same as steps 101-104.

[0099] 305: Obtain the vehicle load of the data segment based on the vehicle load of the road spectrum segment.

[0100] 306: If the vehicle loads of two adjacent data segments are the same, merge the two adjacent data segments into one data segment.

[0101] In the process of segmenting the Internet of Vehicles data, there is a problem that the data segments corresponding to the same work cycle are divided into two parts. For example, in the heavy load distribution scene of a tractor, if the driver temporarily stops for a long time, the data segment under the work cycle will be divided into two parts, which will cause errors in the work cycle information and affect the analysis accuracy. Therefore, after obtaining the vehicle load of the road spectrum segment, the segment merging can be performed based on the vehicle load. The merging rules are as follows:

[0102] If the vehicle loads of two adjacent data segments are the same (i.e., the same), merge the two data segments into one data segment. The vehicle load of the data segment is obtained based on the vehicle load of the road spectrum segment. For example, the mean value of the vehicle loads of all road spectrum segments belonging to one data segment is the vehicle load of the data segment.

[0103] In some examples, one feasible way of segmenting the Internet of Vehicles data includes determining the work cycle segmentation start point and the work cycle segmentation end point in the Internet of Vehicles data, merging the multiple work cycle segmentation start points into one work cycle segmentation start point if there is no work cycle segmentation end point interspersed in the multiple work cycle segmentation start points, merging the multiple work cycle segmentation end points into one work cycle segmentation end point if there is no work cycle segmentation start point interspersed in the multiple work cycle segmentation end points, and segmenting the Internet of Vehicles data into multiple data segments based on the work cycle segmentation start point and the work cycle segmentation end point.

[0104] The work cycle segmentation start point is the start point of the work data belonging to one work cycle in the Internet of Vehicles data, and the work cycle segmentation end point is the end point of the work data belonging to one work cycle in the Internet of Vehicles data. The Internet of Vehicles data is segmented based on the work cycle segmentation start point and the work cycle segmentation end point. For example, the work data at time x is determined as the work cycle segmentation start point, and the work data at time y is determined as the work cycle segmentation end point. Then, the work data from time x to time y can be divided into one data segment. The values of time x and time y are not limited.

[0105] If a plurality of job cycle segmentation start points and a plurality of job cycle segmentation end points can be determined in a piece of vehicle networking data, and the plurality of job cycle segmentation start points are adjacent and continuous (meaning that there is no interlaced job cycle segmentation end point), and the plurality of job cycle segmentation end points are also adjacent and continuous (meaning that there is no interlaced job cycle segmentation start point), then the adjacent and continuous plurality of job cycle segmentation start points are merged into one, and the adjacent and continuous plurality of job cycle segmentation end points are merged into one.

[0106] If the job cycle segmentation start points and the job cycle segmentation end points are time-based, if a plurality of job cycle segmentation start points are adjacent in time, it means that these job cycle segmentation start points are adjacent and continuous; similarly, if a plurality of job cycle segmentation end points are adjacent in time, it means that these job cycle segmentation end points are adjacent and continuous. For example, if job cycle segmentation start point 1, job cycle segmentation start point 2, job cycle segmentation start point 3, job cycle segmentation end point 1, and job cycle segmentation end point 2 are determined to be adjacent in time, then job cycle segmentation start points 1 to 3 are merged, and job cycle segmentation end points 1 to 2 are merged.

[0107] One merging method is to take the minimum time of adjacent job cycle segmentation start points as the job cycle segmentation start point, and to take the maximum time of adjacent job cycle segmentation end points as the job cycle segmentation end point. For example, if the time of job cycle segmentation start point 1 is the minimum, then only job cycle segmentation start point 1 is taken, and job cycle segmentation start point 2 and job cycle segmentation start point 3 are no longer job cycle segmentation start points; if the time of job cycle segmentation end point 2 is the maximum, then only job cycle segmentation end point 2 is taken, and job cycle segmentation end point 1 is no longer a job cycle segmentation end point, and the vehicle networking data is segmented by using job cycle segmentation start point 1 and job cycle segmentation end point 2. That is, when a plurality of job cycle segmentation start points and a plurality of job cycle segmentation end points meet the merging condition (i.e., there is no interlaced segmentation point of different types), the merging in this embodiment means selecting one of the plurality of job cycle segmentation start points, and similarly selecting one of the plurality of job cycle segmentation end points.

[0108] In this embodiment, one feasible way to determine the job cycle segmentation start point and the job cycle segmentation end point is to preset the judgment conditions of the segmentation start point and the judgment conditions of the segmentation end point, and these judgment conditions are related to the vehicle speed, the rotation speed and the torque in the vehicle networking data. When the vehicle speed, the rotation speed and the torque in the vehicle networking data meet these judgment conditions, the job cycle segmentation start point or the job cycle segmentation end point can be determined. The process can be:

[0109] In the current time, the vehicle speed is equal to the first vehicle speed, but the next time the vehicle speed is greater than the first vehicle speed, the vehicle speed is greater than the first vehicle speed for a length of time greater than the first length of time within the first predetermined time period at the current time, and the length of time within the first predetermined time period at the current time is less than the second length of time. The current time is determined as the work cycle segmentation starting point.

[0110] In the current time, the vehicle speed is equal to the second vehicle speed, but the previous time the vehicle speed is greater than the second vehicle speed, the length of time within the first predetermined time period at the current time is greater than the third length of time or the length of time is greater than the fourth length of time. The current time is determined as the work cycle segmentation end point.

[0111] In the second predetermined time period at the current time, the average vehicle speed is equal to the third vehicle speed, and the average torque is greater than the predetermined torque, and the average speed is greater than the predetermined speed. The current time is determined as the work cycle segmentation end point.

[0112] The judgment condition of the segmentation starting point includes: a) the current time vehicle speed is equal to 0km / h (0km / h is an example of the first vehicle speed), the next time the vehicle speed is greater than 0km / h; b) within 3min (3min is an example of the first predetermined time period) at the current time, the vehicle speed is greater than 0km / h for more than 5s (an example of the first length of time); c) within 3min at the current time, the time of the speed below 300r / min (300r / min is an example of the first speed) is less than 5s (5s is an example of the second length of time). When the vehicle speed and speed at the current time meet conditions a, b and c, the current time is determined as the work cycle segmentation starting point.

[0113] The judgment condition of the segmentation end point includes: a) the current time vehicle speed is equal to 0km / h (0km / h is an example of the second vehicle speed), the previous time the vehicle speed is greater than 0km / h; b) the length of time within 3min at the current time is less than 5s (5s is an example of the third length of time) or the length of time is greater than 5s (5s is an example of the fourth length of time). The current time is determined as the work cycle segmentation end point.

[0114] It should be noted here that the job data under different job cycles may have some differences, and different judgment conditions can be set for different job cycles, which will not be described one by one here.

[0115] For the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0116] Corresponding to the above method embodiments, the present embodiment provides a vehicle working condition data acquisition device, the structure of which is as shown in Figure 6 It can include a segmentation unit 10, a slope acquisition unit 20 and a load acquisition unit 30.

[0117] The segmentation unit 10 is used to segment the Internet of Vehicles data into multiple data segments, each data segment corresponding to a job cycle, and to segment the data segments into multiple road profile segments and determine the job cycle to which the road profile segment belongs, to obtain job cycle information including multiple road profile segments.

[0118] In some examples, the process of the segmentation unit 10 segmenting the Internet of Vehicles data into multiple data segments includes: determining the job cycle segmentation start point and the job cycle segmentation end point in the Internet of Vehicles data; if there is no job cycle segmentation end point interspersed in the multiple job cycle segmentation start points, merging the multiple job cycle segmentation start points into one job cycle segmentation start point; if there is no job cycle segmentation start point interspersed in the multiple job cycle segmentation end points, merging the multiple job cycle segmentation end points into one job cycle segmentation end point; and segmenting the Internet of Vehicles data into multiple data segments based on the job cycle segmentation start point and the job cycle segmentation end point.

[0119] Optionally, determining the work cycle split start point and the work cycle split end point in the vehicle networking data comprises: determining the current time as the work cycle split start point when the vehicle speed at the current time is equal to the first vehicle speed but the vehicle speed at the next time is greater than the first vehicle speed, the length of time when the vehicle speed is greater than the first vehicle speed in the first preset time period at the current time is greater than the first length, and the length of time when the rotation speed is less than the first rotation speed in the first preset time period at the current time is less than the second length; determining the current time as the work cycle split end point when the vehicle speed at the current time is equal to the second vehicle speed but the vehicle speed at the previous time is greater than the second vehicle speed, the length of time when the vehicle speed is greater than the second vehicle speed in the first preset time period at the current time is greater than the third length or the length of time when the rotation speed is less than the second rotation speed is greater than the fourth length; determining the current time as the work cycle split end point when the average vehicle speed in the second preset time period at the current time is equal to the third vehicle speed, the average torque is greater than the preset torque, and the average rotation speed is greater than the preset rotation speed.

[0120] In some examples, the process of the segmentation unit 10 for segmenting the data segment into a plurality of road profile segments comprises: obtaining a plurality of atmospheric pressure change points in the data segment; determining the current atmospheric pressure change point as a segment split point when the product of the atmospheric pressure change value between the current atmospheric pressure change point and the atmospheric pressure change value of the previous atmospheric pressure change point is less than a preset pressure change value, the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the previous atmospheric pressure change point is greater than a first mileage difference, or the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the next atmospheric pressure change point is greater than a second mileage difference; and segmenting the data segment into a plurality of road profile segments based on the work cycle split start point and the segment split point of the data segment.

[0121] The slope acquisition unit 20 is configured to acquire the road slope of each road profile segment. The road slope of the road profile segment can be obtained based on the atmospheric pressure and the mileage of the end point of the road profile segment and the atmospheric pressure and the mileage of the start point of the road profile segment. As one possible way, the road profile segment is obtained based on the following formula:

[0122] wherein, End envp is the atmospheric pressure of the end point of the road profile segment, Start envp is the atmospheric pressure of the start point of the road profile segment, End dst is the mileage of the end point of the road profile segment, Start dst is the mileage of the start point of the road profile segment, the unit of the atmospheric pressure is hectopascal, and the unit of the mileage is meter.

[0123] The load acquisition unit 30 is configured to obtain the vehicle load of the road profile segment based on the road slope of each road profile segment and a preset vehicle dynamics equation, and the vehicle working condition data comprises the work cycle information, the road slope, and the vehicle load.

[0124] In some examples, the load obtaining unit 30 obtains the vehicle load of the road spectrum segment in the following manner: determining a stable working condition point in the road spectrum segment, the stable working condition point being an acceleration-stable and constant-speed-stable working condition point; calculating average acceleration, average torque, average speed and average speed-to-rotation ratio of the stable working condition point based on the vehicle speed, torque and rotation speed in the stable working condition point, the Internet of Vehicles data including the vehicle speed, torque and rotation speed; obtaining the vehicle load of the stable working condition point based on the average acceleration, average torque, average speed and average speed-to-rotation ratio of the stable working condition point, the road slope and a preset vehicle dynamics equation, the vehicle load of the stable working condition point being the to-be-determined vehicle load of the road spectrum segment; and obtaining the vehicle load of the road spectrum segment based on the to-be-determined vehicle loads of the plurality of road spectrum segments.

[0125] Optionally, the determining of the stable working condition point in the road spectrum segment comprises: determining a first segment in the road spectrum segment as an acceleration-stable working condition point when the atmospheric pressure in the first segment does not change, the acceleration in the first segment is greater than a first acceleration threshold and the acceleration deviation in the first segment is less than a first acceleration deviation threshold, the torque in the first segment is greater than a first torque value and the torque deviation in the first segment is less than a first torque deviation threshold, the accelerator pedal opening degree in the first segment is greater than a first opening degree threshold, and the deviation of the rotation speed-to-vehicle speed ratio in the first segment is less than a first deviation threshold, the first segment being a road segment in a preset time period in the road spectrum segment, the Internet of Vehicles data including the atmospheric pressure and the accelerator pedal opening degree; and determining the first segment as a constant-speed-stable working condition point when the atmospheric pressure in the first segment does not change, the vehicle speed deviation in the first segment is greater than a first vehicle speed deviation threshold, the accelerator pedal opening degree in the first segment is greater than a second opening degree threshold, the torque deviation in the first segment is less than a second torque deviation threshold, and the deviation of the rotation speed-to-vehicle speed ratio in the first segment is less than a second deviation threshold, the stable working condition point including the acceleration-stable working condition point and the constant-speed-stable working condition point.

[0126] Optionally, the preset vehicle dynamics equation is related to the acceleration, torque, rotation speed and speed-to-rotation ratio, gravitational acceleration, road slope, vehicle speed, moment of inertia, transmission system efficiency, air resistance coefficient, vehicle windward area and rolling friction resistance coefficient, and the derivation process and formula of the preset vehicle dynamics equation are described above.

[0127] Optionally, the vehicle load of the road spectrum segment is obtained based on the pending vehicle loads of the plurality of road spectrum segments, including: eliminating abnormal pending vehicle loads from the pending vehicle loads of the plurality of road spectrum segments; obtaining the vehicle load of the road spectrum segment based on the remaining pending vehicle loads of the plurality of road spectrum segments; wherein the abnormal pending vehicle load is eliminated by: calculating the standard deviation of all pending vehicle loads, and eliminating the pending vehicle load greater than the preset multiple of the standard deviation; or, sorting all pending vehicle loads in ascending order according to the value, calculating the N quantile of all pending vehicle loads, and eliminating the pending vehicle load below the 1 / N quantile point but above the (N-1 / N) quantile point, N is a natural number greater than 1.

[0128] In some examples, the load obtaining unit 30 is further configured to obtain the vehicle load of the data segment based on the vehicle load of the road spectrum segment. Correspondingly, the vehicle working condition data obtaining apparatus further includes a merging unit configured to merge two adjacent data segments into one data segment if the vehicle loads of the two adjacent data segments are the same.

[0129] In addition, the embodiments of the present application further provide a vehicle working condition data obtaining device, which includes a processor and a memory, and the memory stores a program which is run by the processor to implement the vehicle working condition data obtaining method.

[0130] The embodiments of the present application further provide a storage medium, which stores a computer program, and the computer program is run by a processor to implement the vehicle working condition data obtaining method.

[0131] It should be noted that each of the embodiments in the present specification can be described in a progressive manner, the features recorded in each of the embodiments can be replaced or combined with each other, and each embodiment focuses on the difference from other embodiments, and the same or similar parts of each embodiment can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiment.

[0132] Finally, it should be noted that, in this document, the term "only" is used simply to set off from one entity or action to another in order to avoid the use of the term "and / or" or the like. Moreover, the terms "comprise", "comprises" or "comprising" or any variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0133] The above description of disclosed embodiments provides enabling teaching for a person skilled in the art to realize or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0134] The above description is only the preferred embodiments of the present application, and it should be pointed out that, for those skilled in the art, several improvements and refinements can be made without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A method of acquiring vehicle operating condition data, characterized by, The method comprises: segmenting the Internet of Vehicles data into multiple data segments, each data segment corresponding to a work cycle; segmenting the data segments into multiple road profile segments and determining the work cycle to which the road profile segments belong, to obtain work cycle information comprising multiple road profile segments; obtaining the road slope of each road profile segment; obtaining the vehicle load of each road profile segment based on the road slope of each road profile segment and a preset vehicle dynamics equation, the vehicle working condition data comprising the work cycle information, the road slope and the vehicle load; wherein the obtaining of the vehicle load based on the road slope of each road profile segment and the preset vehicle dynamics equation comprises: determining a stable working condition point in the road profile segment, the stable working condition point being an acceleration-stable and constant-speed-stable working condition point; calculating the average acceleration, average torque, average speed and average speed ratio of the stable working condition point based on the vehicle speed, torque and speed within the stable working condition point, the Internet of Vehicles data comprising the vehicle speed, torque and speed; obtaining the vehicle load of the stable working condition point based on the average acceleration, average torque, average speed and average speed ratio of the stable working condition point, the road slope and a preset vehicle dynamics equation, the vehicle load of the stable working condition point being the to-be-determined vehicle load of the road profile segment; obtaining the vehicle load of the road profile segment based on the to-be-determined vehicle loads of multiple road profile segments.

2. The method of claim 1, wherein, The determination of the stable working condition point in the road profile segment comprises: if the atmospheric pressure in a first segment of the road profile segment does not change, the acceleration in the first segment is greater than a first acceleration threshold and the acceleration deviation is less than a first acceleration deviation threshold, the torque in the first segment is greater than a first torque value and the torque deviation is less than a first torque deviation threshold, the accelerator pedal opening in the first segment is greater than a first opening threshold, and the deviation of the speed and the speed ratio in the first segment is less than a first deviation threshold, the first segment is determined to be an acceleration-stable working condition point, the first segment being a road segment within a preset time period in the road profile segment, and the Internet of Vehicles data comprising the atmospheric pressure and the accelerator pedal opening; if the atmospheric pressure in the first segment does not change, the speed deviation in the first segment is greater than a first speed deviation threshold, the accelerator pedal opening in the first segment is greater than a second opening threshold, the torque deviation in the first segment is less than a second torque deviation threshold, and the deviation of the speed and the speed ratio in the first segment is less than a second deviation threshold, the first segment is determined to be a constant-speed-stable working condition point, the stable working condition point comprising the acceleration-stable working condition point and the constant-speed-stable working condition point.

3. The method according to claim 1 or 2, characterized in that, The preset vehicle dynamics equation is related to acceleration, torque, speed and speed ratio, gravitational acceleration, road slope, speed, moment of inertia, transmission system efficiency, air resistance coefficient, vehicle wind area and rolling friction resistance coefficient.

4. The method according to claim 1 or 2, characterized in that, The obtaining of the vehicle load of the road profile segment based on the to-be-determined vehicle loads of multiple road profile segments comprises: eliminating abnormal to-be-determined vehicle loads from the to-be-determined vehicle loads of multiple road profile segments; Obtaining vehicle load of the road profile segment based on the remaining pending vehicle load of the pending vehicle load of the plurality of road profile segments; The method further comprises: obtaining vehicle load of the data segment based on the vehicle load of the road profile segment; 5. The method of claim 1, wherein, If the vehicle loads of two adjacent data segments are the same, merging the two adjacent data segments into one data segment. The method further comprises:

6. The method according to claim 1 or 5, characterized in that, Determining a work cycle division start point and a work cycle division end point in the vehicle networking data; If there is no work cycle division end point interspersed in the plurality of work cycle division start points, merging the plurality of work cycle division start points into one work cycle division start point; If there is no work cycle division start point interspersed in the plurality of work cycle division end points, merging the plurality of work cycle division end points into one work cycle division end point; Dividing the vehicle networking data into a plurality of data segments based on the work cycle division start point and the work cycle division end point. The method further comprises:

7. The method of claim 6, wherein, If the vehicle speed at the current time is equal to a first vehicle speed but the vehicle speed at the next time is greater than the first vehicle speed, the duration that the vehicle speed is greater than the first vehicle speed in a first preset time period at the current time is greater than a first duration, and the duration that the rotation speed is less than a first rotation speed in the first preset time period at the current time is less than a second duration, it is determined that the current time is a work cycle division start point; If the vehicle speed at the current time is equal to a second vehicle speed but the vehicle speed at the previous time is greater than the second vehicle speed, the duration that the vehicle speed is greater than the second vehicle speed in a first preset time period at the current time is greater than a third duration or the duration that the rotation speed is less than a second rotation speed is greater than a fourth duration, it is determined that the current time is a work cycle division end point; If the average vehicle speed in a second preset time period at the current time is equal to a third vehicle speed, the average torque is greater than a preset torque, and the average rotation speed is greater than a preset rotation speed, it is determined that the current time is a work cycle division end point. The method further comprises:

8. The method of claim 1 or 5, wherein, Obtaining a plurality of atmospheric pressure change points in the data segment; If the product of the atmospheric pressure change value at the current atmospheric pressure change point and the atmospheric pressure change value at the previous atmospheric pressure change point is less than a preset pressure change value, the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the previous atmospheric pressure change point is greater than a first mileage difference, or the difference between the mileage corresponding to the current atmospheric pressure change point and the mileage corresponding to the next atmospheric pressure change point is greater than a second mileage difference, it is determined that the current atmospheric pressure change point is a segment division point; ​ Based on the job cycle division start point of the data segment and the segment division point, the data segment is divided into multiple road profile segments.

9. A vehicle operating condition data acquisition apparatus characterized by comprising: The device comprises: A division unit is configured to divide the Internet of Vehicles data into multiple data segments, each data segment corresponding to a job cycle, and to divide the data segments into multiple road profile segments and determine the job cycle to which the road profile segments belong, so as to obtain job cycle information comprising multiple road profile segments. A slope acquisition unit is configured to acquire the road slope of each road profile segment. A load acquisition unit is configured to obtain the vehicle load of each road profile segment based on the road slope of each road profile segment and a preset vehicle dynamics equation, and the vehicle working condition data comprises the job cycle information, the road slope and the vehicle load; wherein the load acquisition unit obtains the vehicle load of each road profile segment based on the road slope of each road profile segment and the preset vehicle dynamics equation, and is specifically configured to: determine a stable working condition point in the road profile segment, the stable working condition point being an acceleration-stable and uniform-speed-stable working condition point; calculate the average acceleration, average torque, average speed ratio of the average speed and the average rotation speed of the stable working condition point based on the vehicle speed, torque and rotation speed in the stable working condition point, the Internet of Vehicles data comprising the vehicle speed, torque and rotation speed; obtain the vehicle load of the stable working condition point based on the average acceleration, average torque, average speed ratio of the average speed and the average rotation speed of the stable working condition point, the road slope and the preset vehicle dynamics equation, the vehicle load of the stable working condition point being the to-be-determined vehicle load of the road profile segment; and obtain the vehicle load of the road profile segment based on the to-be-determined vehicle loads of multiple road profile segments.

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