Method and device for determining load spectrum of differential mechanism of vehicle, processor and vehicle

Abstract

The invention discloses a method and device for determining a load spectrum of a differential mechanism of a vehicle, a processor and the vehicle. The method comprises the steps that operation data of a vehicle are obtained, and the operation data are at least used for representing the operation state of the vehicle; differential data of the vehicle are determined based on the operation data, and the differential data comprise the left half axle rotating speed and the right half axle rotating speed of the vehicle, the rotating speed difference between the left half axle rotating speed and the right half axle rotating speed and the difference rate; based on the differential data and the motor data of the vehicle, the working condition of the vehicle is classified, and a classification result is obtained; based on the classification result, combined load counting is conducted on the input torque and the rotating speed difference, a load counting result is obtained, and based on the load counting result, the damage value of the differential in the vehicle under the working condition of the vehicle is determined; and determining a load spectrum of the differential based on the load counting result and the damage value. The technical problem that the determination accuracy of the load spectrum of the differential mechanism of the vehicle is low is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a method and device for determining a load spectrum of a differential of a vehicle, a processor and a vehicle. BACKGROUND

[0002] At present, as an important component in vehicles, the differential is mainly used to adjust the speed difference of the two sides of the wheels to adapt to different road conditions, especially when turning, the differential can balance the rotation speed of the inside and outside wheels to avoid tire wear and vehicle out of control. With the popularity of new energy vehicles and the introduction of high-performance electric drive systems, the differential is facing new challenges. Unlike traditional fuel vehicles, the characteristics of new energy vehicles in energy recovery, high-frequency dynamic response and instantaneous high-torque output put higher requirements on the working environment and load of the differential. However, the current development and verification of the differential mostly rely on the habits of traditional car users or standardized tests in test fields, which cannot fully reflect the actual operating characteristics of new energy vehicles, especially in terms of coverage and accuracy of high-differential damage conditions. Therefore, there is still a technical problem of low accuracy in determining the load spectrum of the differential of the vehicle.

[0003] There is no effective solution to the technical problem of low accuracy in determining the load spectrum of the differential of the vehicle. SUMMARY

[0004] The embodiments of the present application provide a method and device for determining a load spectrum of a differential of a vehicle, a processor and a vehicle to at least solve the technical problem of low accuracy in determining the load spectrum of the differential of the vehicle.

[0005] According to an aspect of some embodiments of the present application, a method for determining a load spectrum of a differential of a vehicle is provided. The method can include: obtaining operation data of the vehicle, wherein the operation data is used to represent at least an operation state of the vehicle; determining differential data of the vehicle based on the operation data, wherein the differential data includes a left half axle speed and a right half axle speed of the vehicle, a speed difference between the left half axle speed and the right half axle speed, and a differential rate used to represent a proportion of the speed difference relative to an average half axle speed of the vehicle in a target time period; classifying a working condition of the vehicle based on the differential data and motor data of the vehicle to obtain a classification result, wherein the motor data is used to represent an input speed of a motor and an input torque of the motor; jointly counting the input torque and the speed difference based on the classification result to obtain a load counting result, and determining a damage value of the differential in the working condition of the vehicle based on the load counting result, wherein the load counting result is used to represent a frequency of use of the differential under different load conditions, and the damage value is used to represent a degree of accumulated fatigue damage of the differential; and determining a load spectrum of the differential based on the load counting result and the damage value, wherein the load spectrum is used to represent a characteristic of a fatigue load distribution of the differential in a whole life cycle of the vehicle.

[0006] Optionally, determining the differential data of the vehicle based on the operation data includes: performing data cleaning processing and data standardization processing on the operation data respectively to obtain target operation data, wherein a data quality of the target operation data is higher than a data quality of the operation data; and screening the differential data from the target operation data.

[0007] Optionally, classifying the working condition of the vehicle based on the differential data and the motor data of the vehicle to obtain the classification result includes: in response to the differential data being greater than a differential data threshold, the input torque being greater than an input torque threshold, and the input speed being greater than an input speed threshold, determining that the classification result is that the vehicle is in a first working condition type, wherein the first working condition type is used to represent that the vehicle is in a left turn forward driving condition; in response to the differential data being less than the differential data threshold, the input torque being greater than the input torque threshold, and the input speed being greater than the input speed threshold, determining that the classification result is that the vehicle is in a second working condition type, wherein the second working condition type is used to represent that the vehicle is in a right turn forward driving condition; in response to the differential data being greater than the differential data threshold, the input torque being less than the input torque threshold, and the input speed being greater than the input speed threshold, determining that the classification result is that the vehicle is in a third working condition type, wherein the third working condition type is used to represent that the vehicle is in a left turn forward energy recovery condition; and in response to the differential data being less than the differential data threshold, the input torque being less than the input torque threshold, and the input speed being greater than the input speed threshold, determining that the classification result is that the vehicle is in a fourth working condition type, wherein the fourth working condition type is used to represent that the vehicle is in a right turn forward energy recovery condition.

[0008] Optionally, the method further comprises: in response to the differential data being greater than the differential data threshold, the input torque being greater than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in a fifth working condition type, wherein the fifth working condition type is used to represent the vehicle being in a left-turning reverse driving working condition; in response to the differential data being less than the differential data threshold, the input torque being greater than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in a sixth working condition type, wherein the sixth working condition type is used to represent the vehicle being in a right-turning reverse driving working condition; in response to the differential data being greater than the differential data threshold, the input torque being less than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in a seventh working condition type, wherein the seventh working condition type is used to represent the vehicle being in a left-turning reverse energy recovery working condition; in response to the differential data being less than the differential data threshold, the input torque being less than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in an eighth working condition type, wherein the eighth working condition type is used to represent the vehicle being in a right-turning reverse energy recovery working condition.

[0009] Optionally, based on the classification result, joint load counting is performed on the input torque and the rotation speed difference to obtain a load counting result, and based on the load counting result, a damage value of the differential in the working condition of the vehicle is determined, comprising: dividing the input torque and the rotation speed difference into intervals according to a target threshold interval number to obtain motor input torque intervals and rotation speed difference intervals; in each classification result, the differential revolutions under the input torque and the rotation speed difference are mapped into the motor input torque intervals and the rotation speed difference intervals; a combined interval of the motor input torque intervals and the rotation speed difference intervals is determined, and the number of times that the input torque and the rotation speed difference combined interval is in the combined interval is determined, wherein the number of times represents the frequency of use of the differential under different load conditions; the number of times is determined as the load counting result; and the damage value is determined according to the load counting result and a damage model, wherein the damage model is used to evaluate the cumulative fatigue damage of the differential under different load conditions; the method further comprises: sorting the damage value to obtain a sorting result, wherein the sorting result represents the priority of the influence of different combined intervals on the cumulative damage of the differential.

[0010] Optionally, based on the load counting result and the damage value, a load spectrum of the differential is determined, comprising: determining the product of the load counting result under the motor input torque interval and the rotation speed difference interval and the corresponding damage value as the damage load frequency under the two-dimensional motor input torque interval and the rotation speed difference interval; and generating the load spectrum of the differential according to the damage load frequency.

[0011] Optionally, the method further comprises: analyzing the load spectrum according to the durability index requirement information, the target sales region and the target object range, to obtain a target load spectrum, wherein the target load spectrum is used to represent a load spectrum meeting the requirements, the durability index requirement information is used to represent a standard to be met during a life expectancy of the vehicle, the target sales region is used to represent a geographical region where the vehicle is planned to be sold, and the target object range is used to represent a range where a target object applying the vehicle is located.

[0012] According to another aspect of the embodiments of the present application, a device for determining a load spectrum of a differential of a vehicle is further provided. The device can include: an obtaining unit configured to obtain operation data of the vehicle, wherein the operation data is used to represent at least an operation state of the vehicle; a first determining unit configured to determine differential data of the vehicle based on the operation data, wherein the differential data includes a left half axle speed and a right half axle speed of the vehicle, a speed difference between the left half axle speed and the right half axle speed, and a differential rate used to represent a proportion of the speed difference relative to an average half axle speed of the vehicle in a target time period; a classifying unit configured to classify a working condition of the vehicle based on the differential data and motor data of the vehicle, to obtain a classification result, wherein the motor data is used to represent an input speed of a motor and an input torque of the motor in the vehicle; a counting unit configured to jointly count the input torque and the speed difference based on the classification result, to obtain a load counting result, and determine an injury value of the differential in the working condition of the vehicle based on the load counting result, wherein the load counting result is used to represent a frequency of use of the differential under different load conditions, and the injury value is used to represent a degree of fatigue injury accumulated by the differential; and a second determining unit configured to determine the load spectrum of the differential based on the load counting result and the injury value, wherein the load spectrum is used to represent a feature of fatigue load distribution of the differential in a whole life cycle of the vehicle.

[0013] According to another aspect of the embodiments of the present application, a computer readable storage medium is further provided. The computer readable storage medium includes a stored program, wherein the program, when executed, controls a device where the computer readable storage medium is located to perform the method of the embodiments of the present application.

[0014] According to another aspect of the embodiments of the present application, a processor is further provided. The processor is used to execute a program, wherein the program, when executed, performs the method of the embodiments of the present application.

[0015] According to another aspect of the embodiments of the present application, a vehicle is further provided. The vehicle is used to perform the method of the embodiments of the present application.

[0016] In the embodiment of the present application, by analyzing the operation data, the key parameters of the differential are calculated based on the operation data, including the left half shaft speed, the right half shaft speed, the speed difference, and the differential rate, the working conditions of the vehicle are finely divided in combination with the differential data and the motor data (input speed and torque), the motor input torque and the speed difference are counted for each type of working condition, the frequency of the torque and speed difference combination under different working conditions is counted, and the load counting result is obtained; based on the load counting result, the damage value of the differential in the vehicle under the working condition of the vehicle is determined; the load spectrum of the differential is determined by comprehensively considering the load counting result and the damage value, the fatigue damage and load characteristics of the differential in the whole life cycle of the vehicle are accurately evaluated and predicted, the technical problem of low accuracy of determining the load spectrum of the differential of the vehicle is solved, and the technical effect of improving the accuracy of determining the load spectrum of the differential of the vehicle is realized. BRIEF DESCRIPTION OF DRAWINGS

[0017] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a flowchart of a method for determining the load spectrum of a differential of a vehicle according to an embodiment of the present application;

[0019] Figure 2 is a flowchart of a new energy vehicle differential working condition division and load counting method according to an embodiment of the present application;

[0020] Figure 3 is a schematic diagram of user load speed difference distribution characteristics according to an embodiment of the present application;

[0021] Figure 4 is a schematic diagram of another user load speed difference distribution characteristics according to an embodiment of the present application;

[0022] Figure 5 is a schematic diagram of a device for determining the load spectrum of a differential of a vehicle according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0024] It is to be understood that the terms "first", "second", and the like, used in the description and the claims of the application and the above-described accompanying drawings, are used to distinguish similar objects, and are not necessarily used to describe a particular sequential or chronological order. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to the steps or units listed explicitly, but can include other steps or units not listed explicitly or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the application, an embodiment of a method for determining a load spectrum of a differential of a vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0026] Figure 1 is a flowchart of a method for determining a load spectrum of a differential of a vehicle according to an embodiment of the application, as shown in Figure 1 The method can include the following steps:

[0027] Step S102, obtaining running data of the vehicle.

[0028] In the technical solution provided in the above step S102 of the application, the running data is used to represent at least the running state of the vehicle.

[0029] In this embodiment, the running data of the vehicle is obtained, such as the Internet of Vehicles running data, wherein the Internet of Vehicles running data can reflect information such as the running state of the vehicle, environmental conditions and driving behavior, and can include but not limited to vehicle basic information, driving state data, motor and engine data, etc.

[0030] Optionally, the vehicle basic information can be vehicle model, year, configuration, etc., which helps to associate the collected data with a specific type of vehicle. The driving state data can be the actual driving mileage, time, speed, acceleration, direction change, turning radius, etc. of the vehicle, which is an important parameter for analyzing the working condition of the vehicle and the load of the differential. In new energy vehicles, the motor and engine data can include the input speed, input torque and power consumption of the motor; in hybrid vehicles, it can be the speed, torque and fuel consumption of the engine, etc.

[0031] Step S104, determining the differential data of the vehicle based on the running data.

[0032] In the technical solution provided in the above step S104 of the present application, the differential data includes the left half axle speed and the right half axle speed of the vehicle, the speed difference between the left half axle speed and the right half axle speed, and the differential rate, which is used to represent the proportion of the speed difference to the average half axle speed of the vehicle in the target time period.

[0033] In this embodiment, after obtaining the running data of the vehicle, the differential data of the vehicle can be determined based on the running data. The left half axle speed and the right half axle speed of the vehicle can be collectively referred to as the left and right half axle speed.

[0034] Optionally, the left half axle speed and the right half axle speed can be monitored by sensors installed on the half axle of the vehicle, and then collected and recorded in real time through the vehicle network system. Then, the difference between the left half axle speed and the right half axle speed, i.e. the speed difference, can be calculated. The speed difference is a key indicator for measuring whether the differential is working, and reflects the situation that the left and right wheels of the vehicle are not consistent in speed when turning or encountering different road resistances.

[0035] Optionally, the differential rate is the ratio of the speed difference to the average half axle speed, which provides a standardized way to look at the influence of the speed difference on the differential load. The average half axle speed is the average of the left and right half axle speeds of the vehicle in the target time period, and the differential rate is calculated to quantify the degree of change of the speed difference under certain driving conditions.

[0036] Optionally, the target time period can be a specific driving cycle, such as a complete trip, or a certain specific driving mode lasting time, for example, driving time under high speed or urban congestion environment, which is only for illustration and is not limited specifically here.

[0037] In step S106, the working condition of the vehicle is classified based on the differential data and the motor data of the vehicle, and a classification result is obtained.

[0038] In the technical solution of the above step S106 of the present application, the motor data is used to represent the input speed of the motor in the vehicle and the input torque of the motor.

[0039] In this embodiment, after determining the differential data of the vehicle based on the running data, the working condition of the vehicle is classified based on the differential data and the motor data of the vehicle, and a classification result is obtained. The motor data reflects the power output characteristics of the electric drive system of the vehicle.

[0040] Optionally, the working condition classification is based on the working characteristics of the differential and the operating state of the motor, and the operation of the vehicle is divided into a series of explicit operating modes. In a new energy vehicle, the working condition classification can include: forward / reverse: this depends on the direction of the motor input speed and the driving direction of the vehicle. Driving / energy recovery: the positive and negative values of the input torque of the motor can help determine whether the vehicle is in driving (positive torque) or energy recovery (negative torque) mode. Steering condition: the speed difference and the differential rate of the differential can identify whether the vehicle is turning and the direction of the turn (left or right).

[0041] Optionally, when the motor input speed is positive, the vehicle is in forward working condition; when the motor input speed is negative, the vehicle is in reverse working condition.

[0042] Optionally, if the motor input torque is positive, the vehicle is in driving working condition; if the motor input torque is negative, the vehicle is in energy recovery working condition.

[0043] Optionally, by analyzing the trend of the speed difference and the differential rate, it can be determined whether the vehicle is turning left, turning right or driving straight.

[0044] Step S108, based on the classification result, joint load counting is performed on the input torque and the speed difference to obtain a load counting result, and based on the load counting result, a damage value of the differential in the vehicle under the working condition of the vehicle is determined.

[0045] In the technical solution of step S108 of the present application, the load counting result is used to represent the frequency of use of the differential under different load conditions, and the damage value is used to represent the degree of cumulative fatigue damage of the differential.

[0046] In this embodiment, after classifying the working condition of the vehicle based on the differential data and the motor data of the vehicle to obtain a classification result, joint load counting can be performed on the input torque and the speed difference based on the classification result to obtain a load counting result. Further based on the load counting result, a damage value of the differential in the vehicle under the working condition of the vehicle is determined. Through this step, the use of the differential under different working conditions, such as the frequency and intensity of the differential load, can be quantified.

[0047] Optionally, a two-dimensional matrix is created, in which the horizontal axis represents the speed difference range and the vertical axis represents the input torque range. According to the preset interval, each torque interval and speed difference interval can be calibrated. Traverse the working condition classification result, for each record, determine its corresponding torque interval and speed difference interval, then increase the count at the corresponding position of the load matrix to obtain the load counting result.

[0048] Optionally, based on the load counting results, an appropriate damage model is adopted to evaluate the damage contribution under various load conditions. For each torque-speed difference combination in the load matrix, its damage value can be calculated according to its load counting results and damage model parameters. The damage values of various torque-speed difference combinations are summarized to obtain the total damage value of the differential under different working conditions, which reflects the total fatigue damage degree of the differential in the whole life cycle.

[0049] In step S110, the load spectrum of the differential is determined based on the load counting results and the damage values.

[0050] In the technical solution of step S110 of the present application, after the joint load counting of the input torque and the speed difference based on the classification results to obtain the load counting results, and the determination of the damage values of the differential under the working conditions of the vehicle based on the load counting results, the load spectrum of the differential can be determined based on the load counting results and the damage values. The load spectrum is used to represent the characteristics of the fatigue load distribution of the differential in the whole life cycle of the vehicle.

[0051] Optionally, the load spectrum can describe the load distribution characteristics of the product (such as the differential of the vehicle) in the whole life cycle. For the differential, the load spectrum can reveal the fatigue load mode of the differential under different working conditions.

[0052] Optionally, by comprehensively considering the load counting results (i.e. the usage frequency of the differential under different torque and speed difference combinations) and the damage values (indicating the cumulative fatigue damage degree of the differential under various loads), a model reflecting the fatigue load distribution of the differential in the whole life cycle can be established. Considering that different load conditions have different contribution degrees to the damage of the differential, a weight based on the damage value can be assigned to the load counting results of each torque-speed difference combination. In this way, the load frequency is adjusted by weighting according to the damage value, so as to ensure that the load spectrum can more accurately reflect the fatigue load distribution under the real conditions.

[0053] Optionally, the load spectrum takes torque and speed difference as coordinate axes, and uses color depth or contour lines to represent the usage frequency and damage degree of the differential under different working conditions. It can be a collection of multiple two-dimensional graphs, each representing the load distribution under different working conditions (such as forward driving, forward energy recovery, left turn, etc.).

[0054] The steps S102 to S110 of the present application are described above. By analyzing the operation data, the key parameters of the differential are calculated based on the operation data, including the left half shaft speed, the right half shaft speed, the speed difference, and the differential rate. In combination with the differential data and the motor data (input speed and torque), the working conditions of the vehicle are finely divided. For each type of working condition, the motor input torque and the speed difference are jointly counted. The frequency of the combination of torque and speed difference under different working conditions is counted to obtain the load counting result. Based on the load counting result, the damage value of the differential in the vehicle under the working condition of the vehicle is determined. By comprehensively considering the load counting result and the damage value, the load spectrum of the differential is determined. The fatigue damage and load characteristics of the differential in the whole life cycle of the vehicle are accurately evaluated and predicted. The technical problem of low accuracy of determining the load spectrum of the differential of the vehicle is solved, and the technical effect of improving the accuracy of determining the load spectrum of the differential of the vehicle is achieved.

[0055] The above method of the embodiment will be further introduced below.

[0056] As an optional embodiment, in step S104, the differential data of the vehicle is determined based on the operation data, including: performing data cleaning processing and data standardization processing on the operation data to obtain target operation data, wherein the data quality of the target operation data is higher than that of the operation data; and screening the differential data from the target operation data.

[0057] In this embodiment, in order to ensure the accuracy and reliability of the differential data, the operation data can be processed by data cleaning respectively. For example, threshold processing, piecewise interpolation, null value deletion, wheel speed inspection, and data resampling. Data standardization processing can be performed to ensure that the obtained target operation data is cleaner, more consistent and comparable, thereby improving the accuracy of subsequent analysis.

[0058] Optionally, after obtaining the target operation data, the differential data such as the left half shaft speed, the right half shaft speed, the speed difference and the differential rate can be screened from the target operation data, thereby providing high-quality input for subsequent working condition classification and load counting, and ensuring that the subsequent working condition classification and damage calculation are based on the most relevant and accurate data.

[0059] The left and right half shaft speeds can be determined by the following formula:

[0060]

[0061] Wherein, v l ,v r may be used to represent the left wheel speed and the right wheel speed, respectively, with the unit of km / h; d may be used to represent the tire rolling diameter, with the unit of m; n may be used to represent the half shaft speed, with the unit of r / min; n lnL can be used to represent the left half shaft speed, units are r / min. r nR can be used to represent the right half shaft speed, units are r / min.

[0062] Speed difference Δ n It can be determined by the following formula:

[0063] Δ n = n l -n r

[0064] Differential rate r Δ It can be determined by the following formula:

[0065]

[0066] As an optional embodiment, step S106, based on the differential data, and the motor data of the vehicle, classifies the working condition of the vehicle to obtain a classification result, including: in response to the differential data being greater than the differential data threshold value, the input torque being greater than the input torque threshold value, and the input speed being greater than the input speed threshold value, determining that the classification result is that the vehicle is in a first working condition type, wherein the first working condition type is used to indicate that the vehicle is in a left turn forward driving condition; in response to the differential data being less than the differential data threshold value, the input torque being greater than the input torque threshold value, and the input speed being greater than the input speed threshold value, determining that the classification result is that the vehicle is in a second working condition type, wherein the second working condition type is used to indicate that the vehicle is in a right turn forward driving condition; in response to the differential data being greater than the differential data threshold value, the input torque being less than the input torque threshold value, and the input speed being greater than the input speed threshold value, determining that the classification result is that the vehicle is in a third working condition type, wherein the third working condition type is used to indicate that the vehicle is in a left turn forward energy recovery condition; in response to the differential data being less than the differential data threshold value, the input torque being less than the input torque threshold value, and the input speed being greater than the input speed threshold value, determining that the classification result is that the vehicle is in a fourth working condition type, wherein the fourth working condition type is used to indicate that the vehicle is in a right turn forward energy recovery condition.

[0067] In this embodiment, the working condition classification is to distinguish the state of the vehicle in different working conditions by setting specific threshold values, which are specific to the left turn, right turn, forward driving and forward energy recovery of the differential. By monitoring the differential data (such as speed difference and differential rate) and motor data (such as input torque and input speed), the working condition of the vehicle can be judged in real time, and the load of the differential can be accurately analyzed.

[0068] Optionally, a differential data threshold can be used to distinguish whether the difference in the rotational speed of the left and right half shafts is sufficient to indicate that the vehicle is making a turn. The differential data threshold can be set according to the vehicle type, driving conditions, and the characteristics and performance of the differential, such as 0. An input torque threshold can be used to determine whether the motor is providing power (driving condition) or consuming energy (energy recovery condition); positive torque means that the motor is providing power to the vehicle, while negative torque indicates that the motor is recovering energy. An input speed threshold can be used to confirm whether the vehicle is moving forward, because only in forward mode can the motor input speed be positive. In addition, the input speed threshold is also used to identify whether the vehicle is in the valid operating range, to avoid misclassification due to atypical conditions such as vehicle stationary or low-speed coasting.

[0069] Optionally, based on the above-mentioned thresholds, the vehicle operating conditions can be classified into the following types: a first operating condition type (left turn forward driving): when the differential data (rotational speed difference or differential rate) exceeds the differential data threshold, the input torque of the motor is greater than the input torque threshold, and the input speed of the motor is greater than the input speed threshold, it can be determined that the vehicle is in a left turn forward driving condition. This means that when the vehicle is moving forward, the left wheel rotates faster than the right wheel, and the differential provides the necessary torque distribution for the left turn. A second operating condition type (right turn forward driving): when the differential data is less than the differential data threshold, but the input torque and input speed are greater than the respective thresholds, the vehicle is in a right turn forward driving condition. In contrast to the first operating condition type, at this time the right wheel rotates faster than the left wheel, and the differential distributes torque for the right turn operation. A third operating condition type (left turn forward energy recovery): if the differential data exceeds the differential data threshold, the input torque is less than the input torque threshold, but the input speed is still greater than the input speed threshold, then the vehicle is in a left turn forward energy recovery condition. While the vehicle is moving forward and turning left, the motor is recovering energy, which can occur when the vehicle is decelerating or going downhill. A fourth operating condition type (right turn forward energy recovery): when the differential data is less than the differential data threshold, the input torque and input speed are less than and greater than the respective thresholds, respectively, the vehicle is in a right turn forward energy recovery condition. Similar to the third operating condition type, but the direction of turning and energy recovery is reversed.

[0070] As an optional embodiment, the method further comprises: in response to the differential data being greater than the differential data threshold, the input torque being greater than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in a fifth working condition type, wherein the fifth working condition type is used to represent the vehicle being in a left-turning reverse driving working condition; in response to the differential data being less than the differential data threshold, the input torque being greater than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in a sixth working condition type, wherein the sixth working condition type is used to represent the vehicle being in a right-turning reverse driving working condition; in response to the differential data being greater than the differential data threshold, the input torque being less than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in a seventh working condition type, wherein the seventh working condition type is used to represent the vehicle being in a left-turning reverse energy recovery working condition; in response to the differential data being less than the differential data threshold, the input torque being less than the input torque threshold, and the input rotation speed being less than the input rotation speed threshold, determining the classification result as the vehicle being in an eighth working condition type, wherein the eighth working condition type is used to represent the vehicle being in a right-turning reverse energy recovery working condition.

[0071] In this embodiment, the reverse driving condition is taken into account to form a more comprehensive vehicle running state recognition. By including the reverse driving condition, the working condition classification becomes more comprehensive, covering the possible running modes of the vehicle, which is crucial for the overall durability analysis of the differential.

[0072] Optionally, the vehicle working condition is classified into the following types: a fifth working condition type (left-turning reverse driving): when the differential data exceeds a set differential data threshold, the input torque of the motor is greater than an input torque threshold, and the input rotation speed of the motor is less than an input rotation speed threshold (indicating that the vehicle is reversing), it can be determined that the vehicle is in a left-turning reverse driving working condition. In this working condition, the left wheel has a greater rotation speed relative to the right wheel, and the differential needs to consider the mechanical characteristics during reversing when distributing the torque. A sixth working condition type (right-turning reverse driving): similar to the fifth working condition type, but the differential data is less than the differential data threshold, indicating that the right wheel has a higher rotation speed relative to the left wheel. Similarly, the motor input torque and input rotation speed meet the driving condition and the reverse condition, determining that the vehicle is in a right-turning reverse driving working condition. A seventh working condition type (left-turning reverse energy recovery): if the differential data exceeds the differential data threshold, the input torque is less than the input torque threshold (indicating that the motor is recovering energy), and the input rotation speed is less than the input rotation speed threshold (the vehicle is reversing), the vehicle is in a left-turning reverse energy recovery working condition. In this case, the differential needs to handle the complex load caused by reversing and energy recovery simultaneously. An eighth working condition type (right-turning reverse energy recovery): when the differential data is less than the differential data threshold, the input torque and input rotation speed meet the energy recovery and reverse conditions, the vehicle is in a right-turning reverse energy recovery working condition.

[0073] As an optional embodiment, in step S108, based on the classification results, joint load counting is performed on the input torque and the speed difference to obtain load counting results, and based on the load counting results, the damage value of the differential in the working condition of the vehicle is determined, including: dividing the input torque and the speed difference into intervals according to the target threshold interval number to obtain the motor input torque interval and the speed difference interval; in each classification result, the differential speed under the input torque and the speed difference is mapped into the motor input torque interval and the speed difference interval; the combination interval of the motor input torque interval and the speed difference interval is determined, and the number of times that the input torque and the speed difference combination interval is in the combination interval, wherein the number of times represents the frequency of use of the differential under different load conditions; the number of times is determined as the load counting result; the damage value is determined according to the load counting result and the damage model, wherein the damage model is used to evaluate the fatigue damage accumulation of the differential under different load conditions; the method further comprises: sorting the damage value to obtain a sorting result, wherein the sorting result represents the priority of the influence of different combination intervals on the cumulative damage of the differential.

[0074] In this embodiment, according to the preset target threshold, the input torque and the speed difference are divided into multiple intervals, such as 128 intervals. The input torque and the speed difference under each working condition recorded in the classification result can be mapped into the corresponding torque interval and speed difference interval. This mapping process ensures the standardization and comparability of the data.

[0075] Optionally, a series of combination intervals are obtained by the cross combination of the motor input torque interval and the speed difference interval. Each combination interval represents a specific load condition. The number of times that the differential appears in each combination interval in the working condition classification result is counted. The number of times reflects the frequency of use of the differential under a specific load condition, which is an important part of the load counting result. The number of times that the differential appears in the combination interval is taken as the load counting result. This result quantifies the working frequency of the differential under various load conditions, providing basic data for subsequent damage assessment.

[0076] Optionally, a damage model matched with the material and structure of the differential is used to calculate the damage value according to the load counting result. The damage value evaluates the degree of fatigue damage accumulated by the differential under a specific load condition. The damage values under the combination intervals are sorted to obtain a sorting result. The sorting result reflects the priority of the influence of different load combinations on the cumulative damage of the differential, which helps to identify high damage working conditions and optimize design. By analyzing the sorting result, the load combination interval that needs special attention and design optimization is determined. For example, the high damage interval with high sorting priority may need additional reinforcement measures in the differential design to improve its durability and reliability in these working conditions.

[0077] As an optional embodiment, in step S110, the load spectrum of the differential is determined based on the load count result and the damage value, including: multiplying the load count result under the motor input torque interval and the speed difference interval with the corresponding damage value to determine the damage load frequency under the two-dimensional motor input torque interval and the speed difference interval; and generating the load spectrum of the differential according to the damage load frequency.

[0078] In this embodiment, the damage load frequency refers to the product of the cumulative damage and the usage frequency of the differential under a specific motor input torque interval and a speed difference interval. This index comprehensively considers the fatigue damage degree of the differential and the usage frequency under the damage condition, and thus more comprehensively reflects the durability requirements of the differential under different working conditions.

[0079] Optionally, the load count result (i.e., the usage frequency of each torque interval and speed difference interval) is aligned with the corresponding damage value (calculated based on the linear cumulative damage model or other corresponding model) in the same torque and speed difference interval. Then, the load count result of each torque interval and speed difference interval is multiplied by the corresponding damage value to obtain the damage load frequency under the two-dimensional torque-speed difference interval. Once the damage load frequency is calculated, it can be presented in a visual manner to generate the load spectrum of the differential.

[0080] As an optional embodiment, the method further includes: analyzing the load spectrum according to durability index requirement information, a target sales region, and a target object range to obtain a target load spectrum, wherein the target load spectrum is used to represent a load spectrum that meets the requirements, the durability index requirement information is used to represent a standard that should be met during the expected service life of the vehicle, the target sales region is used to represent a geographical region where the vehicle is planned to be sold, and the target object range is used to represent a range in which target objects applying the vehicle are located.

[0081] In this embodiment, the damage value and the usage frequency in the load spectrum can be adjusted with reference to the durability standard that should be met during the expected service life of the vehicle, to ensure that the differential design can maintain stable performance throughout the life cycle and does not occur premature wear or failure. The geographical environment, climate conditions, road conditions, and driving habits of the target sales region can be analyzed to weight the data in the load spectrum. For example, if the target sales region is mostly mountainous or in a cold region, the load data under mountain driving and low-temperature environment should be given a higher weight to reflect the real requirements on the differential. The load spectrum data can be further subdivided according to the needs and preferences of the target objects (i.e., user groups). For example, for young users who pursue high-performance driving experience, their driving style may be more aggressive than that of ordinary users, and more high-load working condition data such as high-speed cornering and emergency braking is required; and for users who commute daily, they may pay more attention to stability, and thus the data of low-speed straight driving working condition is more critical.

[0082] Optionally, through the above steps, the original load spectrum data will be optimized and adjusted to generate a customized target load spectrum that focuses on the target vehicle durability standards, target sales region characteristics, and target user needs. The target load spectrum provides precise direction for the design of the differential. Designers can strengthen specific design elements of the differential, such as material selection, gear strength, performance of the lubrication system, etc., based on the high-damage working condition area in the target load spectrum, thereby improving overall durability and reliability.

[0083] In the embodiment of the present application, by analyzing the operation data, the key parameters of the differential are calculated based on the operation data, including the left half shaft speed, the right half shaft speed, the speed difference, and the differential rate, the working conditions of the vehicle are finely divided in combination with the differential data and the motor data (input speed and torque), the motor input torque and the speed difference are jointly loaded for each type of working condition, the frequency of the torque and speed difference combination under different working conditions is counted to obtain the load counting result; based on the load counting result, the damage value of the differential in the vehicle under the working condition of the vehicle is determined; the load spectrum of the differential is determined by comprehensively considering the load counting result and the damage value, the fatigue damage and load characteristics of the differential in the whole life cycle of the vehicle are accurately evaluated and predicted, the technical problem of low accuracy of determining the load spectrum of the differential of the vehicle is solved, and the technical effect of improving the accuracy of determining the load spectrum of the differential of the vehicle is realized.

[0084] The technical solutions of the embodiments of the present application will be illustrated below in conjunction with preferred embodiments.

[0085] At present, the differential is a key component of the automobile transmission system, mainly playing the role of adjusting the speed difference and torque distribution of the wheels, and the development and verification of the differential are mainly based on the habits of traditional car users or relevant verification. However, due to the high-frequency energy recovery of new energy vehicles and the transient high-torque characteristics of the electric drive system, the external load characteristics of the differential are more complex and severe, and the failure rate is much higher than that of traditional vehicles. Therefore, it is urgent to analyze the operation characteristics of new energy vehicles to provide accurate input for the development and verification of differential products that meet the needs of new energy vehicle users.

[0086] In the related art, data information is acquired by collecting the route and terrain of an actual test track, and differential working condition response data is acquired by using a simulation model, such as full load + curve + ramp working condition, separation road surface working condition, eight-character road winding working condition, high-speed curve passing working condition, medium-speed turning working condition, and low-speed turning working condition. The method has fixed test scenarios, and cannot cover the randomness of actual driving of users, such as lack of snow and rain ground driving in the north, and differential working conditions of large damage such as escape. After mileage extrapolation, the high differential damage is greatly underestimated. Secondly, the above working condition combination and the verified mileage after combination cannot be accurately associated with the user's full life cycle demand and coverage, which easily leads to over-design or under-design. In addition, the simulation of differential working condition data by using an electric drive differential durability simulation model directly affects the accuracy of the differential working condition related data, and further affects the accuracy of the load construction. Therefore, there is still a technical problem of low accuracy of determining the load spectrum of the differential of the vehicle.

[0087] The embodiment of the present application proposes a new energy vehicle differential working condition division and load counting method based on user big data, aiming to solve the problems of low correlation between current differential development input and new energy vehicle users and missing user working condition mapping. By accessing running data (sampling frequency 100 Hz) of ≥10,000 new energy vehicle users, working conditions are divided based on the running characteristics of new energy vehicles, a user real differential load feature library is constructed, damage calculation is performed, and the full life cycle load spectrum meeting the user demand is output by comprehensively considering the durability index demand of the whole vehicle, the main sales area and the covered user range, solving the problems of small sample size of traditional real vehicle, incomplete collection coverage, high cost and long cycle. The load spectrum meeting the target demand can be accurately constructed by the method, thereby providing the input of the actual demand of new energy vehicle users for product design, simulation and verification, improving the accuracy of reliability development, reducing the market failure rate, solving the technical problem of low accuracy of determining the load spectrum of the differential of the vehicle, and achieving the technical effect of improving the accuracy of determining the load spectrum of the differential of the vehicle.

[0088] The embodiment of the present application will be further introduced below.

[0089] Figure 2 A flowchart of a new energy vehicle differential working condition division and load counting method according to the embodiment of the present application is shown in FIG. 1, which can include the following steps. Figure 2

[0090] In step S201, vehicle networking running data is acquired.

[0091] In this embodiment, vehicle networking running data (running data) can be acquired, and is filtered according to the demand of matching new energy vehicles. The filtering factors can include the following aspects: user vehicle selection, user region selection, running month selection, mileage screening, and signal extraction.​

[0092] Optionally, the user vehicle type selection can be as consistent as possible with the target matching vehicle type power configuration and vehicle parameters, and the maximum acceleration of the vehicle, the vehicle weight, the wheel radius and other related parameters that affect the wheel end torque response can be considered.

[0093] Optionally, the user region selection can include high-dimensional cold regions, where users have more snow and rain weather, and it is more likely to occur in large differential speed working conditions, and the durability and limit function requirements of the differential are more demanding. Lack of users in this region may result in incomplete coverage of working conditions and insufficient durability target construction strength.

[0094] Optionally, during the running month selection process, since the differential running working condition in the area with more ice and snow is more sensitive to the running month, the user's complete running data for one year is selected as the input as much as possible.

[0095] Optionally, during the mileage screening process, since the annual mileage is greater than 1000 kilometers, a large enough driving distance can fully represent the driving characteristics of the user.

[0096] Optionally, during the signal extraction process, if it is a pure electric vehicle, the motor torque, motor speed, left front wheel speed, right front wheel speed, left rear wheel speed, right rear wheel speed, time, mileage, and speed signals need to be extracted. If it is a hybrid vehicle driven by an electric motor and an engine, the torque and speed signals of the engine and other driving power sources need to be extracted additionally to ensure the completeness of the differential end power source analyzed.

[0097] Step S202, data cleaning processing is performed on the vehicle networking running data.

[0098] In this embodiment, since the vehicle networking running data is incomplete due to packet loss during transmission, the sensor signal is distorted or jumps due to road bumps, resulting in low data quality and affecting the accuracy of data analysis. Therefore, data cleaning processing is needed. For example, threshold value processing, piecewise interpolation, null value deletion, wheel speed inspection, and data resampling.

[0099] Optionally, the threshold value can be set according to the characteristics of the powertrain of the matched vehicle, and the values exceeding the threshold value are identified as abnormal values and are removed. The main threshold values can be motor torque, motor speed, engine torque, engine speed, and wheel speed. The data exceeding the threshold value can be filled by piecewise interpolation. The rows with all empty signals can be deleted. To ensure the accuracy of the speed difference calculation, the left and right wheel speeds must be non-empty at the same time, and the data that does not meet the condition is deleted by row. Since the sampling frequencies of different signals are inconsistent, the data points cannot be one-to-one corresponding in time, and the data needs to be resampled to realize data alignment.

[0100] Step S203, data preprocessing is performed.

[0101] In this embodiment, differential correlation parameters such as left and right half shaft rotation speeds, rotation speed difference, differential rate can be increased to provide input for subsequent distribution statistics.

[0102] The left and right half shaft rotation speeds can be determined by the following formula:

[0103]

[0104] Wherein, v l ,v r may be used to represent the left wheel speed and the right wheel speed, respectively, in units of km / h; d can be used to represent the tire rolling diameter, in units of m; n can be used to represent the half shaft rotation speed, in units of r / min; n l may be used to represent the left half shaft rotation speed, n r may be used to represent the right half shaft rotation speed, all in units of r / min.

[0105] The rotation speed difference can be determined by the following formula:

[0106] Δ n = n l -n r

[0107] The differential rate can be determined by the following formula:

[0108]

[0109] Step S204, working condition division is performed.

[0110] In this embodiment, working condition division can be performed according to the operating characteristics of new energy vehicles.

[0111] Table 1 is a working condition division table according to an embodiment of the present application, as shown in Table 1, there are a total of 8 working conditions. Among them, TMspeed can be used to represent the input speed of the motor (motor input speed), TMtorque can be used to represent the input torque of the motor (motor input torque).

[0112] Table 1 Working condition division table

[0113]

[0114] Step S205, load counting is performed.

[0115] In this embodiment, based on the above eight subdivided operating conditions, a joint count of motor input torque (TMtorque) and speed difference (Δn) can be performed. The vertical axis represents torque, and the horizontal axis represents speed difference. Intervals can be defined as needed, for example, 128 intervals, to obtain the differential speed revolutions under the torque and speed difference in each interval. The differential speed revolutions N of the speed difference Δnj are... ij It can be determined by the following formula:

[0116] N ij =Δnj*f / 60

[0117] Where f can be used to represent the sampling frequency after resampling.

[0118] Optionally, this yields the torque difference count results for eight subdivided operating conditions, which can be used for comparative analysis of these subdivided operating conditions. Operating condition data can be merged according to analysis needs. For example, to analyze the load characteristics of forward and reverse driving, the forward and reverse datasets can be selected for statistical calculations respectively; to analyze the load characteristics of drive and energy recovery operating conditions, the drive and energy recovery datasets can be selected for statistical calculations; alternatively, all datasets can be selected to obtain the torque-speed difference count graph for that user.

[0119] Figure 3 This is a schematic diagram illustrating the distribution characteristics of user load speed difference according to an embodiment of the present invention, as shown below. Figure 3 As shown, region A represents the load distribution characteristics under energy recovery + left turn conditions, region B represents the load distribution characteristics under energy recovery + right turn conditions, region C represents the load distribution characteristics under drive + left turn conditions, and region D represents the load distribution characteristics under drive + right turn conditions. Since traditional gasoline vehicles do not have energy recovery, the load distribution in regions A and B can be essentially ignored. Figure 3 As shown, new energy vehicles have a large number of energy recovery conditions, so the design of the differential for new energy vehicles must fully consider the load requirements of energy recovery conditions.

[0120] Figure 4 This is a schematic diagram of another user load speed difference distribution characteristic according to an embodiment of the present invention, such as... Figure 4 As shown, for the same as Figure 3 The torque distribution charts for different users with the same mileage show identical maximum and minimum values ​​and proportional relationships on both axes, but significant differences in statistical distribution. Figure 3 Compared to users, Figure 4 Users experience a large number of operating conditions with large speed differences, and high torque conditions are also relatively concentrated.

[0121] Step S206: Calculate the pseudo-damage.

[0122] In this embodiment, based on the above full-condition torque speed difference distribution diagram, the pseudo damage of each user can be calculated, and the differential circle number Ni of each torque interval Ti is represented as:

[0123]

[0124] The pseudo damage of each user can be determined by the following formula:

[0125]

[0126] Wherein, m is related to the failure model, different failure models m take different values, if it is a tapered bearing, it can be 3.33; if the analysis is the bending fatigue of the half gear, it can be 7.69, which is derived from the SN curve parameters.

[0127] Table 2 is a user pseudo damage statistical table according to an embodiment of the present application, as shown in Table 2, which shows the pseudo damage of different users under different driving mileage.

[0128] Table 2 user pseudo damage statistical table

[0129]

[0130] Step S207, output the load spectrum.

[0131] In this embodiment, the load spectrum is determined by comprehensively considering the durability index requirement of the whole vehicle, the main sales area and the range of users covered, for example, the sales area contains extremely cold regions, and covers 95% of users, then the user load characteristic distribution of 95th percentile in high latitude area can be selected, and the load count in the whole life cycle is converted through the mileage, as the input of the damage calculation and verification of the new energy vehicle planetary gear and half shaft gear.

[0132] According to the statistical results in Table 1, assuming that user VIN1 in Table 1 is selected as an example, the method of constructing the whole life cycle load characteristic spectrum is explained. The user driving mileage S1, the design target mileage S0, and the count results of the user VIN1 selected running data mileage S1 are shown in Figure 1 , which includes the count of left and right turning conditions under energy recovery and driving conditions, and the load characteristic count N ij of each torque interval and each speed difference interval.

[0133]

[0134] The above count spectrum can be used as the design spectrum, wherein the number of torque and speed difference intervals can be adjusted according to the requirements. Based on this, the verification sample number is converted into a fixed torque and fixed speed difference test verification spectrum.

[0135] According to an embodiment of the present application, a device for determining a load spectrum of a differential of a vehicle is provided. It should be noted that the device for determining the load spectrum of the differential of the vehicle can be used to execute the method for determining the load spectrum of the differential of the vehicle.

[0136] Figure 5 FIG. 1 is a schematic diagram of a device for determining a load spectrum of a differential of a vehicle according to an embodiment of the present application. As shown in FIG. 1, the device 500 for determining the load spectrum of the differential of the vehicle can include an obtaining unit 502, a first determining unit 504, a classifying unit 506, a counting unit 508, and a second determining unit 510. Figure 5

[0137] The obtaining unit 502 is configured to obtain operation data of the vehicle, wherein the operation data is used to represent at least an operation state of the vehicle.

[0138] The first determining unit 504 is configured to determine differential data of the vehicle based on the operation data, wherein the differential data includes a left half axle speed and a right half axle speed of the vehicle, a speed difference between the left half axle speed and the right half axle speed, and a differential rate, wherein the differential rate is used to represent a proportion of the speed difference relative to an average half axle speed of the vehicle in a target time period.

[0139] The classifying unit 506 is configured to classify a working condition of the vehicle based on the differential data and motor data of the vehicle, to obtain a classification result, wherein the motor data is used to represent an input speed of a motor and an input torque of the motor in the vehicle.

[0140] The counting unit 508 is configured to jointly count the input torque and the speed difference based on the classification result, to obtain a load counting result, and determine an injury value of the differential in the working condition of the vehicle based on the load counting result, wherein the load counting result is used to represent a frequency of use of the differential under different load conditions, and the injury value is used to represent a degree of fatigue damage accumulated by the differential.

[0141] The second determining unit 510 is configured to determine a load spectrum of the differential based on the load counting result and the injury value, wherein the load spectrum is used to represent a feature of a fatigue load distribution of the differential in a whole life cycle of the vehicle.

[0142] ​In the embodiment of the present application, the running data of the vehicle is acquired by the acquisition unit 502, wherein the running data is used to at least represent the running state of the vehicle; the differential data of the vehicle is determined by the first determination unit 504 based on the running data, wherein the differential data includes the left half axle speed and the right half axle speed of the vehicle, the speed difference between the left half axle speed and the right half axle speed, and the differential rate used to represent the proportion of the speed difference to the average half axle speed of the vehicle in the target time period; the working condition of the vehicle is classified by the classification unit 506 based on the differential data and the motor data of the vehicle, and the classification result is obtained, wherein the motor data is used to represent the input speed of the motor and the input torque of the motor; the input torque and the speed difference are jointly counted by the counting unit 508 based on the classification result, and the load counting result is obtained, and the damage value of the differential in the working condition of the vehicle is determined based on the load counting result, wherein the load counting result is used to represent the use frequency of the differential under different load conditions, and the damage value is used to represent the accumulated fatigue damage degree of the differential; the load spectrum of the differential is determined by the second determination unit 510 based on the load counting result and the damage value, wherein the load spectrum is used to represent the characteristics of the fatigue load of the differential distributed in the whole life cycle of the vehicle, and the technical problem of low determination accuracy of the load spectrum of the differential of the vehicle is solved, and the technical effect of improving the determination accuracy of the load spectrum of the differential of the vehicle is realized.

[0143] According to the embodiment of the present application, a computer readable storage medium is also provided, which includes a stored program, wherein the program executes the method in the embodiment.

[0144] According to the embodiment of the present application, a processor is also provided, which is used to run a program, wherein the program executes the method in the embodiment when running.

[0145] According to the embodiment of the present application, a vehicle is also provided, which is used to execute the method in the embodiment of the present application.

[0146] In the above embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0147] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other manners. For example, the described unit embodiments can be divided into other ways, for example, the units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, access layers, or middleware layers, and can be in electrical, mechanical, or other forms.

[0148] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed on multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0149] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can be physically present alone, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0150] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0151] The above description is only the preferred embodiments of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, several improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method of determining a load spectrum of a differential of a vehicle, characterized in that, The method comprises: acquiring running data of a vehicle, wherein the running data is used at least to represent a running state of the vehicle; determining differential data of the vehicle based on the running data, wherein the differential data comprises a left half axle rotation speed and a right half axle rotation speed of the vehicle, a rotation speed difference between the left half axle rotation speed and the right half axle rotation speed, and a differential rate used to represent a proportion of the rotation speed difference relative to an average half axle rotation speed of the vehicle in a target time period; classifying a working condition in which the vehicle is based on the differential data and motor data of the vehicle, to obtain a classification result, wherein the motor data is used to represent an input rotation speed of a motor in the vehicle and an input torque of the motor; jointly counting the input torque and the rotation speed difference based on the classification result, to obtain a load counting result, and determining an injury value of a differential in the vehicle in the working condition in which the vehicle is based on the load counting result, wherein the load counting result is used to represent a frequency of use of the differential in different load conditions, and the injury value is used to represent a degree of fatigue injury accumulated by the differential; determining a load spectrum of the differential based on the load counting result and the injury value, wherein the load spectrum is used to represent characteristics of fatigue loads of the differential distributed in a whole life cycle of the vehicle.

2. The method of claim 1, wherein, The method further comprises: performing data cleaning processing and data standardization processing on the running data respectively, to obtain target running data, wherein a data quality of the target running data is higher than a data quality of the running data; screening the differential data from the target running data.

3. The method of claim 2, wherein, The method further comprises: in response to the differential data being greater than a differential data threshold value, the input torque being greater than an input torque threshold value, and the input rotation speed being greater than an input rotation speed threshold value, determining that the classification result is that the vehicle is in a first working condition type, wherein the first working condition type is used to represent that the vehicle is in a left turn forward driving working condition; in response to the differential data being less than the differential data threshold value, the input torque being greater than the input torque threshold value, and the input rotation speed being greater than the input rotation speed threshold value, determining that the classification result is that the vehicle is in a second working condition type, wherein the second working condition type is used to represent that the vehicle is in a right turn forward driving working condition; in response to the differential data being greater than the differential data threshold value, the input torque being less than the input torque threshold value, and the input rotation speed being greater than the input rotation speed threshold value, determining that the classification result is that the vehicle is in a third working condition type, wherein the third working condition type is used to represent that the vehicle is in a left turn forward energy recovery working condition. determining that the classification result is the fourth working condition type in response to the differential data being less than the differential data threshold, the input torque being less than the input torque threshold, and the input rotating speed being greater than the input rotating speed threshold, wherein the fourth working condition type is used to represent that the vehicle is in a right-turning forward energy recovery working condition.

4. The method of claim 3, wherein, The method further comprises: determining that the classification result is the fifth working condition type in response to the differential data being greater than the differential data threshold, the input torque being greater than the input torque threshold, and the input rotating speed being less than the input rotating speed threshold, wherein the fifth working condition type is used to represent that the vehicle is in a left-turning reverse driving working condition; determining that the classification result is the sixth working condition type in response to the differential data being less than the differential data threshold, the input torque being greater than the input torque threshold, and the input rotating speed being less than the input rotating speed threshold, wherein the sixth working condition type is used to represent that the vehicle is in a right-turning reverse driving working condition; determining that the classification result is the seventh working condition type in response to the differential data being greater than the differential data threshold, the input torque being less than the input torque threshold, and the input rotating speed being less than the input rotating speed threshold, wherein the seventh working condition type is used to represent that the vehicle is in a left-turning reverse energy recovery working condition; determining that the classification result is the eighth working condition type in response to the differential data being less than the differential data threshold, the input torque being less than the input torque threshold, and the input rotating speed being less than the input rotating speed threshold, wherein the eighth working condition type is used to represent that the vehicle is in a right-turning reverse energy recovery working condition.

5. The method of claim 4, wherein, based on the classification result, performing joint load counting on the input torque and the rotating speed difference to obtain a load counting result, and determining an injury value of the differential in the working condition of the vehicle based on the load counting result, comprising: dividing the input torque and the rotating speed difference into intervals according to a target threshold interval number to obtain motor input torque intervals and rotating speed difference intervals; mapping the differential revolutions per minute of the input torque and the rotating speed difference to the motor input torque intervals and the rotating speed difference intervals in each classification result; determining a combined interval of the motor input torque intervals and the rotating speed difference intervals, and a number of times that the input torque and the rotating speed difference combined interval is in the combined interval, wherein the number of times is used to represent the usage frequency of the differential under different load conditions; determining the number of times as the load counting result; determining the injury value according to the load counting result and an injury model, wherein the injury model is used to evaluate the fatigue damage accumulation of the differential under different load conditions; The method further comprises: sorting the injury values to obtain a sorting result, wherein the sorting result is used to represent the priority of the influence of different combined intervals on the cumulative damage of the differential.

6. The method of claim 5, wherein determining the load spectrum of the differential based on the load count result and the damage value comprises: determining a damage load frequency in the two-dimensional motor input torque interval and the rotational speed difference interval based on a product of the load count result and the corresponding damage value in the motor input torque interval and the rotational speed difference interval; and generating the load spectrum of the differential based on the damage load frequency. The method further comprises:

7. The method according to any one of claims 1 to 6, characterized in that, analyzing the load spectrum according to durability index requirement information, a target sales area, and a target object range to obtain a target load spectrum, wherein the target load spectrum is used to represent a load spectrum that meets requirements, the durability index requirement information is used to represent a standard that should be met during an expected service life of the vehicle, the target sales area is used to represent a geographic area in which the vehicle is planned to be sold, and the target object range is used to represent a range in which the target object to which the vehicle is applied is located. comprises:

8. An apparatus for determining a load spectrum of a differential of a vehicle, characterized in that an acquisition unit configured to acquire running data of a vehicle, wherein the running data is used to at least represent a running state of the vehicle; a first determination unit configured to determine differential data of the vehicle based on the running data, wherein the differential data comprises a left half axle rotational speed and a right half axle rotational speed of the vehicle, a rotational speed difference between the left half axle rotational speed and the right half axle rotational speed, and a differential rate used to represent a proportion of the rotational speed difference relative to an average half axle rotational speed of the vehicle in a target time period; a classification unit configured to classify a working condition in which the vehicle is located based on the differential data and motor data of the vehicle to obtain a classification result, wherein the motor data is used to represent an input rotational speed of a motor in the vehicle and an input torque of the motor; a counting unit configured to jointly count the input torque and the rotational speed difference based on the classification result to obtain a load count result, and determine a damage value of a differential in the vehicle in the working condition in which the vehicle is located based on the load count result, wherein the load count result is used to represent a use frequency of the differential under different load conditions, and the damage value is used to represent a degree of accumulated fatigue damage of the differential; a second determination unit configured to determine a load spectrum of the differential based on the load count result and the damage value, wherein the load spectrum is used to represent a characteristic of fatigue load distribution of the differential in a whole life cycle of the vehicle. The processor is configured to run a program, wherein the program performs the method of any one of claims 1 to 7 when the program is running.

9. A processor, comprising: The processor is configured to run a program, wherein the program performs the method of any one of claims 1 to 7 when the program is running.

10. An electronic device, comprising: The computer readable storage medium comprises a stored program, wherein the program controls a device in which the computer readable storage medium is located to perform the method of any one of claims 1 to 7 when the program is running.

11. A computer readable storage medium, characterized in that, The vehicle is configured to perform the method of any one of claims 1 to 7.

12. A vehicle characterized by comprising: ​

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