Vehicle load calculation method, device, equipment and readable storage medium

Abstract

The present application relates to a vehicle load calculation method, device, equipment and readable storage medium, and relates to the field of vehicle load control technology, including determining the readiness values ​​of each speed interval corresponding to a target vehicle in an unloaded state in each preset travel according to the big data of the Internet of Vehicles; obtaining the operating parameter information of the target vehicle in the target travel, the operating parameter information including the target average vehicle speed, target average power, rolling resistance coefficient and transmission efficiency; screening out the target readiness value corresponding to the target average vehicle speed from the readiness values ​​of all speed intervals in the preset travel corresponding to the target travel; and calculating the load of the target vehicle in the target travel according to the target readiness value and the operating parameter information. Through the present application, the real-time load of the vehicle can be accurately calculated, which does not require the calculation of acceleration, nor the acquisition of high-precision vehicle speed, effectively improving the calculation accuracy of the real-time load of the vehicle.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle load control, and in particular to a vehicle load calculation method, device, equipment and readable storage medium. Background Art

[0002] In the automotive field, vehicle load is closely related to fuel consumption, operating costs, etc. Therefore, in many cases, in order to maximize the one-way economy, serious overloading will occur; and this overloading behavior will not only accelerate engine damage and component aging and reduce braking performance, but also seriously damage road infrastructure. More importantly, it is also very easy to cause tire blowouts, sudden deviation, brake failure, rollover and other safety accidents due to excessive tire load and deformation, which seriously threaten the lives of people on the vehicle. Therefore, it is very important to monitor the vehicle load. However, in real life, the real-time load of the vehicle can only be understood through the data reported by the driver, but the authenticity and accuracy of the real-time load reported by the driver cannot be guaranteed, so that the effective monitoring of the vehicle load cannot be achieved.

[0003] In related technologies, the real-time load of a vehicle is often calculated based on Newton's second law, and the dimension and accuracy requirements of the data acquisition technology are very high; however, the parameters collected in practice often have errors, which in turn affect the accuracy and precision of the acceleration value, so that the accuracy of the vehicle load result calculated based on the acceleration value with poor accuracy and precision is also poor. Summary of the invention

[0004] The present application provides a vehicle load calculation method, device, equipment and readable storage medium to solve the problem that the vehicle load cannot be accurately calculated in the related art.

[0005] In a first aspect, a vehicle load calculation method is provided, comprising the following steps:

[0006] Determine the maintenance value of each speed range of the target vehicle in an unloaded state within each preset journey based on the big data of the Internet of Vehicles;

[0007] Acquiring operating parameter information of the target vehicle within a target range, the operating parameter information including a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency;

[0008] Filtering out a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip;

[0009] The load of the target vehicle within the target range is calculated based on the target readiness value and the operating condition parameter information.

[0010] In some embodiments, the Internet of Vehicles big data includes the instantaneous vehicle speed, instantaneous rotation speed, instantaneous torque percentage and timestamp of the target vehicle in an unloaded state, and the determining of the readiness value of each vehicle speed interval corresponding to each preset travel section of the target vehicle in an unloaded state according to the Internet of Vehicles big data includes:

[0011] Dividing the timestamp of the target vehicle according to a preset division rule to obtain multiple preset trips;

[0012] Calculating a plurality of average vehicle speeds corresponding to each preset journey based on the instantaneous vehicle speed;

[0013] Calculating an average speed and an average torque percentage corresponding to each average vehicle speed based on the instantaneous speed and the instantaneous torque percentage;

[0014] Calculate the average torque corresponding to each average vehicle speed based on the average speed and the average torque percentage;

[0015] Calculate the average power corresponding to each average vehicle speed based on the average torque and the average speed;

[0016] Determine a plurality of vehicle speed intervals within each preset journey according to the average vehicle speed;

[0017] The readiness value for each vehicle speed interval is calculated according to the average vehicle speed and the average power.

[0018] In some embodiments, the calculating the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information includes:

[0019] Substituting the target trim value, the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency into a first calculation formula to obtain the load of the target vehicle within the target range, the first calculation formula is:

[0020] Δm=(P1*η / V1-min(P2*η / V2)) / g / f

[0021] Wherein, Δm represents the load, P1 represents the target average power, V1 represents the target average vehicle speed, min(P2 / V2) represents the target curb value of the target vehicle in an unloaded state within the target range and corresponding to the target average vehicle speed, η represents the transmission efficiency, f represents the rolling resistance coefficient, and g represents the acceleration of gravity.

[0022] In some embodiments, the rolling resistance coefficient is determined based on road conditions and / or tire conditions.

[0023] In a second aspect, a vehicle load calculation device is provided, comprising:

[0024] A determination unit, which is used to determine the readiness value of each vehicle speed interval corresponding to each preset journey of the target vehicle in an unloaded state according to the big data of the Internet of Vehicles;

[0025] An acquisition unit, which is used to acquire operating parameter information of the target vehicle within a target range, wherein the operating parameter information includes a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency;

[0026] a screening unit, configured to screen out a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip;

[0027] A calculation unit is used to calculate the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information.

[0028] In some embodiments, the Internet of Vehicles big data includes the instantaneous vehicle speed, instantaneous rotation speed, instantaneous torque percentage and timestamp of the target vehicle in an unloaded state, and the determination unit is specifically used to:

[0029] Dividing the timestamp of the target vehicle according to a preset division rule to obtain multiple preset trips;

[0030] Calculating a plurality of average vehicle speeds corresponding to each preset journey based on the instantaneous vehicle speed;

[0031] Calculating an average speed and an average torque percentage corresponding to each average vehicle speed based on the instantaneous speed and the instantaneous torque percentage;

[0032] Calculate the average torque corresponding to each average vehicle speed based on the average speed and the average torque percentage;

[0033] Calculate the average power corresponding to each average vehicle speed based on the average torque and the average speed;

[0034] Determine a plurality of vehicle speed intervals within each preset journey according to the average vehicle speed;

[0035] The readiness value for each vehicle speed interval is calculated according to the average vehicle speed and the average power.

[0036] In some embodiments, the computing unit is specifically used for:

[0037] Substituting the target trim value, the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency into a first calculation formula to obtain the load of the target vehicle within the target range, the first calculation formula is:

[0038] Δm=(P1*η / V1-min(P2*η / V2)) / g / f

[0039] Wherein, Δm represents the load, P1 represents the target average power, V1 represents the target average vehicle speed, min(P2 / V2) represents the target curb value of the target vehicle in an unloaded state within the target range and corresponding to the target average vehicle speed, η represents the transmission efficiency, f represents the rolling resistance coefficient, and g represents the acceleration of gravity.

[0040] In some embodiments, the rolling resistance coefficient is determined based on road conditions and / or tire conditions.

[0041] In a third aspect, a vehicle load calculation device is provided, comprising: a memory and a processor, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the aforementioned vehicle load calculation method.

[0042] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer storage medium stores a computer program, and when the computer program is executed by a processor, the aforementioned vehicle load calculation method is implemented.

[0043] The beneficial effects brought about by the technical solution provided by this application include: it can effectively improve the calculation accuracy of the real-time load of the vehicle.

[0044] The present application provides a vehicle load calculation method, device, equipment and readable storage medium, including determining the readiness values ​​of each speed interval corresponding to each preset journey of a target vehicle in an unloaded state according to the big data of the Internet of Vehicles; obtaining the operating parameter information of the target vehicle in the target journey, the operating parameter information including the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency; screening out the target readiness value corresponding to the target average vehicle speed from the readiness values ​​of all speed intervals in the preset journey corresponding to the target journey; calculating the load of the target vehicle in the target journey according to the target readiness value and the operating parameter information. The present application determines the readiness values ​​of each speed interval of a vehicle in an unloaded state in each preset journey through the big data of the Internet of Vehicles, and then determines the corresponding readiness value according to the corresponding relationship between the target average vehicle speed in the target journey and the speed interval, and finally calculates the vehicle load according to the readiness value, the average vehicle speed and the average power, etc. It does not need to calculate the acceleration, nor does it need to collect high-precision vehicle speed, which effectively improves the calculation accuracy of the real-time vehicle load. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 A schematic diagram of a vehicle load calculation method provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of the structure of a vehicle load calculation device provided in an embodiment of the present application;

[0048] Figure 3 A schematic diagram of the structure of a vehicle load calculation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0050] The embodiments of the present application provide a vehicle load calculation method, device, equipment and readable storage medium, which can solve the problem of the inability to accurately calculate the vehicle load existing in the related art.

[0051] To solve the above technical problems, the overall idea of ​​this application is as follows:

[0052] A vehicle load calculation method, the method comprising the following steps:

[0053] Step S10: determining the readiness values ​​of the target vehicle in an unloaded state in each speed range corresponding to each preset trip according to the Internet of Vehicles big data;

[0054] Step S20: acquiring operating parameter information of the target vehicle within a target range, wherein the operating parameter information includes a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency;

[0055] Step S30: selecting a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip;

[0056] Step S40: Calculate the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information.

[0057] See also Figure 1 As shown, the embodiment of the present application provides a vehicle load calculation method, comprising the following steps:

[0058] Step S10: determining the readiness values ​​of the target vehicle in an unloaded state in each speed range corresponding to each preset trip according to the Internet of Vehicles big data;

[0059] Furthermore, the Internet of Vehicles big data includes the instantaneous vehicle speed, instantaneous rotation speed, instantaneous torque percentage and timestamp of the target vehicle in an unloaded state, and the determination of the readiness value of each vehicle speed interval corresponding to each preset trip of the target vehicle in an unloaded state according to the Internet of Vehicles big data includes:

[0060] Dividing the timestamp of the target vehicle according to a preset division rule to obtain multiple preset trips;

[0061] Calculating a plurality of average vehicle speeds corresponding to each preset journey based on the instantaneous vehicle speed;

[0062] Calculating an average speed and an average torque percentage corresponding to each average vehicle speed based on the instantaneous speed and the instantaneous torque percentage;

[0063] Calculate the average torque corresponding to each average vehicle speed based on the average speed and the average torque percentage;

[0064] Calculate the average power corresponding to each average vehicle speed based on the average torque and the average speed;

[0065] Determine a plurality of vehicle speed intervals within each preset journey according to the average vehicle speed;

[0066] The readiness value for each vehicle speed interval is calculated according to the average vehicle speed and the average power.

[0067] For example, in this embodiment, the power balance principle is used to calculate the vehicle load, that is, when vehicles of the same model are traveling at a constant speed, the engine output power is the same as the resistance power; therefore, when vehicles of the same model are at the same speed and different loads, only the rolling resistance is different (the influence of weight on the friction torque of the hub bearing can be ignored here). Therefore, if it is assumed that the two vehicles are at the same speed and different loads, the engine output power and the resistance power are different at this time. The difference in resistance power (only rolling resistance is affected) can be obtained by subtracting the engine output power of the two times, and the rolling resistance is directly related to the weight, and the vehicle load can be directly calculated. Therefore, this embodiment can calculate the vehicle load based on the difference in engine output power when the vehicle is in an unloaded state and a non-unloaded state.

[0068] For example, for vehicle A1, it travels at the same speed and within the same distance under the same road conditions with weight M1 and weight M2 (the vehicle is unloaded at this time, so weight M2 refers to the weight of vehicle A1). Therefore, for vehicle A1 with weight M1, there exists:

[0069] P1*η / V1=M1*g*f+F 风阻 1+F 其他

[0070] For vehicle A1 with a weight of M2, there exists:

[0071] P2*η / V2=M2*g*f+F 风阻 2+F 其他 ,

[0072] Where V is the vehicle speed, n is the speed, f is the rolling resistance coefficient, P is the power, η is the transmission efficiency, and g is the acceleration due to gravity. Since the vehicle speeds are similar, that is, V1≈V2 (V is used here instead), then F 风阻 1≈F 风阻 2, so after subtracting the above two equations, we can get:

[0073] (P1-P2)*η / V=(M1-M2)*g*f

[0074] Among them, since △M (load mass, i.e. load) = M1-M2, after integrating the above, we can get:

[0075] △M=(P1-P2)*η / V / g / f=(P1*η / V–P2*η / V) / g / f

[0076] Since the P2 / V of a vehicle in an unloaded state can be expressed as the trim (i.e., minimum power / speed: min(P2 / V)), the above formula can be rewritten based on the trim to obtain:

[0077] △M=(P1*η / V–min(P2*η / V)) / g / f

[0078] Therefore, this embodiment will preset the trim values ​​for different speed ranges within different trips of a vehicle in an unloaded state; so when it is necessary to calculate the load of a vehicle within a certain trip, it is only necessary to use the average speed, average power, transmission efficiency, gravitational acceleration, rolling resistance coefficient of the vehicle within the trip and the corresponding trim value obtained through the correspondence between the average speed and the speed range to calculate how much load is added to the vehicle in the corresponding speed range within the trip relative to the trim, thereby accurately judging the vehicle load.

[0079] Specifically, this embodiment uses a predefined data dictionary to parse, standardize, and perform outlier processing and other data cleaning on the Internet of Vehicles big data (the Internet of Vehicles big data refers to the data generated when the vehicle is running in an unloaded state) uploaded by T-BOX (Telematic-BOX, an intelligent vehicle-mounted terminal); wherein, one piece of Internet of Vehicles big data can be recorded every 1 second, and the Internet of Vehicles big data includes but is not limited to vehicle number, timestamp, instantaneous fuel consumption, engine water temperature, ambient temperature, ambient pressure, gearbox output shaft speed, instrument vehicle speed, altitude, tire speed, latitude, longitude, engine speed, vehicle speed, brake switch signal, throttle opening and torque percentage.

[0080] The timestamps of the vehicles are divided according to the rule that when the time interval between two receipts of Internet of Vehicles big data exceeds the preset time, it is divided into a new trip to obtain multiple preset trips, such as preset trip 1 from 8:00 am to 10:00 am, preset trip 2 from 9:00 am to 10:00 am, preset trip 3 from 10:00 am to 12:00 am, and preset trip 4 from 2:00 pm to 3:30 pm. Among them, the preset time can be set to 15 minutes, and of course it can also be set according to actual needs, which is not limited here. In addition, after the preset trips are divided, each preset trip of each vehicle will be encoded, that is, each preset trip of each vehicle will have a unique number.

[0081] Since each section of the vehicle's journey from the departure point to the destination corresponds to a fixed load, that is, each section of the journey corresponds to a load state; therefore, the readiness value (i.e., minimum power / speed) of each speed interval corresponding to each preset journey can be determined based on the Internet of Vehicles big data. For example, for the above-mentioned preset journey 1: if the corresponding average speed 1 is 15km / h, then the speed interval 1 corresponding to the average speed 1 is 15km / h±5, and the corresponding readiness value 1 is min(P1 / V1); if the average speed 2 corresponding to the preset journey 1 is 21km / h, then the speed interval 2 corresponding to the average speed 2 is 21km / h±5, and the corresponding readiness value 2 is min(P2 / V2); and if the average speed 3 corresponding to the preset journey 1 is 35km / h, then the speed interval 3 corresponding to the average speed 3 is 35km / h±5, and the corresponding readiness value 3 is min(P3 / V3).

[0082] The determination process of the set value 1 of the vehicle speed interval 1 corresponding to the preset trip 1 is explained as an example: the average vehicle speed 1 of the preset trip 1 is calculated by taking the stage where the vehicle speed and speed are relatively stable (for example, the vehicle speed difference is ±5km / h, the engine speed difference is 100rpm, and the vehicle speed stability lasts for more than 5min) and the vehicle speed interval 1 is calculated based on the average vehicle speed 1; then the average speed 1 and the average torque percentage 1 corresponding to the average vehicle speed 1 are calculated, and the average torque 1, the average power 1 and the minimum power / speed 1 (i.e., min(P / V)1) are calculated based on this, and min(P / V)1 is the set value 1 of the vehicle speed interval 1. Among them, the transmission efficiency η≈0.92, P=n*T / 9550; in addition, the average torque can be calculated by the torque calculation formula determined by the mapping relationship between the torque calculation formula and the speed interval shown in Table 1.

[0083] Table 1 Schematic diagram of the relationship between speed range and average torque

[0084]

[0085]

[0086] Step S20: acquiring operating parameter information of the target vehicle within a target range, wherein the operating parameter information includes a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency;

[0087] For example, in this embodiment, the target average speed, target average power, rolling resistance coefficient and transmission efficiency of the target vehicle within the target range need to be obtained first, and then the target trim value can be screened out by the target range and target average speed, wherein the rolling resistance coefficient and transmission efficiency are known numbers.

[0088] Step S30: selecting a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip;

[0089] For example, in this embodiment, assuming that the target trip is from 8:00 am to 10:00 am, and the target average vehicle speed calculated based on the stage in the target trip when the vehicle speed and rotation speed are relatively stable is 23 km / h, then the target trip corresponds to the preset trip 1, and the target average vehicle speed falls within the vehicle speed range 2 in the preset trip 1, so the readiness value 2 (i.e., min(P2 / V2)) is used as the target readiness value of the target vehicle within the target trip.

[0090] Step S40: Calculate the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information.

[0091] Further, the calculating the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information includes:

[0092] Substituting the target trim value, the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency into a first calculation formula to obtain the load of the target vehicle within the target range, the first calculation formula is:

[0093] Δm=(P1*η / V1-min(P2*η / V2)) / g / f

[0094] Wherein, Δm represents the load, P1 represents the target average power, V1 represents the target average vehicle speed, min(P2 / V2) represents the target curb value of the target vehicle in an unloaded state within the target range and corresponding to the target average vehicle speed, η represents the transmission efficiency, f represents the rolling resistance coefficient, and g represents the acceleration of gravity.

[0095] Exemplarily, in this embodiment, after the target trim value, target average vehicle speed, target average power, rolling resistance coefficient and transmission efficiency are obtained in the aforementioned steps, the target trim value, target average vehicle speed, target average power, rolling resistance coefficient and transmission efficiency are substituted into the first calculation formula to obtain the load of the target vehicle within the target range. The first calculation formula is:

[0096] Δm=(P1*η / V1-min(P2*η / V2)) / g / f

[0097] Wherein, Δm represents the load of the target vehicle within the target range, P1 represents the target average power, V1 represents the target average vehicle speed, min(P2 / V2) represents the target curb value of the target vehicle in an unloaded state within the target range corresponding to the target average vehicle speed, η represents the transmission efficiency, f represents the rolling resistance coefficient, and g represents the acceleration of gravity.

[0098] It can be seen that this embodiment can accurately calculate the vehicle load based on the actual vehicle operating data combined with the mathematical model, and timely grasp the actual loading habits of users. At the same time, this method does not rely on too many assumptions, and uses the basic signal fields generally collected by the Internet of Vehicles to carry out calculations. This analysis method is applicable to different vehicle types (including passenger cars and commercial vehicles) and different gearbox types (manual and automatic), with a wide range of applications and no limitations.

[0099] Furthermore, the rolling resistance coefficient is determined based on road conditions and / or tire conditions.

[0100] For example, since the rolling resistance coefficients corresponding to different road conditions (such as highways, provincial roads, national roads, etc.) are different and the rolling resistance coefficients corresponding to different tire conditions (such as tire wear, tire material, etc.) are also different; therefore, in this embodiment, if you want to further obtain a more accurate load value for each trip, you can adjust the rolling resistance coefficients corresponding to tires on different roads or with different wear levels and / or materials, that is, you can optimize the calculation of the load through the rolling resistance coefficient. Specifically, in actual applications, the rolling resistance coefficient can be adjusted for different conditions to obtain a more accurate load value.

[0101] In summary, this embodiment does not require the calculation of acceleration, does not require high speed accuracy (glitches are allowed and no filtering is required), and other signals are common signals, that is, it can accurately calculate the vehicle load when the Internet of Vehicles collects common signals and does not require high accuracy, and can simply and accurately adjust for different road conditions. At the same time, the method involved in this implementation can be directly processed using SparkSQL or HQL commonly used for big data, which is fast and efficient.

[0102] See also Figure 2 As shown, based on the same inventive concept as the method embodiment, the embodiment of the present application provides a vehicle load calculation device, including:

[0103] A determination unit, which is used to determine the readiness value of each vehicle speed interval corresponding to each preset journey of the target vehicle in an unloaded state according to the big data of the Internet of Vehicles;

[0104] An acquisition unit, which is used to acquire operating parameter information of the target vehicle within a target range, wherein the operating parameter information includes a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency;

[0105] a screening unit, configured to screen out a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip;

[0106] A calculation unit is used to calculate the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information.

[0107] Furthermore, the Internet of Vehicles big data includes the instantaneous vehicle speed, instantaneous rotation speed, instantaneous torque percentage and timestamp of the target vehicle in an unloaded state, and the determination unit is specifically used for:

[0108] Dividing the timestamp of the target vehicle according to a preset division rule to obtain multiple preset trips;

[0109] Calculating a plurality of average vehicle speeds corresponding to each preset journey based on the instantaneous vehicle speed;

[0110] Calculating an average speed and an average torque percentage corresponding to each average vehicle speed based on the instantaneous speed and the instantaneous torque percentage;

[0111] Calculate the average torque corresponding to each average vehicle speed based on the average speed and the average torque percentage;

[0112] Calculate the average power corresponding to each average vehicle speed based on the average torque and the average speed;

[0113] Determine a plurality of vehicle speed intervals within each preset journey according to the average vehicle speed;

[0114] The readiness value for each vehicle speed interval is calculated according to the average vehicle speed and the average power.

[0115] Furthermore, the computing unit is specifically used for:

[0116] Substituting the target trim value, the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency into a first calculation formula to obtain the load of the target vehicle within the target range, the first calculation formula is:

[0117] Δm=(P1*η / V1-min(P2*η / V2)) / g / f

[0118] Wherein, Δm represents the load, P1 represents the target average power, V1 represents the target average vehicle speed, min(P2 / V2) represents the target curb value of the target vehicle in an unloaded state within the target range and corresponding to the target average vehicle speed, η represents the transmission efficiency, f represents the rolling resistance coefficient, and g represents the acceleration of gravity.

[0119] Furthermore, the rolling resistance coefficient is determined based on road conditions and / or tire conditions.

[0120] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described device and each unit can refer to the corresponding process in the aforementioned vehicle load calculation method embodiment, and will not be repeated here.

[0121] The vehicle load calculation device provided in the above embodiment can be implemented in the form of a computer program. The computer program can be used in Figure 3 The vehicle load calculation device shown is running.

[0122] An embodiment of the present application also provides a vehicle load calculation device, comprising: a memory, a processor and a network interface connected via a system bus, wherein at least one instruction is stored in the memory, and at least one instruction is loaded and executed by the processor to implement all or part of the steps of the aforementioned vehicle load calculation method.

[0123] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0124] The processor may be a CPU, or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, etc. The processor is the control center of the computer device, and uses various interfaces and lines to connect various parts of the entire computer device.

[0125] The memory can be used to store computer programs and / or modules. The processor realizes various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a video playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as video data, image data, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediacard, SMC), a secure digital (Secure digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device or other volatile solid-state storage device.

[0126] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, all or part of the steps of the aforementioned vehicle load calculation method are implemented.

[0127] The embodiment of the present application implements all or part of the aforementioned process, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of each of the above methods when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0128] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, servers or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0129] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0130] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0131] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A vehicle load calculation method, characterized in that: The following steps are involved: Determine the trim value of each speed interval corresponding to the target vehicle in an unloaded state within each preset travel section according to the Internet of Vehicles big data, wherein the trim value is the minimum power / speed, and the Internet of Vehicles big data includes the instantaneous speed, instantaneous rotation speed, instantaneous torque percentage and timestamp of the target vehicle in an unloaded state; Acquiring operating parameter information of the target vehicle within a target range, the operating parameter information including a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency; Filtering out a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip; Calculate the load of the target vehicle within the target range according to the target trim value and the operating condition parameter information; The method of determining the readiness value of each vehicle speed interval corresponding to each preset trip of the target vehicle in an unloaded state according to the Internet of Vehicles big data includes: Dividing the timestamp of the target vehicle according to a preset division rule to obtain multiple preset trips; Calculating a plurality of average vehicle speeds corresponding to each preset journey based on the instantaneous vehicle speed; Calculating an average speed and an average torque percentage corresponding to each average vehicle speed based on the instantaneous speed and the instantaneous torque percentage; Calculate the average torque corresponding to each average vehicle speed based on the average speed and the average torque percentage; Calculate the average power corresponding to each average vehicle speed based on the average torque and the average speed; Determine a plurality of vehicle speed intervals within each preset journey according to the average vehicle speed; The readiness value for each vehicle speed interval is calculated according to the average vehicle speed and the average power.

2. The vehicle load calculation method according to claim 1, characterized in that: The step of calculating the load of the target vehicle within the target range according to the target readiness value and the operating condition parameter information includes: Substituting the target trim value, the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency into a first calculation formula to obtain the load of the target vehicle within the target range, the first calculation formula is: In the formula, Indicates load, represents the target average power, represents the target average vehicle speed, It indicates the target trim value corresponding to the target average speed within the target range of the target vehicle in the unloaded state. It represents the transmission efficiency. is the rolling resistance coefficient, Represents the acceleration due to gravity.

3. The vehicle load calculation method according to claim 1, characterized in that: The rolling resistance coefficient is determined based on road conditions and / or tire conditions.

4. A vehicle load calculation device, characterized in that: include: a determination unit, configured to determine a trim value of each vehicle speed interval corresponding to a target vehicle in an unloaded state within each preset travel section according to the vehicle networking big data, wherein the trim value is a minimum power / speed, and the vehicle networking big data includes an instantaneous vehicle speed, an instantaneous rotation speed, an instantaneous torque percentage, and a timestamp of the target vehicle in an unloaded state; An acquisition unit, which is used to acquire operating parameter information of the target vehicle within a target range, wherein the operating parameter information includes a target average vehicle speed, a target average power, a rolling resistance coefficient, and a transmission efficiency; a screening unit, configured to screen out a target trim value corresponding to the target average vehicle speed from trim values ​​of all vehicle speed intervals within a preset trip corresponding to the target trip; A calculation unit, used for calculating the load of the target vehicle within the target range according to the target trim value and the operating condition parameter information; The determining unit is specifically used for: Dividing the timestamp of the target vehicle according to a preset division rule to obtain multiple preset trips; Calculating a plurality of average vehicle speeds corresponding to each preset journey based on the instantaneous vehicle speed; Calculating an average speed and an average torque percentage corresponding to each average vehicle speed based on the instantaneous speed and the instantaneous torque percentage; Calculate the average torque corresponding to each average vehicle speed based on the average speed and the average torque percentage; Calculate the average power corresponding to each average vehicle speed based on the average torque and the average speed; Determine a plurality of vehicle speed intervals within each preset journey according to the average vehicle speed; The readiness value for each vehicle speed interval is calculated according to the average vehicle speed and the average power.

5. The vehicle load calculation device according to claim 4, characterized in that: The computing unit is specifically used for: Substituting the target trim value, the target average vehicle speed, the target average power, the rolling resistance coefficient and the transmission efficiency into a first calculation formula to obtain the load of the target vehicle within the target range, the first calculation formula is: In the formula, Indicates load, represents the target average power, represents the target average vehicle speed, It indicates the target trim value corresponding to the target average speed within the target range of the target vehicle in the unloaded state. It represents the transmission efficiency. is the rolling resistance coefficient, Represents the acceleration due to gravity.

6. The vehicle load calculation device according to claim 4, characterized in that: The rolling resistance coefficient is determined based on road conditions and / or tire conditions.

7. A vehicle load calculation device, characterized in that: include: A memory and a processor, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the vehicle load calculation method according to any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle load calculation method according to any one of claims 1 to 3 is implemented.

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