Clutch fault prediction method and device and vehicle

Abstract

The invention discloses a clutch fault prediction method and device and a vehicle, and relates to the technical field of big data. The method comprises the steps of obtaining a sliding friction critical value of a target vehicle according to a clutch model of the target vehicle; determining the current accumulated sliding friction load of the target vehicle according to the target driving data of the target vehicle through an Internet of Vehicles platform; and according to the sliding friction critical value and the current accumulated sliding friction load, whether the target vehicle has a clutch fault or not is determined. According to the technical scheme, the clutch fault prediction accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and particularly to a clutch fault prediction method, device and vehicle. Background Art

[0002] The clutch is a key component in the transmission system of commercial vehicles, mainly responsible for realizing the power transmission and separation between the engine and the transmission, ensuring that the vehicle can shift gears smoothly and operate efficiently under different working conditions, and maintaining stable power output under heavy loads and complex road conditions.

[0003] During long-term operation, the clutch is prone to various faults. The most typical failure mode is that the clutch friction plate wears severely, the friction coefficient decreases, resulting in the engine power being unable to be effectively transmitted to the transmission, manifested as difficult vehicle starting, weak acceleration, the engine speed increasing but the vehicle speed not increasing, and even in severe cases, the clutch friction plate smokes and has a burnt smell.

[0004] Traditional clutch fault detection methods usually require installing additional sensors to monitor the operating state of the clutch. These sensors are not only costly but also easily damaged under the complex working conditions of commercial vehicles, further increasing the maintenance cost. Moreover, most of the existing clutch fault prediction technologies focus on passenger vehicles, and there is still a lack of effective solutions for the complex working conditions and high load requirements of medium and heavy commercial vehicles. Therefore, developing a big data-based clutch fault prediction method applicable to medium and heavy commercial vehicles has important practical significance and broad application prospects. Summary of the Invention

[0005] The present invention provides a clutch fault prediction method, device and vehicle to achieve early prediction of potential clutch faults.

[0006] According to one aspect of the present invention, there is provided a clutch fault prediction method, which includes:

[0007] Obtain the slip friction critical value of the target vehicle according to the clutch model of the target vehicle;

[0008] Determine the current cumulative slip friction load of the target vehicle according to the target driving data of the target vehicle through the vehicle networking platform;

[0009] Determine whether the target vehicle has a clutch fault according to the slip friction critical value and the current cumulative slip friction load.

[0010] According to another aspect of the present invention, there is provided a clutch fault prediction device, which includes:

[0011] A slip friction critical value acquisition module, configured to obtain the slip friction critical value of the target vehicle according to the clutch model of the target vehicle;

[0012] An accumulated sliding friction load determination module, configured to determine the current accumulated sliding friction load of the target vehicle through a vehicle networking platform according to the target driving data of the target vehicle;

[0013] A clutch fault determination module, configured to determine whether the target vehicle has a clutch fault according to the sliding friction threshold value and the current accumulated sliding friction load.

[0014] According to another aspect of the present invention, there is provided a vehicle, including:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the clutch fault prediction method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the clutch fault prediction method according to any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, there is provided a computer program product including a computer program, which implements the clutch fault prediction method according to any embodiment of the present invention when executed by a processor.

[0020] The technical solution of the embodiment of the present invention obtains the sliding friction threshold value of the target vehicle according to the clutch model of the target vehicle; determines the current accumulated sliding friction load of the target vehicle through the vehicle networking platform according to the target driving data of the target vehicle; and determines whether the target vehicle has a clutch fault according to the sliding friction threshold value and the current accumulated sliding friction load. The above technical solution can effectively predict potential faults of the clutch in advance by analyzing the target driving data of the vehicle and combining the sliding friction threshold value of the vehicle, so as to facilitate preventive maintenance.

[0021] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0023] Figure 1 is a flowchart of a clutch fault prediction method provided according to an embodiment of the present invention;

[0024] Figure 2 is a flowchart of a clutch fault prediction method provided according to an embodiment of the present invention;

[0025] Figure 3 is a schematic structural diagram of a clutch fault prediction device provided according to an embodiment of the present invention;

[0026] Figure 4 is a schematic structural diagram of an electronic device for implementing the clutch fault prediction method of the embodiments of the present invention. Detailed implementation manners

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" 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 those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] In addition, it should also be noted that in the technical solutions of the present invention, the collection, storage, use, processing, transmission, provision, and disclosure of relevant data of the vehicle, such as vehicle historical data, target driving data, etc., all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0030] Figure 1 It is a flowchart of a clutch fault prediction method provided according to an embodiment of the present invention. This embodiment is applicable to the situation of how to perform clutch fault prediction, especially applicable to the situation of clutch fault prediction for a commercial vehicle manual transmission based on vehicle networking data; among them, the commercial vehicle is preferably a medium - heavy commercial vehicle. This method can be executed by a clutch fault prediction device, which can be implemented in the form of hardware and / or software and can be integrated into an electronic device with the function of clutch fault prediction, for example, in a commercial vehicle controller. As Figure 1 shown, the method includes:

[0031] S110. Obtain the slip friction critical value of the target vehicle according to the clutch model of the target vehicle.

[0032] In this embodiment, the target vehicle refers to the vehicle for which clutch fault prediction is required. The so - called slip friction critical value refers to the critical load at which the clutch slips.

[0033] Optionally, the slip friction critical value is determined in the following manner: for each clutch model, obtain the vehicle historical data corresponding to the clutch model; determine the total slip friction load of at least one faulty vehicle corresponding to the clutch model according to the vehicle historical data; determine the slip friction critical value corresponding to the clutch model according to the total slip friction load of at least one faulty vehicle.

[0034] Among them, the vehicle historical data is the historical driving data of the faulty vehicle with clutch failure, including but not limited to data such as vehicle speed, engine speed, engine output torque, clutch switch, and timestamp.

[0035] Specifically, for each clutch model, through the vehicle networking system, combined with the vehicle VIN code, obtain the vehicle historical data corresponding to the clutch model. Then, for each faulty vehicle, according to the vehicle historical data of the faulty vehicle, determine the rotational speed difference and slip friction duration at each slip friction stage of the faulty vehicle; determine the slip friction load at each slip friction stage of the faulty vehicle according to the rotational speed difference, engine output torque, and slip friction duration; add up the slip friction loads to obtain the total slip friction load of the faulty vehicle, and then the mean value of the total slip friction loads of at least one faulty vehicle can be obtained to get the slip friction critical value corresponding to the clutch model.

[0036] Furthermore, to determine the slip friction critical value corresponding to the clutch model according to the total slip friction load of at least one faulty vehicle, the total slip friction load of at least one faulty vehicle can also be logarithmically transformed to obtain transformed data; determine the slip friction critical value corresponding to the clutch model according to the mean value and standard deviation of the transformed data, as well as the single - trip mileage of the faulty vehicle.

[0037] Specifically, the total sliding friction load of at least one faulty vehicle is logarithmically transformed to obtain variation data. The mean and standard deviation of at least one variation data are calculated, and in combination with the single-trip mileage of the faulty vehicle, the sliding friction critical value corresponding to this clutch model is determined in stages. For example, if the mean single-trip mileage of at least one faulty vehicle corresponding to this clutch model is less than the first threshold, then the sliding friction critical value corresponding to this clutch model is determined to be the sum of the mean and the set multiple of the standard deviation; wherein, the set multiple can be adaptively set or set by those skilled in the art according to actual needs. If the mean single-trip mileage of at least one faulty vehicle corresponding to this clutch model is greater than or equal to the first threshold and less than the second threshold, then the sliding friction critical value corresponding to this clutch model is determined to be the sum of the mean and the standard deviation. If the mean single-trip mileage of at least one faulty vehicle corresponding to this clutch model is greater than or equal to the second threshold, then the sliding friction critical value corresponding to this clutch model is determined to be the mean. Among them, the first threshold is less than the second threshold, and the first threshold and the second threshold can be adaptively determined or set by those skilled in the art according to actual needs. The first threshold is preferably 100 kilometers, and the second threshold is preferably 300 kilometers.

[0038] It can be understood that since the actual data presents a negative skewed distribution and does not fully conform to the normal distribution, taking the logarithm transformation of the total sliding friction load of the faulty vehicles under each clutch model can compress the skewness of the data and make it closer to the normal distribution, so as to intuitively understand the data change trend and dispersion degree, better grasp the statistical characteristics of the clutch fault data, and then by drawing a histogram, it can be observed that the transformed data basically conforms to the normal distribution form. The mean μ and standard deviation σ of the transformed data are calculated. At the same time, since when the single-trip mileage of the vehicle is less than 100 kilometers, it is usually short-distance transportation, and in such scenarios, it is relatively convenient to find a repair station for maintenance when the vehicle clutch fails. When the single-trip mileage is larger, it indicates that the vehicle's transportation distance is farther, and the transportation failure requirement is also higher. At this time, the vehicle should be maintained earlier to avoid the benefit loss caused by the vehicle's unplanned parking or breakdown on the way. Through the looseness of the threshold setting, the reminder purpose of the corresponding scenario can be achieved to improve the adaptability of the model and the good experience of users.

[0039] In this embodiment, during the operation of the target vehicle, the sliding friction critical value of the target vehicle can be obtained through the vehicle networking platform according to the clutch model of the target vehicle.

[0040] S120. Through the vehicle networking platform, according to the target driving data of the target vehicle, determine the current cumulative sliding friction load of the target vehicle.

[0041] Among them, the current cumulative sliding friction load refers to the total sliding friction load corresponding to the target vehicle from the factory to the current moment.

[0042] An alternative approach is to obtain the target driving data of the target vehicle through the vehicle networking platform, determine a model based on the sliding friction load, and determine the current cumulative sliding friction load of the target vehicle according to the target driving data. Among them, the sliding friction load determination model can be determined based on a machine learning model.

[0043] S130. Determine whether the target vehicle has a clutch failure according to the sliding friction critical value and the current cumulative sliding friction load.

[0044] An alternative approach is to determine that the target vehicle has a clutch failure when the sliding friction critical value reaches the current cumulative sliding friction load.

[0045] Another alternative approach is that if the current cumulative sliding friction load reaches a set percentage of the sliding friction critical value, it is determined that the target vehicle has a clutch failure. Among them, the set percentage can be adjusted adaptively or set by those skilled in the art according to actual needs.

[0046] It can be understood that by setting the percentage, when the current cumulative sliding friction load reaches the set percentage of the sliding friction critical value, it is determined that the target vehicle has a clutch failure, which can ensure that even after it is determined that the vehicle has a clutch failure, there is still a certain guarantee to maintain the normal driving of the vehicle.

[0047] Furthermore, after the clutch failure is identified, a fault prompt is given to the vehicle user. For example, it can be through instrument display, etc., or push fault information through the mobile APP to remind the vehicle user to perform clutch maintenance or replacement. It should be noted that the specific prompt method is not specifically limited in this embodiment.

[0048] The technical solution of the embodiment of the present invention obtains the sliding friction critical value of the target vehicle according to the clutch model of the target vehicle; through the vehicle networking platform, determines the current cumulative sliding friction load of the target vehicle according to the target driving data of the target vehicle; determines whether the target vehicle has a clutch failure according to the sliding friction critical value and the current cumulative sliding friction load. The above technical solution can effectively predict potential clutch failures in advance by analyzing the target driving data of the vehicle and combining the sliding friction critical value of the vehicle, so as to facilitate preventive maintenance.

[0049] Figure 2 It is a flowchart of a clutch failure prediction method provided according to an embodiment of the present invention. On the basis of the above embodiment, this embodiment further optimizes "through the vehicle networking platform, determine the current cumulative sliding friction load of the target vehicle according to the target driving data of the target vehicle", and provides an alternative implementation scheme. As Figure 2 shown, the method includes:

[0050] S210. Obtain the sliding friction critical value of the target vehicle according to the clutch model of the target vehicle.

[0051] S220. Obtain the target driving data at the current slipping friction stage of the target vehicle through the vehicle networking platform.

[0052] Among them, the target driving data includes engine output torque, engine speed, vehicle driving speed, clutch switch signal, speed ratio of the current gear of the transmission, drive axle speed ratio, and tire radius; among them, the speed ratio and tire rolling radius can be queried according to the VIN code; the engine output torque and engine speed can be collected through the vehicle CAN signal. The so-called slipping friction stage refers to the vehicle starting state or emergency braking state.

[0053] Specifically, through the vehicle networking platform, the target driving data at the current slipping friction stage of the target vehicle can be obtained.

[0054] S230. Determine the rotational speed difference and slipping friction duration of the target vehicle at the current slipping friction stage according to the target driving data.

[0055] Among them, the slipping friction duration refers to the continuous duration of a single slipping friction of the clutch, which consists of consecutive discrete moments.

[0056] An optional method for determining the rotational speed difference of the target vehicle at the current slipping friction stage according to the target driving data includes: determining the rotational speed of the transmission input shaft of the target vehicle at the current slipping friction stage according to the speed ratio of the current gear of the transmission, drive axle speed ratio, tire radius, and vehicle driving speed; determining the rotational speed difference according to the rotational speed of the transmission input shaft and the engine speed.

[0057] Specifically, based on a preset formula, determine the rotational speed of the transmission input shaft of the target vehicle at the current slipping friction stage according to the speed ratio of the current gear of the transmission, drive axle speed ratio, tire radius, and vehicle driving speed. For example, it can be determined through the following formula: E b = 2.65 × i g × i0 × V / R; where E b represents the rotational speed of the transmission input shaft; i g represents the speed ratio of the current gear of the transmission; i0 represents the drive axle speed ratio; V represents the vehicle driving speed; R represents the tire radius.

[0058] An optional method for determining the slipping friction duration of the target vehicle at the current slipping friction stage according to the target driving data includes: determining the slipping friction duration of the current slipping friction stage according to the vehicle driving speed and clutch switch signal of the target vehicle.

[0059] Specifically, the duration during which the vehicle driving speed ranges from 0 to greater than 0 and the clutch switch remains on, i.e., the clutch switch information is 1, is used as the slip duration of the current slip stage. Or in the case of an emergency brake, the duration during which the vehicle driving speed suddenly changes from greater than 0 to 0 and the clutch switch remains on, i.e., the clutch switch information is 1, is used as the slip duration of the current slip stage.

[0060] S240. Determine the current slip load of the target vehicle in the current slip stage according to the rotational speed difference, the engine output torque, and the slip duration.

[0061] Specifically, the products of the rotational speed differences and the engine output torques at each moment during the slip duration are added together to obtain the current slip load of the target vehicle in the current slip stage. For example, it can be determined by the following formula: where P n represents the current slip load; ti represents any moment in the current slip stage; n represents the slip duration; Es ti represents the rotational speed difference at the ti-th moment; Ts ti represents the engine output torque at the ti-th moment.

[0062] S250. Obtain the current cumulative slip load according to the current slip load and the historical cumulative slip load before the current slip stage.

[0063] Specifically, the current slip load and the historical cumulative slip load before the current slip stage are added together to obtain the current cumulative slip load.

[0064] S260. Determine whether the target vehicle has a clutch failure according to the slip critical value and the current cumulative slip load.

[0065] The technical solution provided by the embodiments of the present invention obtains the target driving data of the target vehicle in the current slip stage through the vehicle networking platform; wherein, the target driving data includes the engine output torque, the engine rotational speed, the vehicle driving speed, the clutch switch signal, the speed ratio of the current gear of the transmission, the drive axle speed ratio, and the tire radius; according to the target driving data, determine the rotational speed difference and the slip duration of the target vehicle in the current slip stage; according to the rotational speed difference, the engine output torque, and the slip duration, determine the current slip load of the target vehicle in the current slip stage; according to the current slip load and the historical cumulative slip load before the current slip stage, obtain the current cumulative slip load. The above technical solution can, without increasing the vehicle cost, pre-determine the maximum threshold value of the slip load that various types of clutches can withstand, analyze the clutch failure through vehicle networking data, and establish a passive failure analysis, that is, without using a direct slip failure sensor to determine the clutch failure, and indirectly realize the clutch failure prediction through other sensors.

[0066] Figure 3 This is a schematic structural diagram of a clutch fault prediction device provided according to an embodiment of the present invention. The embodiment is applicable to the situation of how to predict clutch faults, and is particularly applicable to the situation of predicting clutch faults of a commercial vehicle manual transmission based on vehicle networking data; among them, the commercial vehicle is preferably a medium - heavy commercial vehicle. The device can be implemented in the form of hardware and / or software, and can be integrated into an electronic device with the function of clutch fault prediction, for example, in a commercial vehicle controller. As Figure 3 shown, the device includes:

[0067] A slip friction critical value acquisition module 310, configured to acquire the slip friction critical value of the target vehicle according to the clutch model of the target vehicle;

[0068] An accumulated slip friction load determination module 320, configured to determine the current accumulated slip friction load of the target vehicle through the vehicle networking platform according to the target driving data of the target vehicle;

[0069] A clutch fault determination module 330, configured to determine whether the target vehicle has a clutch fault according to the slip friction critical value and the current accumulated slip friction load.

[0070] The technical solution of the embodiment of the present invention is to acquire the slip friction critical value of the target vehicle according to the clutch model of the target vehicle; determine the current accumulated slip friction load of the target vehicle through the vehicle networking platform according to the target driving data of the target vehicle; and determine whether the target vehicle has a clutch fault according to the slip friction critical value and the current accumulated slip friction load. The above - mentioned technical solution can effectively predict potential clutch faults in advance by analyzing the target driving data of the vehicle and combining the slip friction critical value of the vehicle, so as to facilitate preventive maintenance.

[0071] Optionally, the accumulated slip friction load determination module 320 is configured to:

[0072] Acquire the target driving data of the target vehicle at the current slip friction stage through the vehicle networking platform; where the target driving data includes engine output torque, engine speed, vehicle driving speed, clutch switch signal, speed ratio of the current gear of the transmission, drive axle speed ratio, and tire radius;

[0073] Determine the rotational speed difference and slip friction duration of the target vehicle at the current slip friction stage according to the target driving data;

[0074] Determine the current slip friction load of the target vehicle at the current slip friction stage according to the rotational speed difference, engine output torque, and slip friction duration;

[0075] Obtain the current accumulated slip friction load according to the current slip friction load and the historical accumulated slip friction load before the current slip friction stage.

[0076] Optionally, the cumulative slip friction load determination module 320 is specifically configured to:

[0077] Determine the rotational speed of the transmission input shaft when the target vehicle is in the current slip friction stage according to the gear ratio of the current gear of the transmission, the drive axle ratio, the tire radius, and the vehicle driving speed;

[0078] Determine the rotational speed difference according to the rotational speed of the transmission input shaft and the engine speed.

[0079] Optionally, the cumulative slip friction load determination module 320 is specifically configured to:

[0080] Determine the slip friction duration of the current slip friction stage according to the vehicle driving speed of the target vehicle and the clutch switch signal.

[0081] Optionally, the device further includes a slip friction critical value determination module, configured to:

[0082] For each clutch model, obtain the vehicle historical data corresponding to the clutch model;

[0083] Determine the total slip friction load of at least one faulty vehicle corresponding to the clutch model according to the vehicle historical data;

[0084] Determine the slip friction critical value corresponding to the clutch model according to the total slip friction load of at least one faulty vehicle.

[0085] Optionally, the slip friction critical value determination module is specifically configured to:

[0086] Perform logarithmic transformation on the total slip friction load of at least one faulty vehicle to obtain transformed data;

[0087] Determine the slip friction critical value corresponding to the clutch model according to the mean and standard deviation of the transformed data and the single-trip mileage of the faulty vehicle.

[0088] Optionally, the clutch fault determination module 330 is specifically configured to:

[0089] If the current cumulative slip friction load reaches a set percentage of the slip friction critical value, determine that the target vehicle has a clutch fault.

[0090] Optionally, it is applied to a commercial vehicle manual transmission.

[0091] The clutch fault prediction device provided by the embodiments of the present invention can execute the clutch fault prediction method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0092] According to an embodiment of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0093] Figure 4 It is a schematic structural diagram of an electronic device for implementing the clutch fault prediction method of the embodiments of the present invention. Among them, the electronic device can be a vehicle. Figure 4 It shows a schematic structural diagram of an electronic device 10 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0094] As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0095] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0096] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the clutch fault prediction method.

[0097] In some embodiments, the clutch fault prediction method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the clutch fault prediction method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the clutch fault prediction method by any other suitable means (e.g., by means of firmware).

[0098] The various embodiments of the systems and techniques described above in this document may be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] The computer program for implementing the method of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer programs may be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0100] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0101] To provide for interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0102] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0103] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0104] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and this is not limited herein.

[0105] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A clutch fault prediction method, characterized in that, Including: Obtain the slip friction critical value of the target vehicle according to the clutch model of the target vehicle; Through the vehicle networking platform, determine the current cumulative slip friction load of the target vehicle according to the target driving data of the target vehicle; Determine whether the target vehicle has a clutch failure according to the slip friction critical value and the current cumulative slip friction load.

2. The method according to claim 1, wherein Through the vehicle networking platform, determine the current cumulative slip friction load of the target vehicle according to the target driving data of the target vehicle, including: Through the vehicle networking platform, obtain the target driving data at the current slip friction stage of the target vehicle; wherein, the target driving data includes engine output torque, engine speed, vehicle driving speed, clutch switch signal, speed ratio of the current gear of the transmission, drive axle speed ratio, and tire radius; According to the target driving data, determine the speed difference and slip friction duration of the target vehicle at the current slip friction stage; According to the speed difference, the engine output torque and the slip friction duration, determine the current slip friction load of the target vehicle at the current slip friction stage; Obtain the current cumulative slip friction load according to the current slip friction load and the historical cumulative slip friction load before the current slip friction stage.

3. The method according to claim 2, wherein According to the target driving data, determine the speed difference of the target vehicle at the current slip friction stage, including: According to the speed ratio of the current gear of the transmission, the drive axle speed ratio, the tire radius and the vehicle driving speed, determine the input shaft speed of the transmission of the target vehicle at the current slip friction stage; Determine the speed difference according to the input shaft speed of the transmission and the engine speed.

4. The method according to claim 2, wherein According to the target driving data, determine the slip friction duration of the target vehicle at the current slip friction stage, including: Determine the slip friction duration of the current slip friction stage according to the vehicle driving speed and the clutch switch signal of the target vehicle.

5. The method according to any one of claims 1-4, characterized in that, The slip friction critical value is determined by the following method: For each clutch model, obtain the vehicle historical data corresponding to the clutch model; Determine the total slip friction load of at least one faulty vehicle corresponding to the clutch model according to the vehicle historical data; Determine the slip friction critical value corresponding to the clutch model according to the total slip friction load of at least one faulty vehicle.

6. The method according to claim 5, wherein Determine the slip friction critical value corresponding to the clutch model according to the total slip friction load of at least one faulty vehicle, including: Perform logarithmic transformation on the total slip friction load of at least one faulty vehicle to obtain transformed data; Determine the slip friction critical value corresponding to the clutch model according to the mean and standard deviation of the transformed data and the single driving mileage of the faulty vehicle.

7. The method according to claim 1, characterized in that, Determine whether the target vehicle has a clutch failure according to the slip friction critical value and the current cumulative slip friction load, including: If the current cumulative slip friction load reaches the set percentage of the slip friction critical value, determine that the target vehicle has a clutch failure.

8. The method according to any one of claims 1-4, applied to a commercial vehicle manual transmission.

9. A clutch fault prediction device, characterized in that, Including: A slip friction critical value acquisition module, configured to obtain the slip friction critical value of the target vehicle according to the clutch model of the target vehicle; An accumulated sliding friction load determination module, configured to determine the current accumulated sliding friction load of the target vehicle through a vehicle networking platform according to the target driving data of the target vehicle; A clutch fault determination module, configured to determine whether a clutch fault occurs in the target vehicle according to the sliding friction critical value and the current accumulated sliding friction load.

10. A vehicle, characterized in that, The vehicle includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the clutch fault prediction method according to any one of claims 1-8.

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