Vehicle health status determination method and driverless vehicle

Abstract

The application provides a vehicle health state determination method and an unmanned vehicle, and can be applied to the technical fields of vehicle control, intelligent auxiliary driving, intelligent mine and vehicle maintenance. The method comprises the following steps: obtaining running information, road surface wet and slippery information and current health information of a target vehicle, wherein the target vehicle comprises a vehicle performing work in an open place, the current health information represents the health state of a vehicle component of the target vehicle, and the running information is collected when the target vehicle performs work; determining a loss increment parameter matched with the road surface wet and slippery information; correcting reference loss information determined based on the running information by using the loss increment parameter, and determining the health state of the vehicle component according to the difference between the corrected reference loss information and the current health information.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical fields of vehicle control, intelligent auxiliary driving, smart mine and vehicle maintenance, and more particularly to a vehicle health state determination method and an unmanned vehicle. BACKGROUND

[0002] With the rapid development of artificial intelligence technology, in open places such as mine operations, work tasks can be performed based on unmanned vehicles to improve work efficiency. However, the environment of mine operation scene is harsh, and it often faces alternating high and low temperature, high dust concentration, rugged and uneven road surface and other complex working conditions. Unmanned vehicles run in this environment for a long time, and vehicle components such as engines, transmission systems and braking devices are prone to wear, aging, failure and other problems. Therefore, it is very important to carry out accurate health state evaluation and maintenance on unmanned vehicles.

[0003] In the process of implementing the present application concept, the inventors found that at least the following problems exist in the related art: the related art uses a fixed prediction model or threshold to evaluate the health degree of the vehicle, ignoring the accelerated wear caused by the working environment factors, resulting in low accuracy of health state evaluation. SUMMARY

[0004] Therefore, the present application provides a vehicle health state determination method and an unmanned vehicle.

[0005] One aspect of the present application provides a vehicle health state determination method, comprising: obtaining running information, road wet slip information and current health information of a target vehicle, wherein the target vehicle includes a vehicle performing work in an open place, the current health information represents the health state of the vehicle components of the target vehicle, and the running information is collected when the target vehicle performs work; determining a wear increment parameter matched with the road wet slip information; correcting reference wear information determined based on the running information by using the wear increment parameter, and determining the health state of the vehicle components according to the difference between the corrected reference wear information and the current health information.

[0006] According to the embodiments of the present application, the wear increment parameter includes a first sub-parameter corresponding to the road surface state; determining the wear increment parameter matched with the road wet slip information comprises: determining road surface state information matched with the road wet slip information; and determining the first sub-parameter according to the relative difference between the road surface state information and reference road surface state information, wherein the reference road surface state information includes the road surface state of the open place under reference road wet slip information.

[0007] According to an embodiment of the present application, the wear increment parameter comprises a second sub-parameter corresponding to braking performance of the target vehicle; determining the wear increment parameter matching the road surface wetness information comprises: determining reference braking information of the target vehicle when running in a running state indicated by the reference road surface wetness information and the running information, if the road surface wetness information satisfies a predetermined condition; and determining the second sub-parameter according to a deviation between the braking information in the running information and the reference braking information.

[0008] Preferably, the running information at least comprises at least one of the following: road surface type, road surface slope, load state, braking information.

[0009] According to an embodiment of the present application, the braking information comprises braking times and braking performance parameters; and determining the second sub-parameter according to a deviation between the braking information in the running information and the reference braking information comprises: determining the second sub-parameter according to a first deviation between the braking times and reference braking times, and a second deviation between the braking performance parameters and reference braking performance parameters; and preferably, the second sub-parameter is obtained by weighted sum of the first deviation and the second deviation, and the weights of the first deviation and the second deviation are determined based on historical running information of the target vehicle.

[0010] According to an embodiment of the present application, the wear increment parameter comprises a first sub-parameter and a second sub-parameter; and determining the wear increment parameter matching the road surface wetness information comprises: fusing the first sub-parameter and the second sub-parameter to obtain the wear increment parameter.

[0011] Preferably, the first sub-parameter has a greater impact on the wear increment parameter than the second sub-parameter.

[0012] According to an embodiment of the present application, the vehicle component comprises a braking device; and determining the health state of the vehicle component according to a difference between the reference wear information determined based on the running information and the current health information, by correcting the reference wear information with the wear increment parameter, comprises: correcting reference wear information of a single braking operation with the wear increment parameter to obtain corrected reference wear information of the single braking operation; and determining the health state of the braking device according to a difference between the corrected reference wear information of the single braking operation and the current health information.

[0013] According to an embodiment of the present application, the reference wear information of the single braking operation comprises a difference between hardware wear information before and after the braking device performs the single braking operation when the target vehicle runs in a running state indicated by the running information; and / or the reference wear information comprises heat wear information caused by the braking device performing the single braking operation when the target vehicle runs in the running state indicated by the running information.

[0014] According to an embodiment of the present application, the method further comprises: in the case that the road wetness information is road wetness information at a future time point after the current time point, correcting the reference loss information determined based on the estimated operation information by using the loss increment parameter, and determining the health state of the vehicle component according to a difference between the corrected reference loss information and the current health information, wherein the estimated operation information is determined according to a job to be performed by the target vehicle at the future time point.

[0015] According to an embodiment of the present application, the method further comprises: in the case that the health state satisfies the early warning condition, generating early warning information for the target vehicle.

[0016] Preferably, in the case that the road wetness information is road wetness information at a future time point and the health state satisfies the early warning condition, the early warning information is generated to maintain the target vehicle before performing the job to be performed based on the early warning information.

[0017] An aspect of the present application provides an unmanned vehicle, comprising: a processor configured to execute the vehicle health state determination method.

[0018] An embodiment of the present application considers not only the operation information and the current health information of the target vehicle itself, but also the road wetness information representing the environmental factors. By determining the loss increment parameter matched with the road wetness information and correcting the reference loss information determined based on the operation information by using the loss increment parameter, the equipment loss law under different wet and slippery working conditions can be adapted in real time, so that the corrected reference loss information is more suitable for the actual working state, solving the problem that the traditional fixed life model and threshold cannot cope with real-time working condition fluctuations. Then, the difference between the current health information representing the real-time state of the vehicle component and the corrected reference loss information is used to determine the health state, which can improve the dynamicity and accuracy of health state evaluation, reduce safety problems such as false negatives, false positives, and sudden failures, and further reduce the vehicle maintenance cost based on the health state. BRIEF DESCRIPTION OF DRAWINGS

[0019] The above and other objects, features and advantages of the present application will become more apparent from the following description when taken in conjunction with the accompanying drawings, in which:

[0020] Figure 1 An exemplary system architecture to which the vehicle health state determination method and device according to an embodiment of the present application can be applied is shown.

[0021] Figure 2 A flowchart of a vehicle health state determination method according to an embodiment of the present application is shown.

[0022] Figure 3A flow chart of a method of correcting reference loss information according to a loss increment parameter and determining a health state according to an embodiment of the present application is shown.

[0023] Figure 4 A scenario diagram of determining a health state according to an embodiment of the present application is shown.

[0024] Figure 5 A structure diagram of a vehicle health state determination apparatus according to an embodiment of the present application is shown.

[0025] Figure 6 A block diagram of an unmanned vehicle adapted to implement the method described above according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. It should be understood, however, that the description which follows is merely illustrative and is not intended to limit the scope of the present application. In the following detailed description of embodiments of the present application, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one skilled in the art that one or more embodiments of the present application can be practiced without these specific details. In other instances, well-known structures and functions have not been described in detail in order to avoid obscuring aspects of the present application.

[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used herein, the term "includes" and tautological equivalents thereof, means that the named feature, step, operation, and / or component is present, but not excluding the presence or addition of one or more other features, steps, operations, or components.

[0028] All terms used herein including technical and scientific terms have the same meanings as commonly understood by one of ordinary skill in the art unless otherwise defined herein. It should be noted that the terms used herein are merely specific embodiments proposed by the inventor(s) for the purpose of descriptions based on prior art to the best of the inventor(s) understanding, and are not intended to be limiting of the present application. Accordingly, it should be understood that there can be many variations made to the preferred embodiments described herein without departing from the spirit and scope of the application.

[0029] In the case where expressions similar to "at least one of A, B, and C, etc." are used, it is generally intended to mean the same as "at least one of A, B, and C, etc." unless otherwise noted. For example, "a system having at least one of A, B, and C" is intended to include a system having A alone, a system having B alone, a system having C alone, a system having A and B together, a system having A and C together, a system having B and C together, and / or a system having A, B, and C together, etc.

[0030] In the embodiments of the present application, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) comply with the relevant legal regulations, are used for legal purposes, and do not violate public order and good customs. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and to maintain user personal information security, network security and other security.

[0031] In the embodiments of the present application, the authorization or consent of the user is obtained before the user personal information is acquired or collected.

[0032] In the related art, the health state evaluation and maintenance of the unmanned vehicle mainly rely on the running parameters or historical data of the unmanned vehicle itself, such as engine working time, driving mileage, vibration frequency, etc., and are judged by establishing a fixed life model or threshold.

[0033] However, these traditional methods have significant shortcomings: they completely ignore the special and variable environmental factors in the open operation scene, especially the nonlinear accelerated wear and tear caused by adverse weather conditions such as rain and snow, and wet road surface after watering. For example, after rain and snow or watering, the road surface is wet and slippery, and the adhesion coefficient decreases, resulting in a sharp increase in the frequency and intensity of the brake of the mine truck, frequent slipping of the driving system, and increased load of the steering system, thereby causing the wear rate of the key brake device in the brake device to far exceed the model prediction under ideal working conditions. The life model or threshold determination in the related art cannot perceive and quantify this additional accelerated wear and tear caused by environmental factors, resulting in a serious deviation of the health state evaluation result from the real state of the device, and thus the predictive maintenance strategy for the health state fails (either sudden failure or excessive maintenance), increasing the operating cost and safety risk.

[0034] To this end, the embodiments of the present application provide a vehicle health state determination method, comprising: acquiring running information, road surface wetness information and current health information of a target vehicle, wherein the target vehicle includes a vehicle performing operation in an open place, the current health information represents the health state of a vehicle component of the target vehicle, and the running information is collected when the target vehicle performs operation; determining a wear increment parameter matched with the road surface wetness information; correcting the reference wear information determined based on the running information by using the wear increment parameter, and determining the health state of the vehicle component according to the difference between the corrected reference wear information and the current health information.

[0035] Therefore, in addition to considering the operation information and the current health information of the target vehicle, the embodiment of the present application also considers the road surface wetness information representing the environmental factors, determines the loss increment parameter matched with the road surface wetness information, and corrects the reference loss information determined based on the operation information by using the loss increment parameter, so as to adapt the equipment loss law under different wetness working conditions in real time, so that the corrected reference loss information is more suitable for the actual working state, and the problem that the traditional fixed life model and threshold cannot cope with real-time working condition fluctuations is solved. Then, the difference between the current health information representing the real-time state of the vehicle components and the corrected reference loss information is used to determine the health state, so as to improve the dynamicity and accuracy of the health state evaluation, reduce the safety problems such as false alarm, false alarm and sudden failure, and then reduce the vehicle maintenance cost based on the health state.

[0036] Figure 1 An exemplary system architecture to which the vehicle health state determination method and device according to the embodiment of the present application can be applied is shown. It should be noted that, Figure 1 The shown is only an example of a system architecture to which the embodiment of the present application can be applied, to help those skilled in the art understand the technical content of the present application, but does not mean that the embodiment of the present application cannot be used in other devices, systems, environments or scenarios.

[0037] As Figure 1 The system architecture 100 according to the embodiment can include a vehicle 101, a network 102 and a server 103, as shown. The network 102 is a medium for providing a communication link between the vehicle 101 and the server 103. The network 102 can include various connection types, such as wired and / or wireless communication links, etc.

[0038] The user can use the vehicle 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the vehicle 101, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only as an example).

[0039] The vehicle 101 can be a vehicle capable of performing work in an open place, for example, the vehicle 101 can be a watering vehicle, a snow melting vehicle, a soil and stone excavating vehicle, a soil and stone transporting vehicle, etc. The above vehicles can be unmanned vehicles, etc. The embodiment of the present application does not limit the specific type of the vehicle 101, as long as the vehicle capable of performing work in an open place.

[0040] The server 103 can be a server that provides various services, such as a background management server that provides support for a website browsed by a user using the vehicle 101 (as an example). The background management server can perform analysis and the like on received user requests and the like, and feed back the processing results (such as a webpage, information, or data, or the like, obtained or generated in accordance with the user request) to the terminal device.

[0041] It should be noted that the vehicle health state determination method provided by the embodiments of the present application can generally be executed by the server 103. Accordingly, the vehicle health state determination apparatus provided by the embodiments of the present application can generally be arranged in the server 103. The vehicle health state determination method provided by the embodiments of the present application can also be executed by a server or a server cluster different from the server 103 and capable of communicating with the vehicle 101 and / or the server 103. Accordingly, the vehicle health state determination apparatus provided by the embodiments of the present application can also be arranged in a server or a server cluster different from the server 103 and capable of communicating with the vehicle 101 and / or the server 103. Alternatively, the vehicle health state determination method provided by the embodiments of the present application can also be executed by the vehicle 101, or by another vehicle different from the vehicle 101. Accordingly, the vehicle health state determination apparatus provided by the embodiments of the present application can also be arranged in the vehicle 101, or in another vehicle different from the vehicle 101.

[0042] It should be understood that Figure 1 The number of vehicles, networks, and servers in the above description is merely illustrative. Depending on the implementation needs, there can be any number of terminal devices, networks, and servers.

[0043] Figure 2 A flowchart of a vehicle health state determination method according to an embodiment of the present application is shown. As shown in Figure 2 The vehicle health state determination method includes operations S210-S230.

[0044] In operation S210, running information, road surface wetness information, and current health information of a target vehicle are acquired.

[0045] In operation S220, a wear increment parameter matching the road surface wetness information is determined.

[0046] In operation S230, the reference wear information determined based on the running information is corrected using the wear increment parameter, and the health state of the vehicle component is determined based on the difference between the corrected reference wear information and the current health information.

[0047] The target vehicle includes a vehicle performing a job at an open site. The target vehicle refers to a vehicle to be evaluated for a health state, such as a watering vehicle, a snow-melting vehicle, a soil and stone excavating vehicle, a soil and stone transporting vehicle, and the like to be evaluated for a health state. It can be understood that the target vehicle performs a job to accelerate the aging / loss of vehicle components, and the same job performed by different operation information results in different degrees of aging / loss.

[0048] The operation information is collected when the target vehicle performs a job. In order to accurately determine the health state according to the real-time job of the target vehicle, the reference loss information is determined based on the operation information collected when the target vehicle performs a job. For example, the operation information can be: engine working time, mileage, vibration frequency, braking information, and the like. The job performed by the target vehicle can be watering, snow-melting agent spraying, soil and stone excavation, soil and stone transportation, and the like.

[0049] The road surface wetness information refers to information representing the degree of road surface wetness, for example, it can be climate information and / or job information that affects the degree of road surface wetness, for example, it can be climate information such as rain and snow that affects the degree of road surface wetness, which can include weather type, rainfall / snow level, rainfall / snow amount, temperature, and the like; it can also be job information such as watering and snow-melting agent spraying that affects the degree of road surface wetness, which can include spraying amount, spraying direction, and the like.

[0050] In one specific embodiment, the target vehicle can obtain the road surface wetness information by communicating with the monitoring device in real time. For example, it can communicate with the meteorological station deployed in the mine to obtain climate information in real time, and communicate with the monitoring sensor or the vehicle-mounted Internet of Things terminal (used to manage and store monitoring sensor data) to obtain job information in real time. Similarly, for the above-mentioned operation information and current health information, the target vehicle can also obtain it by communicating with the monitoring sensor or the vehicle-mounted Internet of Things terminal, or communicating with the server that stores the above-mentioned information.

[0051] The loss increment parameter refers to the additional loss caused to the vehicle components when driving on the road surface corresponding to the road surface wetness information. Different degrees of road surface wetness cause different additional losses to the vehicle components, and thus, a plurality of road surface wetness information representing a plurality of degrees of road surface wetness matches a plurality of loss increment parameters. For example, the additional loss caused to the vehicle components is different when driving on dry road surface and wet road surface, and the additional loss caused to the vehicle components is different when driving on road surface with different degrees of wetness.

[0052] In one embodiment, the matching relationship between the loss increment parameter and the road surface wetness information can be determined in advance, so that the loss increment information matched with the current degree of road surface wetness can be directly determined when the target vehicle performs the current job.

[0053] As stated above, the running information can determine the baseline loss information, the loss increment parameter is an increment loss brought by the additional road wetness information, and thus the loss increment parameter and the baseline loss information can be fused by mathematical operation to obtain the corrected baseline loss information. Then, the health status (e.g., the health status updated after the current operation) is determined by the difference between the current health information and the corrected baseline loss information.

[0054] The current health information represents the health status of the vehicle component of the target vehicle, which can be the same as or different from the health status obtained after the current operation. The vehicle component for which the health status needs to be determined can be a component affected by whether the road is wet or not, such as a braking device.

[0055] For example, the health status is: slight loss, severe loss, no loss, to be repaired, to be replaced, etc. Alternatively, the health status can also be in the form of a numerical value, which indicates the corresponding state by a specific numerical value.

[0056] In addition to considering the running information and the current health information of the target vehicle, the embodiment of the present application also considers the road wetness information representing the environmental factor, determines the loss increment parameter matched with the road wetness information, and corrects the baseline loss information determined based on the running information by using the loss increment parameter, so as to adapt to the device loss law under different wetness working conditions in real time, so that the corrected baseline loss information is more suitable for the actual working state, and solves the problem that the traditional fixed life model and threshold cannot cope with real-time working condition fluctuations. Then, the health status is determined by the difference between the current health information representing the real-time state of the vehicle component and the corrected baseline loss information, which can improve the dynamicity and accuracy of health status evaluation, reduce safety problems such as false negatives, false positives, and sudden failures, and thus reduce the vehicle maintenance cost based on the health status.

[0057] According to the embodiment of the present application, the loss increment parameter includes a first sub-parameter corresponding to the road state; determining the loss increment parameter matched with the road wetness information includes: determining road state information matched with the road wetness information; and determining the first sub-parameter according to the relative difference between the road state information and baseline road state information, wherein the baseline road state information includes the road state of the open place under the baseline road wetness information.

[0058] In this embodiment, the loss increment parameter can be the first sub-parameter, or the first sub-parameter and its coefficient, etc., and the coefficient can be determined in advance.

[0059] The road surface state information is used to represent the road surface state when the target vehicle performs the work. For example, the road surface state information can include dry, wet, water accumulation, snow cover, and ice. In some embodiments, the road surface state information can be a road surface adhesion coefficient indicating the above-mentioned road surface states, which indicates the corresponding road surface state (such as dry, wet, etc. as mentioned above) by quantifying the friction adhesion between the road surface and the vehicle tire.

[0060] In one embodiment, the road surface wetness information includes climate information, and the road surface state information under various climate influences can be determined based on expert experience to obtain a matching relationship therebetween, so that the road surface state information corresponding to the road surface wetness information obtained by performing the work is determined based on the matching relationship.

[0061] For example, the road surface wetness information includes weather type and rainfall / snow level. If the weather type is rain and the rainfall / snow level is low, the road surface state information is wet or the corresponding road surface adhesion coefficient. Further, if the rainfall / snow level is medium or high, the road surface state information is water accumulation or the corresponding road surface adhesion coefficient. If the weather type is snow and the rainfall / snow level is low, the road surface state information is wet or the corresponding road surface adhesion coefficient. Further, if the rainfall / snow level is medium or high, the road surface state information is snow cover or the corresponding road surface adhesion coefficient. Alternatively, if the rainfall / snow level is medium or high and the temperature is lower than 0°, the road surface state information can be determined as ice or the corresponding road surface adhesion coefficient. If the weather type is sunny, the road surface state information is dry or the corresponding road surface adhesion coefficient.

[0062] In another embodiment, the road surface wetness information includes work information, and the road surface state under various work information influences can be determined based on expert experience to obtain a matching relationship therebetween, so that the road surface state information matched with the road surface wetness information obtained by performing the work is determined based on the matching relationship.

[0063] For example, the road surface wetness information includes water spraying amount. If the spraying amount is greater than a certain threshold, the road surface state information is water accumulation or the corresponding road surface adhesion coefficient. Otherwise, if the spraying amount is less than a certain threshold, the road surface state information is wet or the corresponding road surface adhesion coefficient. If the water spraying amount is zero, the road surface state information is dry or the corresponding road surface adhesion coefficient. Alternatively, the road surface wetness information includes snow-melting agent spraying amount. If the spraying amount is greater than a certain threshold, the road surface state information is wet / ice or the corresponding road surface adhesion coefficient. Otherwise, if the spraying amount is less than a certain threshold, the road surface state information is snow cover or the corresponding road surface adhesion coefficient.

[0064] In another embodiment, the road surface wetness information can include both the work information and the weather information. For example, if the weather type is sunny, and the amount of water sprayed is greater than a certain threshold, the road surface state information is water accumulation or the corresponding road surface adhesion coefficient. If the weather type is sunny, and no work is performed, the road surface state information is dry or the corresponding road surface adhesion coefficient.

[0065] The reference road surface state information includes the road surface state of the open site under the reference road surface wetness information, that is, the reference road surface state information can be the road surface state that causes the least additional loss to the target vehicle, such as dry or the corresponding road surface adhesion coefficient. For example, the reference road surface wetness information can be sunny weather type, and / or no work is performed.

[0066] Considering that it is difficult to accurately quantify the characteristics of different road surface wetness levels based on road surface state information alone, the relative difference between the road surface state information and the reference road surface state information can be determined as a first sub-parameter. For example, the first sub-parameter can be the difference, ratio, etc. between the road surface state information and the reference road surface state information.

[0067] For example, the first sub-parameter can be determined with reference to the following formula (1):

[0068] (1).

[0069] wherein, and respectively represent the reference road surface state information (such as the road surface adhesion coefficient of dry) and the current road surface state information (such as the road surface adhesion coefficient of the current road surface state), represents the first sub-parameter, which can also be referred to as a theoretical wear amplification factor.

[0070] In this embodiment, different road surface wetness levels of the same road surface state can be embodied by the specific numerical value of the road surface adhesion coefficient, so as to further quantify different road surface wetness levels on the basis of quantifying the road surface state.

[0071] For example, when the road surface state is "snow covered", the corresponding road surface adhesion coefficient is 0.25 (which can be determined based on the real-time road surface wetness level under the current road surface state according to historical data), and the reference road surface state information is the road surface adhesion coefficient 0.8 under the dry state, the first sub-parameter K theoretical = 0.8 / 0.25 = 3.2. Or, if the road surface state is "snow covered" on a certain day, and the wetness level is greater than the current one, the corresponding road surface adhesion coefficient can be 0.20.

[0072] In addition, in addition to accurately quantifying the characteristics of different road surface wetness levels, considering that there are various types of road surfaces in open sites (such as gravel roads, soil roads, and temporary paved roads), and that the reference road surface state information of various types of road surfaces naturally differs, for example, the inherent adhesion ability of a dry gravel road is different from that of a dry asphalt road. Therefore, the road surface state that causes the least additional loss to the target vehicle on a specific type of road surface can be taken as the reference road surface state information, and the characteristics of different road surface wetness levels can be further accurately quantified. For example, in a mine operation scenario, the reference road surface state information can be the road surface adhesion coefficient of the dry state of the compacted soil road (for example, 0.8 as described above).

[0073] In the embodiment of the present application, the first sub-parameter corresponding to the road surface state is determined as the loss increment parameter, which can accurately correct the reference loss information from the dimension of the additional nonlinear loss caused by the road surface state, so as to improve the accuracy of the subsequent determined health state information. In addition, in this embodiment, the first sub-parameter is determined by the relative difference between the current road surface state information and the reference road surface state information, which can accurately reflect the influence degree of the current working condition on the road adhesion ability, and further determine the influence degree of the road adhesion ability on the subsequent reference loss information, thereby improving the dynamicity and accuracy of the health state evaluation.

[0074] According to the embodiment of the present application, the loss increment parameter includes a second sub-parameter corresponding to the braking performance of the target vehicle; determining the loss increment parameter matching the road surface wetness information includes: if the road surface wetness information satisfies a predetermined condition, determining the reference braking information of the target vehicle when running in the running state indicated by the reference road surface wetness information and the running information; and determining the second sub-parameter according to the deviation degree between the braking information in the running information and the reference braking information.

[0075] It can be understood that the road surface wetness has a greater additional loss to the vehicle parts related to the braking equipment in the target vehicle, and therefore, the loss increment parameter can be the second sub-parameter, or the second sub-parameter and its coefficient, etc., and the coefficient can be determined in advance.

[0076] In this embodiment, in the case of dry road surface and / or slightly wet road surface, the loss to the vehicle parts related to the braking equipment is normal loss or negligible slight additional loss. In order to balance the accuracy and computing power, the calculation process of the second sub-parameter can be triggered when the road surface wetness information satisfies the predetermined condition.

[0077] For example, the predetermined condition can include at least one of the following: the climate type in the climate information (if the road surface wetness information includes the climate information) is a specific climate type (such as rain and / or snow), and / or the rainfall / snow level is greater than a threshold; the spraying amount in the operation information (if the road surface wetness information includes the operation information) satisfies the operation amount requirement.

[0078] In practical applications, the running information of the vehicle will affect the braking performance. For example, different road types, different road slopes, and different load states have different effects on the braking performance. In order to accurately quantify the additional loss caused by the current vehicle, the reference braking information required when the vehicle runs on various road wetness information and various running information can be determined in advance to obtain a reference for quantitatively determining the second sub-parameter.

[0079] Preferably, the running information at least includes at least one of the following: road type, road slope, load state, and braking information. The road type, the road slope, and the load state are respectively used to indicate the road type, the road slope, and the load amount of the target vehicle performing the current operation. The braking information refers to information related to the braking operation.

[0080] For example, the test vehicle (the target vehicle or a vehicle of the same type as the target vehicle) can be controlled to run in advance in the running state indicated by the reference road wetness information and the running information, and the braking information in various situations can be obtained. When the health state of the target vehicle is evaluated, the reference braking information matching the current running state and the reference road wetness information is selected. For example, the vehicle can be controlled to run in advance under the conditions of the above-mentioned reference road wetness information, and the braking information of different road types, uphill and downhill, and various road slopes, and various load states (full load / heavy load / empty load) is obtained.

[0081] In some embodiments, the difference between the braking information and the reference braking information can be determined as the above-mentioned deviation degree, or the ratio of the difference between the above-mentioned braking information and the reference braking information to the reference braking information can also be used as the deviation degree. Then, the deviation degree can be used as the second sub-parameter.

[0082] In this embodiment, the second sub-parameter corresponding to the braking performance is determined as the loss increment parameter, which can accurately correct the reference loss information from the dimension of the braking performance (causing additional nonlinear loss) to improve the accuracy of the subsequently determined health state information. In addition, in this embodiment, the reference braking information and the reference braking information determined by the second sub-parameter are completely consistent with the current working condition of the vehicle, which can accurately reflect the influence of the current working condition on the braking performance. Not only can it adapt to the variable road and running scenes in mines, but also can improve the dynamicity and accuracy of the health state evaluation.

[0083] According to one specific embodiment of the present application, the braking information includes the number of braking times and the braking performance parameter; and the second sub-parameter is determined according to the deviation degree between the braking information in the running information and the reference braking information, which includes: determining the second sub-parameter according to the first deviation degree between the number of braking times and the reference number of braking times, and the second deviation degree between the braking performance parameter and the reference braking performance parameter.

[0084] The braking times and the braking performance parameters can be average values of the braking times and the braking performance parameters of the target vehicle for a predetermined section / length of road. The braking performance parameters can be control amounts required for the target vehicle to perform braking operations and / or acting amounts acting on vehicle components in the braking device.

[0085] For example, the difference between the braking information and the reference braking information and the ratio of the reference braking information can be taken as the deviation degree. The first deviation degree and the second deviation degree are obtained in the case of the braking information being the braking times and the braking performance parameters. The second sub-parameter is obtained by summing the first deviation degree and the second deviation degree.

[0086] Preferably, the first deviation degree and the second deviation degree can also be weighted and summed to obtain the second sub-parameter. The weight of each of the first deviation degree and the second deviation degree is determined based on the historical operation information of the target vehicle. For example, the historical operation information can be analyzed by means of statistics, deep learning, big data analysis to determine the incremental influence of the braking times and the braking performance parameters on the additional loss, so as to obtain the weight of each of the first deviation degree and the second deviation degree.

[0087] For example, the second sub-parameter can be determined according to the following formula (2):

[0088] (2).

[0089] Wherein, is the second sub-parameter, which can also be referred to as a correction factor. and are the reference braking times and the reference braking performance parameters in the reference braking information, respectively, and are the braking times and the braking performance parameters, respectively, , , , are the first deviation degree, the second deviation degree and the corresponding weights, respectively.

[0090] In one specific embodiment, and are the average braking times and the average braking pressures per kilometer (or per hundred kilometers), respectively, and are the average braking times and the average braking pressures per kilometer (or per hundred kilometers) in the current work process, respectively.

[0091] In the embodiments of the present application, by taking the braking times and the braking performance parameters of the braking information from two dimensions, the additional nonlinear loss caused by the braking frequency and the braking intensity can be accurately corrected to improve the accuracy of the subsequently determined health state information.

[0092] According to another specific embodiment of the present application, the loss increment parameter comprises a first sub-parameter and a second sub-parameter, and determining the loss increment parameter matching the road surface wetness information comprises: fusing the first sub-parameter and the second sub-parameter to obtain the loss increment parameter.

[0093] For example, the first sub-parameter and the second sub-parameter can be summed or weighted summed to obtain the loss increment parameter. Alternatively, the product of the first sub-parameter and the second sub-parameter can also be taken as the loss increment parameter.

[0094] Preferably, the influence of the first sub-parameter on the loss increment parameter is greater than the influence of the second sub-parameter on the loss increment parameter.

[0095] For example, when the first sub-parameter and the second sub-parameter are weighted summed, the weight of the first sub-parameter is greater than the weight of the second sub-parameter, so that the influence of the first sub-parameter on the loss increment parameter is greater than the influence of the second sub-parameter on the loss increment parameter.

[0096] Alternatively, the first sub-parameter is taken as a coefficient to amplify the sum of the second sub-parameter and a reference value, so that the influence of the first sub-parameter on the loss increment parameter is greater than the influence of the second sub-parameter on the loss increment parameter.

[0097] In one example, the loss increment parameter may be determined according to the following formula (3):

[0098] (3).

[0099] wherein, "1" is a reference value. The first sub-parameter corresponding to the road surface state is usually a value greater than 1, which is used to amplify the loss increment parameter by the influence of the second sub-parameter, so as to highlight the more sensitive additional loss caused by the road surface state to the vehicle components.

[0100] If the target vehicle is currently running with the reference road surface wetness information and the running information, the loss increment parameter is a predetermined value 1, that is =1. For example, if the determined according to the current actual road surface wetness information and the running information is 3.5, the wear rate of the current braking device is 3.5 times of the predetermined value .

[0101] In the embodiments of the present application, the hybrid model architecture combining the first sub-parameter determined by the theoretical model of the road surface state and the second sub-parameter determined by the correction model deviating from the current real-time running information can realize accurate correction and physically interpretable quantification of the loss information, and further realize accurate measurement of the health state.

[0102] Figure 3 A flow chart of a method for correcting reference loss information according to a loss increment parameter and determining a health state according to an embodiment of the application is shown. As shown in Figure 3 , the method comprises operations S331-S332.

[0103] In operation S331, the reference loss information of a single braking operation is corrected by using the loss increment parameter to obtain corrected reference loss information of the single braking operation.

[0104] In operation S332, the health state of the braking device is determined according to the difference between the corrected reference loss information of the single braking operation and the current health information.

[0105] The vehicle component comprises a braking device. The braking device can be a device directly cooperating with a wheel / axle to generate braking force, such as a brake pad, a brake chamber, a brake push rod, etc., or a device for providing stable braking pressure, such as an air compressor, a brake pump, etc.

[0106] It can be understood that each time a braking operation is performed, the braking device will be worn, i.e., the health state will be reduced based on the current health information. The wear caused by a single braking operation is related to the road wetness information and the running information, and therefore, the reference loss information of a single braking operation (wear when running according to the running information) can be corrected by using the loss increment parameter determined above, and the current health information is subtracted by the corrected reference loss information of the single braking operation to obtain the health state of the braking device, which can also be understood as the remaining health state.

[0107] For example, the health state of the braking device can be determined according to formula (4).

[0108] (4).

[0109] wherein, represents the reference loss information of a single braking operation, is the loss increment parameter determined above, represents the health state of the braking device, represents the current health information.

[0110] Alternatively, the braking information further comprises a braking frequency, and the health state can also be determined according to the difference between the current health information and the corrected reference loss information after the cumulative braking frequency, such as , and N represents the number of braking operations performed by the target vehicle after the current health state is determined, i.e., the braking frequency.

[0111] It can be understood that the reference loss information is determined based on expert experience or historical operation data without considering the road wet information. In the embodiment of the present application, the reference loss information matched can be directly obtained from the expert database of the server according to the operation information.

[0112] In this embodiment, the loss increment coefficient related to the weather such as rain and snow is introduced dynamically to correct the reference loss information, so that the current health information and the corrected reference loss information can be used to obtain the instantaneous loss of the vehicle component device in the harsh working condition, and the accuracy of the health state evaluation is improved.

[0113] Figure 4 The scene diagram for determining the health state of the embodiment of the present application is shown. As shown in Figure 4 The target vehicle 401 can pass through three areas such as the first area 402, the second area 403 and the third area 404 when working in an open place. Taking the earth and stone transportation operation in the mine operation scene as an example, the target vehicle 401 passes through the first area 402, the second area 403 and the third area 404 in sequence before going to the earth and stone area, and the load state can be empty. In the process of going from the earth and stone area to the loading and unloading area, the target vehicle 401 passes through the third area 404, the second area 403 and the first area 402 in sequence, and the load state can be heavy.

[0114] The first area 402, the second area 403 and the third area 404 belong to different road types respectively. In the snowy weather, the road states of the three areas are ice, snow cover and wet respectively.

[0115] In the case of brake operation in the above three areas, the first sub-parameter of each area can be determined based on the road wet information; the corresponding reference braking information is obtained according to the load state, the operation information actually running in the above three areas is determined, and then the second sub-parameter is determined. Then, the loss increment parameters of the corresponding areas are obtained by fusing the first sub-parameters and the second sub-parameters of the three areas respectively.

[0116] In combination with the load state and the road surface state, six different loss increment parameters, such as K1-K6, can be determined when the target vehicle 401 sequentially passes through the first area 402, the second area 403, the third area 404 (the first time the above areas are passed through is empty load), the third area 404, the second area 403, and the first area 402 (the second time the above areas are passed through is heavy load) in the entire process of "going to the earthwork area - going from the earthwork area to the loading and unloading area". For the number of braking operations of the target vehicle 401 in each area, the K1-K6 can be used to correct the reference loss information of the single braking operation performed by each, and the health status of the vehicle components can be obtained according to the current health information and the corrected reference loss information. The health status can be the health status of the braking components after performing the entire earthwork operation.

[0117] According to an embodiment of the present application, the reference loss information for a single braking operation includes the difference between the hardware loss information before and after the braking device performs a single braking operation when the target vehicle runs in the running state indicated by the running information; and / or the reference loss information includes the heat loss information caused by the braking device performing a single braking operation when the target vehicle runs in the running state indicated by the running information.

[0118] In some embodiments, the braking device performs a braking operation to produce physical hardware loss information. For example, taking the brake pad as an example, after performing a braking operation, the thickness of the brake pad will be worn, and the hardware loss information can be the thickness of the brake pad. The thickness loss of the brake pad can be measured by a laser thickness gauge, a profilometer, or the like.

[0119] In other embodiments, the braking device can convert the kinetic energy or potential energy of the vehicle into heat energy loss through friction, and the heat loss information can be the heat loss. In some embodiments, a theoretical correlation between the heat loss information and the wear of the braking device can be established through an energy dissipation model, so as to determine the loss of the braking device caused by a single braking operation through the heat loss information. The heat loss information can be measured by an infrared thermometer, a thermocouple, or the like sensor arranged on the braking device.

[0120] In an embodiment of the present application, the flexible selection of the single dimension or the two-dimensional combination of the reference loss information acquisition mode can adapt to the sensing monitoring capability of different open-air operation scenes and the operation and maintenance demand of different types of target vehicles, and enhance the adaptability and practicality of the health status evaluation.

[0121] According to an embodiment of the present application, the method further comprises: in the case that the road wetness information is road wetness information at a future time point after the current time point, correcting the reference loss information determined based on the estimated operation information by using the loss increment parameter, and determining the health state of the vehicle component according to the difference between the corrected reference loss information and the current health information, wherein the estimated operation information is determined according to the operation to be performed by the target vehicle at the future time point.

[0122] In an actual mine operation scene, the operation performed by the target vehicle can be determined in advance, and the road wetness information can also be determined in advance, such as being determined based on a weather forecast. Thus, the predictive evaluation of the health state of the target vehicle at a future time point can be realized by using the road wetness information at the future time point after the current time point and the estimated operation information. The determination manner of the health state is similar to the real-time health state evaluation described above, and thus will not be described herein again.

[0123] For example, the future time point can be a time point after 4 hours, the road wetness information (such as weather information) after 4 hours can be obtained from a weather station deployed in the mine at the current time point, and the operation to be performed after 4 hours and the estimated operation information required for performing the operation, such as the estimated load, the estimated road type, the estimated road slope, etc., can be determined according to the scheduling operation of the target vehicle. Then, the health state of the target vehicle after performing the operation can be predicted according to the road wetness information and the estimated operation information.

[0124] In this embodiment, by predicting the health state in advance, the sudden reduction of the service life of the vehicle component caused by climate mutation can be predicted, sudden failure during operation can be effectively avoided, non-planned downtime can be reduced, excessive maintenance can be prevented, and the operating cost can be reduced.

[0125] According to an embodiment of the present application, the method further comprises: in the case that the health state satisfies a warning condition, generating warning information for the target vehicle.

[0126] The warning condition may, for example, be that the health state is severe loss, to be maintained, to be replaced, etc., or, for the health state in the form of a numerical value, such as the H rest The warning condition may, for example, be that the health state is severe loss, to be maintained, to be replaced, etc., or, for the health state in the form of a numerical value, such as the H

[0127] In one embodiment, the warning can be performed in real time according to the relationship between the health state determined according to the current real-time operation condition and the warning condition.

[0128] In another more preferred embodiment, in the case that the road wetness information is road wetness information at a future time point and the health state satisfies a warning condition, the warning information is generated to maintain the target vehicle before performing the operation to be performed based on the warning information.

[0129] For example, still taking the case that the future time can be a certain time after 4h, if it is predicted that the health state of the target vehicle after performing the work meets the early warning condition, the target vehicle can be maintained in advance before performing the work, so as to realize the prior maintenance.

[0130] In this embodiment, the health state determination method described above can provide an open site with a quantitative relationship model of “wet road (climate) - wear - life”, so that preventive resource allocation (such as spare parts and personnel) based on weather forecasts is possible, and the intelligent level of overall operation and maintenance management is improved.

[0131] In addition, the health state after a single braking operation is determined by using the running information or the estimated running information, which can be fed back to the automatic driving control system of the target vehicle, so as to prompt the control system to automatically adopt a smoother and more conservative control strategy under the condition of wet road (climate), thereby reducing wear from the source and improving work safety, and forming a pre-active health management closed loop of “evaluation - early warning - control”.

[0132] Figure 5 The structure schematic diagram of the vehicle health state determination device of the embodiment of the present application is shown. As shown in the figure, Figure 5 The vehicle health state determination device 500 includes: an acquisition module 510, configured to acquire running information, wet road information and current health information of a target vehicle, wherein the target vehicle includes a vehicle performing work in an open site, the current health information represents the health state of a vehicle component of the target vehicle, and the running information is collected when the target vehicle performs the work. A first determination module 520 is configured to determine a wear increment parameter matched with the wet road information. A second determination module 530 is configured to correct reference wear information determined based on the running information by using the wear increment parameter, and determine the health state of the vehicle component according to the difference between the corrected reference wear information and the current health information.

[0133] It should be noted that the data processing system part in the embodiment of the present application corresponds to the data processing method part in the embodiment of the present application, and the description of the data processing system part is specifically referred to the data processing method part, which will not be repeated here.

[0134] Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present application, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present application can be split into a plurality of modules to be implemented. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present application can be implemented at least in part as a hardware circuit, for example, a field-programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on board, a system on package, an application-specific integrated circuit (ASIC), or any other reasonable manner of hardware or firmware by integrating or packaging circuits, or in any one of software, hardware, and firmware, or in a proper combination of any one or more of them. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the present application can be implemented at least in part as computer program modules, which can perform corresponding functions when the computer program modules are run.

[0135] For example, any one or more of the modules 510, the first determining module 520, and the second determining module 530 can be combined in one module / unit / sub-unit to be implemented, or any one of them can be split into a plurality of modules / units / sub-units. Alternatively, at least part of the functions of one or more of the modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units, and implemented in one module / unit / sub-unit. According to embodiments of the present application, at least one of the modules 510, the first determining module 520, and the second determining module 530 can be implemented at least in part as a hardware circuit, for example, a field-programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on board, a system on package, an application-specific integrated circuit (ASIC), or any other reasonable manner of hardware or firmware by integrating or packaging circuits, or in any one of software, hardware, and firmware, or in a proper combination of any one or more of them. Alternatively, at least one of the modules 510, the first determining module 520, and the second determining module 530 can be implemented at least in part as computer program modules, which can perform corresponding functions when the computer program modules are run.

[0136] An aspect of the present application provides an unmanned vehicle, comprising: a processor configured to perform the vehicle health state determination method. The unmanned vehicle can be the target vehicle in the vehicle health state determination method, such as Figure 1 the vehicle 101 in FIG. 1.

[0137] Figure 6A block diagram of an unmanned vehicle suitable for implementing the above-described method according to an embodiment of the present application is shown. Figure 6 The shown unmanned vehicle is merely an example and should not impose any limitation on the function and scope of use of embodiments of the present application, in which other devices other than the processor can be regarded as devices for implementing data input, processing and output.

[0138] As Figure 6 shown, the unmanned vehicle 600 according to an embodiment of the present application includes a processor 601 that can perform various appropriate actions and processes according to a program stored in a ROM (Read Only Memory) 602 or a program loaded from a storage section 608 into a RAM (Random Access Memory) 603. The processor 601 can include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor, and / or a related chipset, and / or a special-purpose microprocessor (e.g., an application specific integrated circuit (ASIC)), and so on. The processor 601 can also include an on-board memory for cache use. The processor 601 can include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present application.

[0139] In the RAM 603, various programs and data required for the operation of the unmanned vehicle 600 are stored. The processor 601, the ROM 602 and the RAM 603 are connected to each other through a bus 604. The processor 601 performs various operations of the method flow according to an embodiment of the present application by executing the programs in the ROM 602 and / or the RAM 603. It is to be noted that the programs can also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 can also perform various operations of the method flow according to an embodiment of the present application by executing the programs stored in the one or more memories.

[0140] According to an embodiment of the present application, the unmanned vehicle 600 can further include an input / output (I / O) interface 605 that is also connected to the bus 604. The unmanned vehicle 600 can further include one or more of the following components connected to the input / output (I / O) interface 605: an input part 606 including a keyboard, a mouse, etc.; an output part 607 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part 608 including a hard disk, etc.; and a communication part 609 including a network interface card such as a LAN card, a modem, etc. The communication part 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as necessary. A removable recording medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 610 as necessary, so that a computer program read therefrom is installed into the storage part 608 as necessary.

[0141] According to an embodiment of the present application, the method flow according to the embodiment of the present application can be implemented as a computer software program. For example, the embodiment of the present application includes a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program codes for executing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network by the communication part 609, and / or installed from the removable recording medium 611. When the computer program is executed by the processor 601, the above-described functions defined in the system implementing the embodiment of the present application are performed. According to an embodiment of the present application, the system, device, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0142] The present application also provides a computer readable storage medium, which can be included in the device / apparatus / system described in the above embodiments, or exist separately without being assembled into the device / apparatus / system. The above computer readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiment of the present application.

[0143] According to an embodiment of the present application, the computer readable storage medium can be a non-transitory computer readable storage medium. For example, it can include, but is not limited to, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in connection with an instruction execution system, apparatus, or device.

[0144] For example, according to an embodiment of the present application, the computer readable storage medium can include one or more memories of ROM 602 and / or RAM 603 and / or other than ROM 602 and RAM 603 described above.

[0145] An embodiment of the present application also includes a computer program product, which includes a computer program containing program codes for executing the method provided by the embodiment of the present application, and when the computer program product is run on the unmanned vehicle, the program codes are used to make the unmanned vehicle implement the above-mentioned method provided by the embodiment of the present application.

[0146] When the computer program is executed by the processor 601, the above-mentioned functions defined in the system / apparatus of the embodiment of the present application are executed. According to an embodiment of the present application, the system, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0147] In one embodiment, the computer program can rely on tangible storage media such as optical storage media, magnetic storage media, etc. In another embodiment, the computer program can also be transmitted, distributed, downloaded and installed in the form of signals on network media, and be downloaded and installed through the communication part 609, and / or installed from the detachable medium 611. The program codes contained in the computer program can be transmitted by any appropriate network media, including but not limited to wireless, wired, etc., or any suitable combination of the foregoing.

[0148] According to embodiments of the present application, program code for implementing the computer programs provided by embodiments of the present application can be written in any combination of one or more programming languages, and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. The programming language includes, but is not limited to, such languages as Java, C++, python, "C" language, or the like. The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the remote computing device, or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider.

[0149] The computer program instructions can also be loaded onto a computer or other programmable information processing apparatus to cause a series of operations to be performed on the computer or other programmable information processing apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable information processing apparatus implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0150] The above-described embodiments of the application have been described in order to allow a clear and consistent understanding of the application. Subsequently, the application can be implemented in various ways and embodiments of the application can be configured in various ways. The application is not limited to the embodiments described above and many alternatives, modifications and variations can be made thereto without departing from the scope of the application as set forth in the claims.

Claims

1. A vehicle health state determination method, characterized by, The method comprises: obtaining operation information, road surface wetness information and current health information of a target vehicle, wherein the target vehicle comprises a vehicle performing a task in an open site, the current health information represents a health state of a vehicle component of the target vehicle, and the operation information is collected when the target vehicle performs the task; determining a wear increment parameter matched with the road surface wetness information; and correcting reference wear information determined based on the operation information by using the wear increment parameter, and determining the health state of the vehicle component according to a difference between the corrected reference wear information and the current health information.

2. The method of claim 1, wherein, The wear increment parameter comprises a first sub-parameter corresponding to a road surface state. The determination of the wear increment parameter matched with the road surface wetness information comprises: determining road surface state information matched with the road surface wetness information; determining the first sub-parameter according to a relative difference between the road surface state information and reference road surface state information, wherein the reference road surface state information comprises a road surface state of the open site under reference road surface wetness information.

3. The method of claim 1, wherein, The wear increment parameter comprises a second sub-parameter corresponding to a braking performance of the target vehicle. The determination of the wear increment parameter matched with the road surface wetness information comprises: if the road surface wetness information satisfies a predetermined condition, determining reference braking information of the target vehicle when the target vehicle runs in a running state indicated by the reference road surface wetness information and the operation information; determining the second sub-parameter according to a deviation degree between braking information in the operation information and the reference braking information.

4. The method of claim 3, wherein, The braking information comprises braking times and a braking performance parameter; and the determination of the second sub-parameter according to the deviation degree between the braking information in the operation information and the reference braking information comprises: determining the second sub-parameter according to a first deviation degree between the braking times and reference braking times and a second deviation degree between the braking performance parameter and a reference braking performance parameter; wherein the second sub-parameter is obtained by weighted summation of the first deviation degree and the second deviation degree, and the weights of the first deviation degree and the second deviation degree are determined based on historical operation information of the target vehicle.

5. The method of claim 1, wherein, The wear increment parameter comprises a first sub-parameter corresponding to a road surface state and a second sub-parameter corresponding to a braking performance of the target vehicle; and the determination of the wear increment parameter matched with the road surface wetness information comprises: fusing the first sub-parameter and the second sub-parameter to obtain the wear increment parameter, wherein an influence of the first sub-parameter on the wear increment parameter is greater than an influence of the second sub-parameter on the wear increment parameter.

6. The method according to any one of claims 1 to 5, characterized in that, The vehicle component comprises a braking device; and the correction of the reference wear information based on the operation information by using the wear increment parameter, and the determination of the health state of the vehicle component according to a difference between the corrected reference wear information and the current health information, comprises: correcting the reference wear information of a single braking operation by using the wear increment parameter to obtain corrected reference wear information for the single braking operation; and determine the health state of the braking device according to a difference between the reference loss information for a single braking operation and the current health information.

7. The method of claim 6, wherein, The reference loss information for a single braking operation includes: a difference between hardware loss information before and after the braking device performs a single braking operation when the target vehicle is running in a running state indicated by the running information; and / or The reference loss information includes heat loss information caused by the braking device performing a single braking operation when the target vehicle is running in a running state indicated by the running information.

8. The method of claim 1, wherein, The method further includes: In a case where the road surface wetness information is road surface wetness information at a future time point after the current time point, correcting reference loss information determined based on estimated running information by using the loss increment parameter, and determining the health state of the vehicle component according to a difference between the corrected reference loss information and the current health information, wherein the estimated running information is determined according to a job to be performed by the target vehicle at the future time point.

9. The method according to claim 1 or 8, characterized in that, The method further includes: In a case where the health state meets a warning condition, generating warning information for the target vehicle; and / or In a case where the road surface wetness information is road surface wetness information at a future time point, and the health state meets a warning condition, generating the warning information, so as to maintain the target vehicle before performing the job to be performed based on the warning information.

10. An unmanned vehicle, characterized in that comprise: a processor configured to execute the method according to any one of claims 1 to 9.

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