Equipment residual life processing method and device, electronic equipment and vehicle

Abstract

The invention provides a residual life processing method and device for equipment, electronic equipment and a vehicle, and the method comprises the steps: obtaining a first residual life value of to-be-detected equipment at the previous time and first data of the current vehicle when determining that the vehicle is in an offline mode at present; processing the first data and the first residual life value by using a first calculation model in the vehicle to obtain a second residual life value; if it is determined that the vehicle recovers to the online mode, obtaining operation parameters of a vehicle engine and an operation parameter library of the to-be-detected equipment; processing the operation parameters of the vehicle engine and the operation parameter library of the to-be-detected equipment by using a second calculation model of the cloud to obtain a third residual life value; and performing correction based on the second residual life value and the third residual life value to obtain a target residual life value of the to-be-detected equipment. According to the invention, through the first calculation model in the vehicle and the second calculation model in the cloud, the accuracy and stability of service life calculation can be ensured no matter which signal environment the vehicle runs.

Description

Technical Field

[0001] The present invention relates to the field of vehicle processing technology, and in particular to a method and device for processing the remaining life of equipment, an electronic device and a vehicle. Background Art

[0002] Currently, the remaining life of equipment in vehicles is calculated by online cloud computing to reduce the workload of in-vehicle computing in the future.

[0003] When the engine is running in areas with poor signals, such as coal mines and deserts, the cloud cannot receive data and send back calculation results in time due to poor signals, resulting in interruptions or delayed and inaccurate display of the remaining life calculation results. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a method, device, electronic device and vehicle for processing the remaining life of an equipment, so as to solve the problem of interruption or delayed inaccuracy in the remaining life calculation result display in the prior art.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] A first aspect of an embodiment of the present invention shows a method for processing the remaining life of a device, the method comprising:

[0007] When it is determined that the vehicle is currently in the offline mode, obtaining a first remaining life value of the previously detected device and first data of the current vehicle;

[0008] Processing the first data and the first remaining life value using a first calculation model in the vehicle to obtain a second remaining life value, wherein the first calculation model is pre-constructed;

[0009] If it is determined that the vehicle is restored to the online mode, the operating parameters of the vehicle engine and the operating parameter library of the device to be detected are obtained;

[0010] Processing the operating parameters of the vehicle engine and the operating parameter library of the device to be detected using a second computing model in the cloud to obtain a third remaining life value, wherein the second computing model is pre-built;

[0011] Correction is performed based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, and the target remaining life value is displayed through the vehicle.

[0012] Optionally, determine that the vehicle is currently in offline mode, including:

[0013] Determine whether a message exists in the bus and whether the duration of the message exceeds a preset threshold;

[0014] If not received or exceeded, it is determined that the vehicle is currently in offline mode;

[0015] If a corresponding message is received and the message continues to exceed a preset value, it is determined that the vehicle is currently in online mode.

[0016] Optionally, using a first calculation model in the vehicle to process the first data and the first remaining life value to obtain a second remaining life value includes:

[0017] Determining a preset remaining life value corresponding to the first data using a first calculation model in the vehicle;

[0018] The difference between the first remaining life value and the preset remaining life value is calculated based on the first calculation model to obtain a second remaining life value.

[0019] Optionally, the process of pre-building the first calculation model includes:

[0020] Constructing a correspondence between different first data and preset remaining life values;

[0021] A first calculation model is constructed based on the correspondence between the first data and a preset remaining life value.

[0022] Optionally, the process of pre-building the second calculation model includes:

[0023] Obtain the historical operating parameter library of the equipment to be tested and the historical operating data of the engine, and use them as a sample set;

[0024] Training is performed based on the sample set to obtain a second computing model.

[0025] Optionally, the operating parameters of the vehicle engine and the operating parameter library of the device to be detected are processed using the second computing model in the cloud to obtain a third remaining life value, including:

[0026] Inputting the operating parameters of the vehicle engine and the operating parameter library of the device to be detected into a second computing model in the cloud;

[0027] Based on the second calculation model in the cloud, the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected are input into the cloud for processing, and a corresponding third remaining life value is output.

[0028] Optionally, performing correction based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected includes:

[0029] Determine the current life correction factor;

[0030] The third remaining life value is corrected using the second remaining life value and the current life correction coefficient to obtain a target remaining life value of the device to be detected.

[0031] A second aspect of an embodiment of the present invention shows a device for processing the remaining life of a device, the device comprising:

[0032] A first acquisition unit, configured to acquire, when determining that the vehicle is currently in an offline mode, a first remaining life value of a previously detected device and first data of the current vehicle;

[0033] a first processing model, for processing the first data and the first remaining life value using a first calculation model in the vehicle to obtain a second remaining life value;

[0034] A second acquisition unit, for acquiring the operating parameters of the vehicle engine and the operating parameter library of the device to be detected if it is determined that the vehicle is restored to the online mode;

[0035] A second processing unit is used to process the operating parameters of the vehicle engine and the operating parameter library of the device to be detected by using a second computing model in the cloud to obtain a third remaining life value;

[0036] The correction unit is used to perform correction based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, and display the target remaining life value through the vehicle.

[0037] The third aspect of an embodiment of the present invention shows an electronic device, including: a processor and a memory, wherein the processor and the memory are connected via a communication bus; wherein the processor is used to call and execute a program stored in the memory; and the memory is used to store a program, wherein the program is used to implement the remaining life processing method of the device shown in the first aspect of the embodiment of the present invention.

[0038] The fourth aspect of the present invention shows a vehicle, comprising the electronic device shown in the third aspect of the embodiment of the present invention, wherein the electronic device is used to execute the remaining life processing method of the device shown in the first aspect of the embodiment of the present invention.

[0039] Based on the above-mentioned embodiment of the present invention, a method, device, electronic device and vehicle for processing the remaining life of a device are provided. The method includes: when it is determined that the vehicle is currently in offline mode, obtaining the first remaining life value of the device to be detected last time and the first data of the current vehicle; using the first calculation model in the vehicle to process the first data and the first remaining life value to obtain the second remaining life value; if it is determined that the vehicle is restored to online mode, obtaining the operating parameters of the vehicle engine and the operating parameter library of the device to be detected; using the second calculation model in the cloud to process the operating parameters of the vehicle engine and the operating parameter library of the device to be detected to obtain the third remaining life value; based on the obtained second remaining life value and the third remaining life value calculated last time in the online mode, the target remaining life value of the device to be detected is corrected, and the change from the target remaining life value to the third remaining life value is displayed by the vehicle. The present invention uses the first calculation model in the vehicle and the second calculation model in the cloud to ensure the continuity, stability and accuracy of the life display regardless of the signal environment in which the vehicle is running. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0041] Figure 1 A schematic diagram of a vehicle and a cloud server according to an embodiment of the present invention;

[0042] Figure 2 A schematic flow chart of a method for processing the remaining life of a device according to an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of determining an online mode and an offline mode according to an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of a flow chart of online mode calculation according to an embodiment of the present invention;

[0045] Figure 5 A schematic diagram of a process flow for processing the remaining life of a device shown in an embodiment of the present invention;

[0046] Figure 6 The present invention is a schematic structural diagram of a device for processing the remaining life of a device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0049] It should be noted that the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0050] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0051] See also Figure 1 , is a schematic diagram of a vehicle and a cloud server shown in an embodiment of the present invention.

[0052] The vehicle 10 includes a first controller 11 and a device to be detected 12 ; the cloud server 20 includes a cloud controller 21 .

[0053] The vehicle 10 is wirelessly connected to the cloud server 20 .

[0054] The first controller 11 and the device to be detected 12 are connected to the cloud controller 21 in the cloud server 20 via an in-vehicle terminal communication device (not shown in the figure).

[0055] The first controller 11 is connected to the devices to be detected 12 through the bus CAN, respectively, and the devices to be detected 12 are arranged to be connected to the engine.

[0056] The device to be detected 12 includes a filter, a pressure / differential pressure sensor is provided on the filter, or an engine equipped with oil.

[0057] The first controller 11 may be an intelligent three-filter controller.

[0058] Among them, the filter can be a liquid filter for filtering media such as fuel / engine oil / hydraulic oil, as well as an air filter, which can be used to filter impurities in the engine fuel system, lubrication system, hydraulic system and intake system to avoid abnormal wear of the engine.

[0059] The process of implementing device processing based on the architecture shown above includes:

[0060] When it is determined that the vehicle is currently in the offline mode, obtaining a first remaining life value of the device to be detected last time;

[0061] The first controller 11 obtains first data of the current vehicle, wherein the operating parameters include operating time or mileage; uses a first calculation model in the vehicle to process the operating parameters and the first remaining life value to obtain a second remaining life value, and temporarily stores it; if the vehicle is offline for a period of time, the second remaining life value will be continuously updated in real time according to the first calculation model; if it is determined that the vehicle is restored to the online mode, the operating parameters of the vehicle engine and the operating parameter library of the device to be detected are sent to the cloud controller 21;

[0062] The cloud controller 21 obtains the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected; uses the second calculation model on the cloud to process the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected to obtain a third remaining life value; based on the second remaining life value calculated last time in the online mode obtained, that is, the second remaining life value and the third remaining life value outputted by the first calculation model for the last time are corrected to obtain a target remaining life value of the equipment to be detected, and the target remaining life value is displayed through the vehicle.

[0063] The cloud refers to the cloud server 20 shown in the above architecture.

[0064] It should be noted that if the device to be detected 12 is a filter with a pressure / differential pressure sensor, the device processing of the present application is used to determine the remaining life of the filter; if the device to be detected 12 is an engine equipped with engine oil, the device processing of the present application can also be used to determine the remaining life of the engine oil.

[0065] In an embodiment of the present invention, when the first controller determines that the vehicle is currently in offline mode, it uses the first calculation model in the vehicle to process the operating parameters and the first remaining life value obtained by the previous processing to obtain a second remaining life value, and temporarily stores it; if the vehicle is in an offline state for a period of time, the second remaining life value will be continuously updated in real time according to the first calculation model; if it is determined that the vehicle is restored to online mode, the cloud controller uses the second calculation model in the cloud to process the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected to obtain a third remaining life value; based on the second remaining life value and the third remaining life value of the last time, corrections are made to obtain the target remaining life value of the equipment to be detected, and displayed through the vehicle. The present invention uses the first calculation model in the vehicle and the second calculation model in the cloud to ensure the continuity, stability and accuracy of the life display regardless of the signal environment in which the vehicle operates.

[0066] See also Figure 2 , is a flow chart of a filter detection method according to an embodiment of the present invention, the method comprising:

[0067] Step S201: Determine whether the vehicle is currently in offline mode. If so, execute step S202. If not, it means that the vehicle is in online mode, and steps S206 and S207 can be executed.

[0068] It should be noted that the specific process of implementing step S201 includes the following steps.

[0069] Step S11: Determine whether a message is received in the bus and whether the duration of the message exceeds a preset threshold. If so, execute step S12; if not, execute step S13.

[0070] Optionally, if the current vehicle network is in a normal state, the vehicle terminal driving companion or vehicle electrical component T-BOX in the vehicle continuously sends messages to the vehicle bus CAN according to a preset period; if the current vehicle network is in an abnormal state, the vehicle terminal driving companion or vehicle electrical component T-BOX in the vehicle cannot continuously send messages to the vehicle bus CAN according to the preset period;

[0071] The message here is a feedback message, and the content of the message may be FF FF FF FF FF, which is not limited in the embodiment of the present invention. That is, the content of the message may be set according to demand and is not limited to FF FF FF FF FF.

[0072] It should be noted that the preset cycle is set by technicians based on multiple experiments or experience, and can generally be set to 1S.

[0073] In the specific implementation of step S11, the first controller detects whether there is a message in the bus, and detects that the duration of the message existence is greater than a preset threshold. If greater, step S12 is executed; if less than or equal to, step S13 is executed.

[0074] It should be noted that the preset threshold is set in advance by the technician based on multiple experiments or experience, and can generally be set to 10s.

[0075] Step S12: Determine whether the current vehicle is in online mode and record it.

[0076] Optionally, it indicates that the current operating environment signal of the vehicle is good, and an online remaining life calculation prediction is performed. The front and rear pressures or pressure differences, flow, engine speed and other information of the actual filter are detected by sensors, and the on-board terminal transmits the information to the cloud. The remaining life is calculated by the second calculation model embedded in the cloud, that is, the process of steps S206 and S207 is executed, and the calculation results are transmitted to the vehicle in real time so that the vehicle can display them through its own instrument or the mobile phone APP connected to it.

[0077] Step S13: Determine whether the current vehicle is in offline mode, record it, and then execute step S202.

[0078] In the specific implementation of step S12 and step S13, after determining whether the current vehicle is in the online mode or the offline mode, the current mode of the vehicle is recorded.

[0079] Optionally, based on the process shown in the above steps S11 to S13, Figure 3 Provide explanation.

[0080] It should be noted that the determination of the vehicle mode is obtained in real time according to the number of times. For example, when it is determined that the current vehicle is in online mode, the vehicle network continues to be detected, and the changes in the vehicle mode are monitored in real time.

[0081] In the embodiment of the present invention, whether the vehicle is currently operating in offline mode or online mode is detected in real time by the duration of the message existence; the life of the filter and the engine oil is calculated by switching between the offline mode and the online mode.

[0082] Step S202: obtaining a first remaining life value of the previously detected device and obtaining first data of the current vehicle;

[0083] In the specific step S202, the first controller detects the mode of the vehicle in real time. If the vehicle is currently in offline mode, first, it is determined whether the vehicle was in online mode in the previous detection times. If it is determined that the vehicle was not in online mode in the previous detection times, the initial remaining life value is used as the first remaining life value of the device to be detected last time.

[0084] When the vehicle enters a mining area or a desert or other area with poor signal, the first controller determines that the vehicle is in an offline mode.

[0085] It should be noted that the device to be detected may be a filter or engine oil. When the device to be detected is a filter, the first remaining life value is the remaining life value of the filter; when the device to be detected is engine oil, the first remaining life value is the remaining life value of the engine oil.

[0086] It should be noted that the remaining life value of the engine oil is not the oil residue. If the vehicle is in a harsh working environment, even if there is still a lot of engine oil left, the carbon content has exceeded the limit. At this time, new engine oil needs to be replaced, that is, the remaining life value is equal to 0.

[0087] The initial remaining life value refers to the pre-set value, which is generally 100% or a specific kilometer / hour life limit.

[0088] Secondly, if it is determined that the vehicle was in online mode in all previous detection times, determine whether the vehicle model in the previous time was in online mode; if so, obtain the first remaining life value stored in the previous vehicle, that is, obtain the remaining life A of the last calculation result of the online calculation.

[0089] It should be noted that the first life is calculated based on the basic parameters of the device to be tested and the operating parameters of the engine.

[0090] If the vehicle mode last time was an offline mode, the first remaining life value stored in the last vehicle is obtained, that is, the remaining life A of the last calculation result of the offline calculation is obtained.

[0091] It should be noted that the specific process of obtaining the first data of the current vehicle is that the first controller obtains the first working time / working mileage of the current vehicle and uses it as the first data of the vehicle.

[0092] It should be noted that the first working time / working mileage refers to the time length / mileage span from the last time the engine determined that the vehicle was in the online mode to the current time the vehicle was in the offline mode.

[0093] Vehicle operation data may also include actual mileage, operating hours, etc.

[0094] Step S203: using a first calculation model in the vehicle to process the first data and the first remaining life value to obtain a second remaining life value, and temporarily store it;

[0095] Optionally, if the vehicle remains in an offline state, the second remaining life value will be continuously updated in real time according to the first calculation model.

[0096] Wherein, the first computing model is pre-built.

[0097] It should be noted that the process of pre-building the first calculation model includes:

[0098] Step S21: constructing a correspondence between different first data and preset remaining life values.

[0099] It should be noted that the larger the first data is, the larger the corresponding preset remaining life value is. In other words, the longer the vehicle is running, the shorter its corresponding life will be.

[0100] In the specific implementation of step S21, the life span change of the device to be detected is determined in advance using first data of different sizes, and a preset remaining life span value corresponding to the life span is set.

[0101] Step S22: constructing a first calculation model based on the correspondence between the first data and the preset remaining life value.

[0102] Optionally, a calculation method is provided in the first calculation model, and the calculation method calculates the difference between the input first remaining life value and a preset remaining life value.

[0103] In the specific implementation process of step S203, the first controller uses a first calculation model in the vehicle to determine a preset remaining life value corresponding to the first data; based on the first calculation model, the difference between the first remaining life value and the preset remaining life value is calculated to obtain a second remaining life value.

[0104] Specifically, a first calculation model in the vehicle is used to first determine a corresponding preset remaining life value based on the corresponding relationship between the first data and the preset remaining life value; then the difference between the first remaining life value and the preset remaining life value is calculated to obtain the offline remaining life, that is, the second remaining life value, and it is transmitted to the CAN bus in real time for storage.

[0105] In an embodiment of the present invention, the first computing model is embedded in the vehicle-mounted controller and runs the calculation in an offline state. The first computing model is a simplified mode to reduce the requirements on the computing power of the controller and reduce the production cost of the first controller.

[0106] Step S204: Determine whether the vehicle is restored to the online mode. If so, execute step S205. If not, determine that the current vehicle mode is still the offline mode, and continue to return to execute steps S202 to S203.

[0107] In the process of implementing step S204, when the vehicle network changes, the first controller can determine that the vehicle is in online mode and execute step S205. If there is still no change in the network, it means that the vehicle is still in offline mode, and continue to return to execute steps S202 to S203.

[0108] It should be noted that the specific implementation process of step S204 is the same as the specific implementation process of the above step S201, and they can refer to each other.

[0109] Step S205: Acquire the operating parameters of the vehicle engine and the operating parameter library of the device to be detected.

[0110] In the specific implementation of step S205, when the first controller determines that the vehicle is restored to the online mode and determines that the device to be detected is a filter, a series of parameters monitored by the vehicle terminal, specifically, the pressure sensor / pressure difference sensor is controlled to detect the front and rear pressure or pressure difference of the current filter, and the flow sensor is controlled to detect the flow of the current filter, engine speed, working time / mileage and other operating parameter libraries, and then the above operating parameter library is sent to the cloud controller through the vehicle terminal communication device;

[0111] When the first controller determines that the vehicle has returned to online mode and determines that the device to be detected is a device equipped with engine oil, the on-board terminal communication device sends the operating parameter library such as engine torque, engine speed, working time / working mileage, etc. in the engine CAN bus to the cloud controller.

[0112] Step S206: Use the second computing model in the cloud to process the operating parameters of the vehicle engine and the operating parameter library of the device to be tested to obtain a third remaining life value.

[0113] It should be noted that the second computing model is embedded in the cloud server and realizes life detection by running calculations online. The second computing model is pre-built.

[0114] It should be noted that there are multiple ways to implement the process of constructing the second computing model.

[0115] In a first implementation, the second calculation model is calculated based on historical operating data of the device to be tested and the engine;

[0116] The specific process of constructing the second calculation model includes:

[0117] Step S31: Acquire the historical operating parameter library of the equipment to be tested and the historical operating data of the engine, and use them as a sample set;

[0118] The sample set includes relevant operating parameters of the engine, a flow resistance curve database of filters at different flow rates in new and end-of-life states, a carbon content Map database of engine oil and other data as the sample set.

[0119] Step S32: Perform training based on the sample set to obtain a second calculation model.

[0120] In the process of implementing step S31 and step S32, the cloud controller in the cloud server is used to collect relevant operating parameters of the engine, a database of flow resistance curves of filters at different flow rates in a new state and at the end of their life, a database of carbon content Map of engine oil and other data; and use them as a sample set; then, use a preset algorithm to learn the sample set to train the preset algorithm and obtain an initial model constructed by the preset algorithm; based on the initial model, the remaining life value corresponding to the historical operating data in the sample set is predicted, and the remaining life value is compared with the life of the actual equipment to be tested in the same environment as the historical operating data. If they are consistent, the initial model is used as the second calculation model. If they are inconsistent, the preset algorithm in the initial model is continued to be learned based on the sample set until the prediction result output by the initial model is consistent with the actual life corresponding to the sample set.

[0121] Finally, the constructed second computing model is embedded in the cloud server.

[0122] Among them, the preset algorithm can be based on a neural network algorithm, a machine learning algorithm, etc.

[0123] Based on the second calculation model constructed above, the process of implementing step S207 specifically includes the following steps:

[0124] Step S41: Input the operating parameters of the vehicle engine and the operating parameter library of the device to be detected into the second computing model in the cloud.

[0125] Step S42: Based on the second calculation model on the cloud, the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected are input into the cloud for processing, and the corresponding third remaining life value is output.

[0126] In the process of implementing step S41 and step S42, the cloud controller inputs the operating parameters of the vehicle engine and the operating parameter library of the equipment to be tested into the second computing model on the cloud to call the second computing model in the cloud server to process them, output the corresponding third remaining life value, and pass it to the vehicle's CAN for storage.

[0127] It should be noted that no matter the device to be tested is a filter or a device containing engine oil, the above-mentioned steps S41 to S42 can be used to construct the corresponding second calculation model. If the input data is the detection information of the filter and the operating parameters of the vehicle engine, the output third remaining life value is the current remaining life value of the filter; if the input data is the operating parameters of the vehicle engine, the output third remaining life value is the remaining life value of the device containing engine oil.

[0128] Optionally, if the device to be detected is a filter, the second calculation model may be constructed in the following manner;

[0129] Based on the relevant operating parameters of the vehicle engine in history and the flow resistance curve database of the filter at different flow rates in the new state and at the end of its life, training is performed to obtain the corresponding second calculation model.

[0130] In a specific implementation, the K-means clustering algorithm K-means is used to divide the flow resistance curve database of the operating parameter filter of the vehicle engine at different flow rates in the new state and at the end of life into multiple samples.

[0131] It should be noted that each sample includes the operating data of the vehicle engine corresponding to the filter at a certain effective flow resistance value.

[0132] The effective flow resistance value refers to the flow resistance value adjusted based on the engine's operating data.

[0133] The flow resistance value refers to the pressure difference before and after the filter at a certain flow rate, also known as the pressure loss value.

[0134] Next, the multiple samples are divided into K groups, wherein each group contains at least one sample and each sample can only be divided into one group; the K groups are clustered to train the corresponding models, thereby obtaining a trained second computing model.

[0135] At this time, the trained second calculation model can determine the current effective flow resistance value of the filter based on the operating parameters of the engine and the operating parameter library of the filter.

[0136] The second calculation model is also provided with a linear regression fitting algorithm or an interpolation calculation method.

[0137] If a linear regression fitting algorithm is provided in the second calculation model, a linear regression fitting is performed on the effective flow resistance value obtained by the above calculation and the effective flow resistance value obtained by the previous calculation to form an effective flow resistance fitting curve; based on the change in the effective flow resistance fitting curve and the resistance curve of a new filter element under different flow rates, the remaining life, i.e., the third remaining life value, is determined.

[0138] If an interpolation calculation method is provided in the second calculation model, the interpolation calculation method is used to interpolate the calibrated flow resistance value of the new filter element and the current effective flow resistance value to obtain the remaining life percentage, that is, the third remaining life value.

[0139] Optionally, based on the process shown in the above steps S206 to S207, Figure 4 The architecture diagram shown is used for explanation.

[0140] If it is only processed in online mode, the cloud controller will send the third remaining life value back to the vehicle or mobile client so that the remaining life can be displayed through the vehicle instrument or mobile phone APP.

[0141] In an embodiment of the present invention, the first controller uploads the input data required for calculation to the cloud controller, or the cloud controller directly reads the data transmitted to the CAN bus by the vehicle terminal; and adjusts the second calculation model in the cloud server to process its data to obtain the corresponding third remaining life value, and transmits its third remaining life value to the vehicle or mobile phone APP.

[0142] Step S207: performing correction based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, and displaying the target remaining life value through the vehicle.

[0143] It should be noted that the specific implementation of step S207 includes the following steps:

[0144] Step S51: determining the current life correction coefficient;

[0145] In the specific implementation of step S51, the engine running time from when the vehicle enters the offline mode to when the vehicle resumes the online mode is recorded, and the corresponding life correction coefficient a is calculated according to the running time.

[0146] It should be noted that a=1 at the beginning and a=0 at the end. The life correction coefficient a is set according to demand. The purpose is to smoothly transition the last offline calculation result to the online calculation result. It can generally be set to 0.02 / h.

[0147] Step S52: using the second remaining life value and the current life correction coefficient to correct the third remaining life value to obtain a target remaining life value of the device to be detected.

[0148] In the specific implementation of step S52, first, the third remaining life value C is substituted into formula (1) by the second remaining life value B and the current life correction coefficient a to correct the third remaining life value C, so as to obtain the target remaining life value D of the device to be detected.

[0149] Formula (1):

[0150] D = B*a+(1-a)*C(1)

[0151] Next, the first controller controls the remaining life D displayed on the APP or the vehicle instrument to gradually approach the life C, with the ultimate goal of smoothing the life to C while online.

[0152] Optionally, based on the process shown in step S28 above, Figure 5 The architecture diagram shown is used for explanation.

[0153] When the cloud controller determines that the vehicle has returned to online mode, it obtains the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected, and at the same time obtains the second remaining life value of the vehicle. At this time, the calculation of step S207 can be performed directly on the cloud.

[0154] The cloud sends the calculated third remaining life value and target remaining life value to the vehicle, so that when the vehicle controller receives the third remaining life value and the target remaining life value, it controls the remaining life D displayed on the APP or vehicle instrument to gradually approach the life C. The ultimate goal is to smooth the life to C when online.

[0155] It should be noted that the applicant has found that since only online calculation is used, signal difference is prone to occur, resulting in interruption of online life calculation, and the life display results are inaccurate and have no reference value, affecting user satisfaction and actual maintenance operations; while only offline calculation requires high requirements for data storage and processing workload, which leads to high manufacturing cost of the controller, large size and reduced reliability.

[0156] In an embodiment of the present invention, when it is determined that the vehicle is currently in offline mode, the operating parameters and the first remaining life value obtained by the previous processing are processed using the first calculation model in the vehicle to obtain a second remaining life value, which is temporarily stored; if the vehicle is offline for a period of time, the second remaining life value will be continuously updated in real time according to the first calculation model; if it is determined that the vehicle is restored to online mode, the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected are processed using the second calculation model in the cloud to obtain a third remaining life value; based on the second remaining life value and the third remaining life value temporarily stored last time in the offline mode, corrections are made to obtain the target remaining life value of the equipment to be detected, and displayed through the vehicle. The present invention uses the first calculation model in the vehicle and the second calculation model in the cloud to ensure the continuity, stability and accuracy of the life display regardless of the signal environment in which the vehicle operates.

[0157] Based on the method shown in the above embodiment of the present invention, the embodiment of the present invention also shows a device processing device, such as Figure 6 As shown, the device comprises:

[0158] A first acquisition unit 601 is used to acquire a first remaining life value of a previously detected device and first data of the current vehicle when it is determined that the vehicle is currently in an offline mode;

[0159] A first processing model 602 is used to process the first data and the first remaining life value using a first calculation model in the vehicle to obtain a second remaining life value;

[0160] The second acquisition unit 603 is used to acquire the operating parameters of the vehicle engine and the operating parameter library of the device to be detected if it is determined that the vehicle is restored to the online mode;

[0161] The second processing unit 604 is used to process the operating parameters of the vehicle engine and the operating parameter library of the device to be detected by using the second computing model in the cloud to obtain a third remaining life value;

[0162] The correction unit 605 is used to perform correction based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, and display the target remaining life value through the vehicle.

[0163] It should be noted that the specific implementation process of each unit of the device processing apparatus shown in the above embodiment of the present invention is the same as the specific implementation process of the device processing method shown in the above embodiment, and they can refer to each other.

[0164] In an embodiment of the present invention, when it is determined that the vehicle is currently in offline mode, the operating parameters and the first remaining life value obtained by the previous processing are processed using the first calculation model in the vehicle to obtain a second remaining life value, which is temporarily stored; if the vehicle is offline for a period of time, the second remaining life value will be continuously updated in real time according to the first calculation model; if it is determined that the vehicle is restored to online mode, the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected are processed using the second calculation model in the cloud to obtain a third remaining life value; based on the second remaining life value and the third remaining life value temporarily stored last time in the offline mode, corrections are made to obtain the target remaining life value of the equipment to be detected, and displayed through the vehicle. The present invention uses the first calculation model in the vehicle and the second calculation model in the cloud to ensure the continuity, stability and accuracy of the life display regardless of the signal environment in which the vehicle operates.

[0165] Optionally, based on the device processing apparatus shown in the above embodiment of the present invention, the first acquisition unit 601 that determines that the vehicle is currently in an offline mode is specifically configured to:

[0166] Determine whether a message exists in the bus and whether the duration of the message exceeds a preset threshold;

[0167] If not received or exceeded, it is determined that the vehicle is currently in offline mode;

[0168] If a corresponding message is received and the message continues to exceed a preset value, it is determined that the vehicle is currently in online mode.

[0169] Optionally, based on the device processing apparatus shown in the above embodiment of the present invention, the first processing model 602 is specifically used for:

[0170] Determining a preset remaining life value corresponding to the first data using a first calculation model in the vehicle;

[0171] The difference between the first remaining life value and the preset remaining life value is calculated based on the first calculation model to obtain a second remaining life value.

[0172] Optionally, based on the device processing apparatus shown in the above embodiment of the present invention, the first processing model 602 is further used for:

[0173] Constructing a correspondence between different first data and preset remaining life values;

[0174] A first calculation model is constructed based on the correspondence between the first data and a preset remaining life value.

[0175] Optionally, based on the device processing apparatus shown in the above embodiment of the present invention, the second processing model 604 is further used for:

[0176] Obtain the historical operating parameter library of the equipment to be tested and the historical operating data of the engine, and use them as a sample set;

[0177] Training is performed based on the sample set to obtain a second computing model.

[0178] Optionally, based on the apparatus for processing the remaining life of a device shown in the above embodiment of the present invention, the second processing model 604 is specifically used for:

[0179] Inputting the operating parameters of the vehicle engine and the operating parameter library of the device to be detected into a second computing model in the cloud;

[0180] Based on the second calculation model in the cloud, the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected are input into the cloud for processing, and a corresponding third remaining life value is output.

[0181] Optionally, based on the device processing apparatus shown in the above embodiment of the present invention, the correction unit 605 is specifically configured to:

[0182] Determine the current life correction factor;

[0183] The third remaining life value is corrected using the second remaining life value and the current life correction coefficient to obtain a target remaining life value of the device to be detected.

[0184] An embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory is used to store program code and data for the remaining life processing of the device, and the processor is used to call the program instructions in the memory to execute the steps shown in the remaining life processing method of the device in the above embodiment.

[0185] An embodiment of the present invention provides a vehicle, the vehicle includes the electronic device provided by the above-mentioned embodiment of the present application, and the electronic device is used to execute the remaining life processing method of the device disclosed in the embodiment of the present application.

[0186] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0187] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0188] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for processing the remaining life of equipment, characterized in that: The method comprises: When it is determined that the vehicle is currently in the offline mode, obtaining a first remaining life value of the previously detected device and first data of the current vehicle, wherein the first data is a first working time or working mileage of the current vehicle; Processing the first data and the first remaining life value by using a first calculation model in the vehicle to obtain a second remaining life value, wherein the first calculation model is pre-constructed and is a model constructed by a correspondence between the first data and a preset remaining life value; If it is determined that the vehicle is restored to the online mode, the operating parameters of the vehicle engine and the operating parameter library of the device to be detected are obtained; Processing the operating parameters of the vehicle engine and the operating parameter library of the device to be detected using a second computing model in the cloud to obtain a third remaining life value, wherein the second computing model is pre-built; Correction is performed based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, and the target remaining life value is displayed through the vehicle.

2. The method according to claim 1, characterized in that Determine if the vehicle is currently in offline mode, including: Determine whether a message exists in the bus and whether the duration of the message exceeds a preset threshold; If not received or exceeded, it is determined that the vehicle is currently in offline mode; If a corresponding message is received and the message continues to exceed a preset value, it is determined that the vehicle is currently in online mode.

3. The method according to claim 1, characterized in that Processing the first data and the first remaining life value by using a first calculation model in the vehicle to obtain a second remaining life value includes: Determining a preset remaining life value corresponding to the first data using a first calculation model in the vehicle; The difference between the first remaining life value and the preset remaining life value is calculated based on the first calculation model to obtain a second remaining life value.

4. The method according to claim 1, characterized in that The process of pre-building the first calculation model includes: Constructing a correspondence between different first data and preset remaining life values; A first calculation model is constructed based on the correspondence between the first data and a preset remaining life value.

5. The method according to claim 1, characterized in that The process of pre-building the second calculation model includes: Obtain the historical operating parameter library of the equipment to be tested and the historical operating data of the engine, and use them as a sample set; Training is performed based on the sample set to obtain a second computing model.

6. The method according to claim 1, characterized in that The operating parameters of the vehicle engine and the operating parameter library of the device to be tested are processed using the second computing model in the cloud to obtain a third remaining life value, including: Inputting the operating parameters of the vehicle engine and the operating parameter library of the device to be detected into a second computing model in the cloud; Based on the second calculation model in the cloud, the operating parameters of the vehicle engine and the operating parameter library of the equipment to be detected are input into the cloud for processing, and a corresponding third remaining life value is output.

7. The method according to claim 1, characterized in that Correction is performed based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, including: Determine the current life correction factor; The third remaining life value is corrected using the second remaining life value and the current life correction coefficient to obtain a target remaining life value of the device to be detected.

8. A device for processing the remaining life of equipment, characterized in that: The device comprises: A first acquisition unit, configured to acquire, when determining that the vehicle is currently in an offline mode, a first remaining life value of a previously detected device and first data of the current vehicle, wherein the first data is a first working time or working mileage of the current vehicle; a first processing model, used to process the first data and the first remaining life value by using a first calculation model in the vehicle to obtain a second remaining life value, wherein the first calculation model is pre-constructed and is a model constructed by a correspondence between the first data and a preset remaining life value; A second acquisition unit, for acquiring the operating parameters of the vehicle engine and the operating parameter library of the device to be detected if it is determined that the vehicle is restored to the online mode; a second processing unit, configured to process the operating parameters of the vehicle engine and the operating parameter library of the device to be detected by using a second computing model in the cloud to obtain a third remaining life value, wherein the second computing model is pre-built; The correction unit is used to perform correction based on the second remaining life value and the third remaining life value to obtain a target remaining life value of the device to be detected, and display the target remaining life value through the vehicle.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the processor and the memory are connected via a communication bus; wherein the processor is used to call and execute a program stored in the memory; The memory is used to store a program, and the program is used to implement the remaining life processing method of the device as described in any one of claims 1-7.

10. A vehicle, characterized in that: The electronic device comprises the electronic device described in claim 9, and the electronic device is used to execute the remaining life processing method of the device described in any one of claims 1-7.

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