Fault early warning method and device, computer equipment and storage medium
By obtaining and updating vehicle parameters, using gate control and exponential function technology, the problem of difficult to accurately warn of potential vehicle failures in traditional methods is solved, and the accuracy and effectiveness of fault warnings are improved.
Patent Information
- Application Number
- CN202411623182.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-14
- Publication Date
- 2025-03-11
AI Technical Summary
Traditional methods are difficult to accurately warn of potential vehicle failures and lack foresight.
By obtaining the historical initial vehicle parameters of the target vehicle, determining the initial parameter weight based on input gate and output gate, updating the weight using an exponential function, and then updating the vehicle parameters to achieve fault warning.
It improves the accuracy and effectiveness of fault warning and can more accurately reflect the vehicle failure status of the target vehicle.
Smart Images
Figure CN119590437A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of artificial intelligence and automobile fault warning, and in particular to a fault warning method, device, computer equipment and storage medium. Background Art
[0002] With the continuous development of artificial intelligence and intelligent control technology, many cars (such as new energy vehicles) are equipped with advanced intelligent driving systems, in-vehicle Internet and application platforms, providing a more convenient driving experience and improving user interactivity. At the same time, vehicle safety has also attracted much attention, and how to accurately warn of potential vehicle failures has become a key issue that needs to be solved urgently.
[0003] The traditional method is to develop maintenance plans based on past failure cases and maintenance records, but this method can only target known problems and lacks foresight. It is also unable to accurately warn of some potential failures in vehicles. Summary of the invention
[0004] Based on this, it is necessary to provide a fault warning method, device, computer equipment and storage medium that can improve the accuracy of warning in response to the above technical problems.
[0005] In a first aspect, the present application provides a fault warning method, the method comprising:
[0006] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0007] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0008] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0009] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0010] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0011] In one of the embodiments, the initial vehicle parameters are updated according to the target parameter weights to determine the target vehicle parameters, including: updating the initial vehicle parameters according to the target parameter weights to obtain retained parameter data of the target vehicle in a historical time period; and determining the target vehicle parameters based on the retained parameter data and input gating.
[0012] In one of the embodiments, the initial vehicle parameters are updated according to the target parameter weights to obtain the retained parameter data of the target vehicle in the historical time period, including: updating the initial vehicle parameters according to the target parameter weights to obtain the initial retained parameters corresponding to the initial vehicle parameters; based on output gating, performing a nonlinear transformation on the initial retained parameters to obtain the retained parameter data of the target vehicle in the historical time period.
[0013] In one embodiment, target vehicle parameters are determined based on retained parameter data and input gating, including: performing residual connection and projection transformation on the retained parameter data to obtain target retained parameters; and determining target vehicle parameters based on the target retained parameters based on the input gating.
[0014] In one of the embodiments, a fault warning is provided to a target vehicle based on target vehicle parameters and initial vehicle parameters, including: determining a vehicle fault state corresponding to the target vehicle based on the target vehicle parameters and initial vehicle parameters; and providing a fault warning to the target vehicle based on the vehicle fault state.
[0015] In one embodiment, the battery parameters include battery voltage, battery temperature, terminal temperature, battery current and battery safety performance parameters.
[0016] In a second aspect, the present application also provides a fault warning device. The device comprises:
[0017] A data acquisition module, used to acquire the initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status and brake system status;
[0018] A first determination module, configured to determine initial parameter weights according to initial vehicle parameters based on input gating and output gating;
[0019] A second determination module is used to update the initial parameter weight according to the exponential function to determine the target parameter weight;
[0020] A third determination module is used to update the initial vehicle parameters according to the target parameter weights to determine the target vehicle parameters;
[0021] The fault warning module is used to provide fault warning to the target vehicle based on the target vehicle parameters and the initial vehicle parameters.
[0022] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:
[0023] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0024] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0025] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0026] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0027] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0028] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:
[0029] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0030] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0031] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0032] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0033] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0034] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:
[0035] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0036] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0037] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0038] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0039] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0040] The above-mentioned fault warning method, device, computer equipment and storage medium obtain the initial vehicle parameters of the target vehicle within the historical time period; based on input gating and output gating, determine the initial parameter weight according to the initial vehicle parameters; update the initial parameter weight according to the exponential function to determine the target parameter weight, thereby ensuring that the target parameter weight can accurately reflect the vehicle fault status of the target vehicle; update the initial vehicle parameters according to the target parameter weight to determine the target vehicle parameters, thereby ensuring that the target vehicle parameters contain both the data at the historical moment and the data target at the current moment, thereby more accurately reflecting the vehicle fault status of the target vehicle; perform fault warning on the target vehicle according to the target vehicle parameters and the initial vehicle parameters, thereby improving the accuracy and effectiveness of the fault warning. BRIEF DESCRIPTION OF THE DRAWINGS
[0041] Figure 1 A flowchart of a fault warning method provided in an embodiment of the present application;
[0042] Figure 2 A flowchart of the steps for determining target vehicle parameters provided in an embodiment of the present application;
[0043] Figure 3 A flowchart of the steps for implementing fault warning provided in an embodiment of the present application;
[0044] Figure 4 A flowchart of another fault warning method provided in an embodiment of the present application;
[0045] Figure 5 A structural block diagram of a fault warning device provided in an embodiment of the present application;
[0046] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION
[0047] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0048] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. In the description of the present application, the description of the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms is not necessarily for the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples without contradicting each other.
[0049] In one embodiment, Figure 1 A flowchart of a fault warning method provided in an embodiment of the present application. This embodiment uses the method applied to a terminal as an example. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be but is not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server can be implemented as an independent server or a server cluster composed of multiple servers. In this embodiment, the method includes the following steps:
[0050] In an exemplary embodiment, Figure 1 The fault warning method shown includes:
[0051] S101, obtaining initial vehicle parameters of a target vehicle in a historical time period.
[0052] Among them, the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status and braking system status.
[0053] It should be noted that the battery parameters may include one or more combinations of battery voltage, battery temperature, pole temperature, battery current, battery type (such as lithium-ion battery, nickel-metal hydride battery and fuel cell, etc.), battery remaining life and battery safety performance parameters; further, the battery safety performance parameters may include the thermal stability of the battery, the antioxidant capacity, the stability of the electrolyte, the puncture strength of the diaphragm, etc. The motor may include a drive motor; the motor state may include one or more combinations of motor power (such as instantaneous active power, reactive power rated power and peak power), speed (such as real-time speed, rated speed and maximum operating speed), torque (such as stall torque, peak torque and rated torque), differential input voltage, motor temperature, ambient temperature, motor output voltage and current, rated frequency, response speed, speed range, power density; the on-board energy storage device state may include one or more combinations of the total capacity of the energy storage device, charge, power, energy state, internal resistance, DC internal resistance change rate; the power converter state may include one or more combinations of; the high-voltage interlock state may include; the insulation state may include; the brake system state may include.
[0054] In one embodiment of the present application, the process of obtaining the initial vehicle parameters of the target vehicle within the historical time period may specifically include the following contents: at any historical moment, the target vehicle is monitored according to the vehicle monitoring platform of the target vehicle to obtain the vehicle parameters of the target vehicle at the historical moment; within a preset time period, the vehicle parameters of the target vehicle at each historical moment are combined to obtain the initial vehicle parameters of the target vehicle within the historical time period; further, with authorization, the initial vehicle parameters of the target vehicle within the historical time period are obtained from the background database of the vehicle monitoring platform.
[0055] Among them, the vehicle monitoring platform is used to collect the battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status and braking system status of the target vehicle.
[0056] For example, the preset duration is two moments. At moment t1, the vehicle parameters collected through the vehicle monitoring platform are: {battery parameter 1, motor state 1, on-board energy storage device state 1, power converter state 1, high-voltage interlock state 1, insulation state 1, brake system state 1}; at moment t2, the vehicle parameters collected through the vehicle monitoring platform are: {battery parameter 2, motor state 2, on-board energy storage device state 2, power converter state 2, high-voltage interlock state 2, insulation state 2, brake system state 2}. The initial vehicle parameters of the target vehicle in the historical time period are: {{battery parameter 1, motor state 1, on-board energy storage device state 1, power converter state 1, high-voltage interlock state 1, insulation state 1, brake system state 1}, {battery parameter 2, motor state 2, on-board energy storage device state 2, power converter state 2, high-voltage interlock state 2, insulation state 2, brake system state 2}}.
[0057] The time units may include microseconds, milliseconds, seconds, minutes, hours, days, months, etc.
[0058] S102, determining initial parameter weights based on input gating and output gating and initial vehicle parameters.
[0059] Among them, input gating is used to control the data retention amount of the initial vehicle parameters at that historical moment to the next historical moment, and has the function of data filtering and dynamically adjusting the data retention amount; output gating is used to determine the initial vehicle parameters to be retained to the next historical moment, and has the function of transmitting sequential data and feature selection, ensuring that the retained initial vehicle parameters can accurately reflect the vehicle fault status; initial parameter weights are used to indicate the degree of influence of the initial vehicle parameters on the vehicle fault status after the initial vehicle parameters have been subjected to input gating, output gating and forgetting gating.
[0060] It should be noted that the input gating is composed of input data, gating function and output data, wherein, for any historical moment, the input data of the input gating includes the initial vehicle parameters at the historical moment and the vehicle fault state at the next historical moment; the gating function of the input gating is composed of the weight matrix of the input gating, the recursive weight matrix of the input gating, the initial vehicle parameters at the historical moment and the vehicle fault state at the previous historical moment; the output data of the input gating includes the normalized and / or indexed initial parameter weights and the normalized and / or indexed initial vehicle parameters. The output gating is composed of output data, gating function and output data, wherein, for any historical moment, the input data of the output gating includes the initial vehicle parameters at the historical moment and the vehicle fault state at the next historical moment; the gating function of the output gating is composed of the weight matrix of the output gating, the recursive weight matrix of the output gating, the initial vehicle parameters at the historical moment and the vehicle fault state at the previous historical moment; the output data of the output gating includes the initial parameter weights after activation by an activation function (such as a sigmoid function) and the initial vehicle parameters after the activation function. It is further explained that, for any historical moment, forget gate is used to filter the data that should be removed from the retained initial vehicle parameters at that historical moment; forget gate is composed of output data, gating function and output data, and the input data of forget gate includes the initial vehicle parameters at that historical moment and the vehicle fault status at the next historical moment; the gating function of forget gate is composed of the weight matrix of forget gate, the recursive weight matrix of forget gate, the initial vehicle parameters at that historical moment and the vehicle fault status at the previous historical moment; the output data of forget gate includes the normalized and / or indexed initial parameter weights and the normalized and / or indexed initial vehicle parameters.
[0061] In one embodiment of the present application, the process of determining the initial parameter weights may specifically include the following: inputting the initial vehicle parameters into the input gate, filtering the data of the initial vehicle parameters through the input gate, and obtaining the first parameter weight; inputting the initial vehicle parameters into the output gate, performing feature selection on the initial vehicle parameters through the output gate, and obtaining the second parameter weight; inputting the initial vehicle parameters into the forget gate, removing the data of the initial vehicle parameters through the forget gate, and obtaining the third parameter weight; further, using the first parameter weight, the second parameter weight, and the third parameter weight as the initial parameter weight.
[0062] S103, updating the initial parameter weights according to the exponential function to determine the target parameter weights.
[0063] It should be noted that the target parameter weight is used to represent the initial parameter weight after indexation, which can realize dynamic adjustment of the target parameter weight at different times, so that the target parameter weight obtained at each time can more accurately reflect the vehicle fault status of the target vehicle, thereby improving the accuracy of fault warning.
[0064] Exemplarily, the initial parameter weights are used as input data of the natural exponential function, and the initial parameter weights are updated through function transformation, and the output data of the natural exponential function is used as the target parameter weights.
[0065] S104, updating the initial vehicle parameters according to the target parameter weights to determine the target vehicle parameters.
[0066] The target vehicle parameters are used to represent parameters that have a significant impact on the vehicle fault state of the target vehicle at the current moment.
[0067] It should be noted that since the initial vehicle parameters are used to represent the vehicle fault status of the target vehicle in the historical time period, they cannot accurately reflect the vehicle fault status of the target vehicle at the current moment and in the future. Therefore, it is necessary to update the initial vehicle parameters through the target parameter weights to determine the target vehicle parameters.
[0068] Exemplarily, the initial vehicle parameters can be updated according to the target parameter weights to obtain the retained parameter data of the target vehicle in the historical time period; further, the retained parameter data and the vehicle parameters at the current moment are input into the input gate, and the retained parameter data and the vehicle parameters at the current moment are filtered using the input gate to obtain the output data of the input gate, which is the target vehicle parameters.
[0069] S105, providing a fault warning to the target vehicle according to the target vehicle parameters and the initial vehicle parameters.
[0070] In one embodiment of the present application, the process of providing a fault warning for a target vehicle may specifically include the following: determining a vehicle fault state corresponding to the target vehicle based on target vehicle parameters and initial vehicle parameters; further, providing a fault warning for the target vehicle based on the vehicle fault state.
[0071] Among them, the vehicle failure status may include one or more combinations of engine failure, electrical system failure, fuel system failure, exhaust system failure, transmission system failure, steering system failure, braking system failure, tire failure, emission control system failure, cooling system, ignition system failure, and suspension system failure.
[0072] To further illustrate, the target vehicle parameters and the initial vehicle parameters can be fused to obtain fused vehicle parameters; the fused vehicle parameters are low-dimensionally mapped through a feature mapping function to obtain the probability value corresponding to each state in the fused vehicle parameters, and the state with the largest probability value is used as the vehicle fault state corresponding to the target vehicle.
[0073] Among them, the feature mapping function may include but is not limited to a fully connected network, a graph attention network, and a graph convolutional network.
[0074] It should be noted that, since different vehicle fault states correspond to different fault locations, when performing fault warning on the target vehicle, different fault warning methods may be set according to different vehicle fault states.
[0075] For example, if the vehicle fault status is an engine fault, specifically described as engine overheating, a warning can be given through the high temperature warning light on the vehicle dashboard. The high temperature warning light flashes, indicating that the target vehicle's engine temperature is too high and needs to be cooled to ensure the safe driving of the target vehicle.
[0076] The above fault warning method obtains the initial vehicle parameters of the target vehicle within the historical time period; based on the input gating and the output gating, the initial parameter weights are determined according to the initial vehicle parameters; the initial parameter weights are updated according to the exponential function to determine the target parameter weights, thereby ensuring that the target parameter weights can accurately reflect the vehicle fault status of the target vehicle; according to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters, thereby ensuring that the target vehicle parameters contain both the data at the historical moment and the data target at the current moment, thereby more accurately reflecting the vehicle fault status of the target vehicle; according to the target vehicle parameters and the initial vehicle parameters, a fault warning is performed on the target vehicle, thereby improving the accuracy and effectiveness of the fault warning.
[0077] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the determination process of the target vehicle parameters is optimized and improved to achieve the effect that the target vehicle parameters can more accurately reflect the vehicle fault state of the target vehicle and improve the accuracy of fault warning.
[0078] like Figure 2 The process of determining the target vehicle parameters shown includes the following steps:
[0079] S201, updating the initial vehicle parameters according to the target parameter weights to obtain the retained parameter data of the target vehicle in the historical time period.
[0080] Among them, the retained parameter data is used to represent the initial vehicle parameters retained from the previous moment to the current moment.
[0081] In one embodiment of the present application, the process of determining the retained parameter data may specifically include the following contents: updating the initial vehicle parameters according to the target parameter weights to obtain the initial retained parameters corresponding to the initial vehicle parameters; performing a nonlinear transformation on the initial retained parameters based on output gating to obtain the retained parameter data of the target vehicle in the historical time period.
[0082] It is further explained that the initial retention parameters are used as input data of the output gating, and feature selection is performed on the initial retention parameters through the output gating to obtain the initial retention parameters after feature selection; further, a sine transform is performed on the initial retention parameters after feature selection to obtain the retention parameter data of the target vehicle in the historical time period.
[0083] S202, determining target vehicle parameters according to the retained parameter data and input gating.
[0084] It should be noted that since the retained parameter data is used to reflect the initial vehicle parameters of the target vehicle at the previous moment, it cannot accurately reflect the initial vehicle parameters of the target vehicle at the current moment. Therefore, the initial vehicle parameters at the current moment can be feature filtered through input gating, and the initial vehicle parameters after feature filtering are combined with the retained parameter data to obtain the target vehicle parameters, ensuring that the target vehicle parameters contain both data from historical moments and data from the current moment, making the target vehicle parameters more valuable for reference and ensuring the accuracy of fault warning.
[0085] In one embodiment of the present application, the process of determining the target vehicle parameters may specifically include the following: performing residual connection and projection transformation on the retained parameter data to obtain the target retained parameters; based on input gating, determining the target vehicle parameters according to the target retained parameters.
[0086] To further illustrate, the target retained parameters are used as input data of the input gate, and the target retained parameters are filtered through the input gate to obtain the output data of the input gate, which is the target vehicle parameter.
[0087] The above fault warning method obtains the target vehicle parameters by inputting the gated and retained parameter data, thereby ensuring that the target vehicle parameters contain both the data at the historical moment and the data target at the current moment, so that the vehicle parameters can more accurately reflect the vehicle fault status of the target vehicle and improve the accuracy of the fault warning.
[0088] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the step of performing fault warning on the target vehicle is optimized and improved to achieve the effect of improving the accuracy and effectiveness of fault warning. Figure 3 The method shown comprises the following steps:
[0089] S301, determining a vehicle fault state corresponding to the target vehicle according to the target vehicle parameters and the initial vehicle parameters.
[0090] S302, providing a fault warning to the target vehicle according to the vehicle fault status.
[0091] It should be noted that the target vehicle parameters and the initial vehicle parameters can be fused to obtain fused vehicle parameters; the fused vehicle parameters are low-dimensionally mapped through the feature mapping function to obtain the probability value corresponding to each state in the fused vehicle parameters, and the state with the largest probability value is used as the vehicle fault state corresponding to the target vehicle.
[0092] Among them, the feature mapping function may include but is not limited to a fully connected network, a graph attention network, and a graph convolutional network.
[0093] For example, if the vehicle fault state is a brake system fault, specifically described as a brake fluid leakage, a warning can be given through the brake system warning light. The brake system warning light flashes, indicating that there is a brake fluid leakage in the target vehicle. The brake fluid level can be manually checked to ensure safe driving of the target vehicle.
[0094] For example, if the vehicle fault status is electrical system fault and steering system fault, specifically described as electrical line short circuit or open circuit and steering wheel shaking, for electrical system fault, an early warning can be issued through the vehicle real-time monitoring platform. After detecting the abnormality, the vehicle real-time monitoring platform can send text messages or intelligent voice to the owner to achieve timely and effective fault warning; for steering system fault, the working status of the steering valve can be checked to ensure the safe driving of the target vehicle.
[0095] The above fault warning method uses the target vehicle parameters and the initial vehicle parameters to accurately reflect the vehicle fault status of the target vehicle at the current moment and in the future, thereby improving the accuracy and effectiveness of the fault warning.
[0096] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the fault warning process is described in detail. Figure 4 The fault warning method shown includes:
[0097] S401, obtaining initial vehicle parameters of the target vehicle in a historical time period.
[0098] S402 , determining initial parameter weights based on input gating and output gating and initial vehicle parameters.
[0099] S403: Update the initial parameter weights according to the exponential function to determine the target parameter weights.
[0100] S404: Update the initial vehicle parameters according to the target parameter weights to obtain initial retained parameters corresponding to the initial vehicle parameters.
[0101] S405 , based on output gating, nonlinearly transform the initial retained parameters to obtain retained parameter data of the target vehicle in a historical time period.
[0102] S406, performing residual connection and projection transformation on the retained parameter data to obtain target retained parameters.
[0103] S407, based on the input gating, determine the target vehicle parameters according to the target retention parameters.
[0104] S408, determining a vehicle fault state corresponding to the target vehicle according to the target vehicle parameters and the initial vehicle parameters.
[0105] S409, providing a fault warning to the target vehicle according to the vehicle fault status.
[0106] The above fault warning method obtains the initial vehicle parameters of the target vehicle within the historical time period; based on the input gating and the output gating, the initial parameter weights are determined according to the initial vehicle parameters; the initial parameter weights are updated according to the exponential function to determine the target parameter weights, thereby ensuring that the target parameter weights can accurately reflect the vehicle fault status of the target vehicle; according to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters, thereby ensuring that the target vehicle parameters contain both the data at the historical moment and the data target at the current moment, thereby more accurately reflecting the vehicle fault status of the target vehicle; according to the target vehicle parameters and the initial vehicle parameters, a fault warning is performed on the target vehicle, thereby improving the accuracy and effectiveness of the fault warning.
[0107] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
[0108] Based on the same inventive concept, the embodiment of the present application also provides a fault warning device for implementing the fault warning method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more fault warning device embodiments provided below can refer to the limitations of the fault warning method above, and will not be repeated here.
[0109] In one embodiment, Figure 5 As shown, a fault warning device is provided, comprising: a data acquisition module 10, a first determination module 20, a second determination module 30, a third determination module 40 and a fault warning module 50, wherein:
[0110] The data acquisition module 10 is used to obtain the initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status and braking system status.
[0111] The first determination module 20 is used to determine the initial parameter weights based on the input gating and the output gating and according to the initial vehicle parameters.
[0112] The second determination module 30 is used to update the initial parameter weight according to the exponential function to determine the target parameter weight.
[0113] The third determination module 40 is used to update the initial vehicle parameters according to the target parameter weights to determine the target vehicle parameters.
[0114] The fault warning module 50 is used to provide fault warning to the target vehicle according to the target vehicle parameters and the initial vehicle parameters.
[0115] The above-mentioned fault warning device obtains the initial vehicle parameters of the target vehicle within the historical time period; based on the input gating and the output gating, according to the initial vehicle parameters, the initial parameter weights are determined; the initial parameter weights are updated according to the exponential function to determine the target parameter weights, thereby ensuring that the target parameter weights can accurately reflect the vehicle fault status of the target vehicle; according to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters, thereby ensuring that the target vehicle parameters contain both the data at the historical moment and the data target at the current moment, thereby more accurately reflecting the vehicle fault status of the target vehicle; according to the target vehicle parameters and the initial vehicle parameters, a fault warning is performed on the target vehicle, thereby improving the accuracy and effectiveness of the fault warning.
[0116] Each module in the above-mentioned fault warning device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.
[0117] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a fault warning method is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.
[0118] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0119] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:
[0120] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0121] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0122] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0123] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0124] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0125] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the target parameter weight, the initial vehicle parameters are updated to obtain the retained parameter data of the target vehicle in the historical time period; according to the retained parameter data and the input gating, the target vehicle parameters are determined.
[0126] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the target parameter weights, the initial vehicle parameters are updated to obtain the initial retention parameters corresponding to the initial vehicle parameters; based on the output gating, the initial retention parameters are nonlinearly transformed to obtain the retention parameter data of the target vehicle in the historical time period.
[0127] In one embodiment, when the processor executes the computer program, the following steps are also implemented: residual connection and projection transformation are performed on the retained parameter data to obtain target retained parameters; based on input gating, target vehicle parameters are determined according to the target retained parameters.
[0128] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining a vehicle fault state corresponding to the target vehicle according to the target vehicle parameters and the initial vehicle parameters; and providing a fault warning to the target vehicle according to the vehicle fault state.
[0129] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the battery parameters include battery voltage, battery temperature, electrode temperature, battery current and battery safety performance parameters.
[0130] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
[0131] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0132] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0133] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0134] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0135] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0136] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the target parameter weight, the initial vehicle parameters are updated to obtain the retained parameter data of the target vehicle in the historical time period; according to the retained parameter data and the input gating, the target vehicle parameters are determined.
[0137] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the target parameter weights, the initial vehicle parameters are updated to obtain the initial retention parameters corresponding to the initial vehicle parameters; based on the output gating, the initial retention parameters are nonlinearly transformed to obtain the retention parameter data of the target vehicle in the historical time period.
[0138] In one embodiment, when the processor executes the computer program, the following steps are also implemented: residual connection and projection transformation are performed on the retained parameter data to obtain target retained parameters; based on input gating, target vehicle parameters are determined according to the target retained parameters.
[0139] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining a vehicle fault state corresponding to the target vehicle according to the target vehicle parameters and the initial vehicle parameters; and providing a fault warning to the target vehicle according to the vehicle fault state.
[0140] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the battery parameters include battery voltage, battery temperature, electrode temperature, battery current and battery safety performance parameters.
[0141] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:
[0142] Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status;
[0143] Based on the input gating and the output gating, according to the initial vehicle parameters, initial parameter weights are determined;
[0144] The initial parameter weights are updated according to the exponential function to determine the target parameter weights;
[0145] According to the target parameter weights, the initial vehicle parameters are updated to determine the target vehicle parameters;
[0146] According to the target vehicle parameters and the initial vehicle parameters, a fault warning is issued to the target vehicle.
[0147] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the target parameter weight, the initial vehicle parameters are updated to obtain the retained parameter data of the target vehicle in the historical time period; according to the retained parameter data and the input gating, the target vehicle parameters are determined.
[0148] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the target parameter weights, the initial vehicle parameters are updated to obtain the initial retention parameters corresponding to the initial vehicle parameters; based on the output gating, the initial retention parameters are nonlinearly transformed to obtain the retention parameter data of the target vehicle in the historical time period.
[0149] In one embodiment, when the processor executes the computer program, the following steps are also implemented: residual connection and projection transformation are performed on the retained parameter data to obtain target retained parameters; based on input gating, target vehicle parameters are determined according to the target retained parameters.
[0150] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining a vehicle fault state corresponding to the target vehicle according to the target vehicle parameters and the initial vehicle parameters; and providing a fault warning to the target vehicle according to the vehicle fault state.
[0151] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the battery parameters include battery voltage, battery temperature, electrode temperature, battery current and battery safety performance parameters.
[0152] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.
[0153] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, data block or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The data blocks involved in the various embodiments provided in this application may include at least one of relational data blocks and non-relational data blocks. Non-relational data blocks may include distributed data blocks based on blockchain, etc., but are not limited to this. The processors involved in the various embodiments provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., but are not limited to this.
[0154] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0155] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A fault warning method, characterized in that: The method comprises: Obtaining initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status, and brake system status; Determining initial parameter weights based on the input gating and the output gating and according to the initial vehicle parameters; The initial parameter weight is updated according to the exponential function to determine the target parameter weight; According to the target parameter weights, the initial vehicle parameters are updated to determine target vehicle parameters; According to the target vehicle parameters and the initial vehicle parameters, a fault warning is performed on the target vehicle.
2. The method according to claim 1, characterized in that: The updating of the initial vehicle parameters according to the target parameter weights to determine the target vehicle parameters includes: According to the target parameter weight, the initial vehicle parameters are updated to obtain the retained parameter data of the target vehicle in the historical time period; Target vehicle parameters are determined based on the retained parameter data and the input gating.
3. The method according to claim 2, characterized in that The updating of the initial vehicle parameters according to the target parameter weights to obtain the retained parameter data of the target vehicle in the historical time period includes: According to the target parameter weights, the initial vehicle parameters are updated to obtain initial retained parameters corresponding to the initial vehicle parameters; Based on the output gating, the initial retained parameters are nonlinearly transformed to obtain the retained parameter data of the target vehicle in a historical time period.
4. The method according to claim 2, characterized in that: The step of determining target vehicle parameters according to the retained parameter data and the input gating includes: Performing residual connection and projection transformation on the retained parameter data to obtain target retained parameters; Based on the input gating, target vehicle parameters are determined according to the target retained parameters.
5. The method according to claim 1, characterized in that The step of providing a fault warning to the target vehicle according to the target vehicle parameters and the initial vehicle parameters includes: Determining a vehicle fault state corresponding to the target vehicle according to the target vehicle parameters and the initial vehicle parameters; According to the vehicle fault status, a fault warning is issued to the target vehicle.
6. The method according to claim 1, characterized in that The battery parameters include battery voltage, battery temperature, electrode temperature, battery current and battery safety performance parameters.
7. A fault warning device, characterized in that: The device comprises: A data acquisition module, used to acquire initial vehicle parameters of the target vehicle within a historical time period; wherein the initial vehicle parameters include battery parameters, motor status, on-board energy storage device status, power converter status, high-voltage interlock status, insulation status and brake system status; A first determination module, configured to determine an initial parameter weight according to the initial vehicle parameters based on the input gating and the output gating; A second determination module is used to update the initial parameter weight according to an exponential function to determine the target parameter weight; A third determination module, used to update the initial vehicle parameters according to the target parameter weights to determine target vehicle parameters; The fault warning module is used to provide fault warning to the target vehicle according to the target vehicle parameters and the initial vehicle parameters.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.