Vehicle power-on self-test method and device, electronic equipment and storage medium
By dynamically determining the self-test sequence during the vehicle starting process, the problem of low power-on self-test efficiency in the existing technology is solved, and a more efficient vehicle starting process is achieved.
Patent Information
- Application Number
- CN202411355792.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-27
- Publication Date
- 2025-01-14
Smart Images
Figure CN119305500A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle power-on self-test method, device, electronic device and storage medium. Background Art
[0002] Power-On Self Test (POST) is an important step to ensure that the hardware and software status of each system on the vehicle is correct when the vehicle is started, which is crucial to improving driving safety and driving experience. By testing each system on the vehicle, it can not only ensure that each system is in a usable state, but also through real-time fault detection, potential problems can be discovered at the beginning of the vehicle startup, and timely measures can be taken to repair or isolate them to prevent the spread of faults and affect the stability of the system, thereby improving driving safety and driving experience.
[0003] Traditional power-on self-test solutions often follow a preset, static test process, and the same self-test steps are performed regardless of the vehicle's environment or usage scenario. This may not only ignore key checks in specific situations, but also perform lengthy checks unnecessarily, affecting the vehicle's startup speed. Summary of the invention
[0004] In view of this, an embodiment of the present application provides a vehicle power-on self-test method, device, electronic device and storage medium to solve the problem in the prior art that, during the power-on and startup of the vehicle, each module can only perform self-test according to a pre-set detection process, resulting in low power-on self-test efficiency.
[0005] In a first aspect of an embodiment of the present application, a vehicle power-on self-test method is provided, the method comprising: during the vehicle startup process, determining the vehicle startup scenario; obtaining the target importance of each module to be self-tested in the vehicle, and determining the weight value of each module to be self-tested in the startup scenario according to the target importance of each module to be self-tested; obtaining at least two self-test sequences, each self-test sequence being used to indicate the sequence of controlling multiple modules to be self-tested to perform self-tests; calculating the detection cost of each self-test sequence based on the weight value of each module to be self-tested in the startup scenario, the detection cost being used to characterize the detection efficiency of the self-test sequence; determining a target self-test sequence according to the detection cost corresponding to each self-test sequence, and controlling each module to be self-tested to perform a power-on self-test based on the target self-test sequence.
[0006] According to a second aspect of an embodiment of the present application, a vehicle power-on self-test device is provided, the device comprising: an environment module, configured to determine a vehicle startup scenario during the vehicle startup process; a weight module, configured to obtain a target importance of each module to be self-tested in the vehicle, and determine a weight value of each module to be self-tested in the startup scenario according to the target importance of each module to be self-tested; a self-test module, configured to obtain at least two self-test sequences, each self-test sequence being used to indicate an order in which a plurality of modules to be self-tested are controlled to perform self-test; a detection cost of each self-test sequence is calculated based on the weight value of each module to be self-tested in the startup scenario, the detection cost being used to characterize the detection efficiency of the self-test sequence; a target self-test sequence is determined according to the detection cost corresponding to each self-test sequence, and each module to be self-tested is controlled to perform a power-on self-test based on the target self-test sequence.
[0007] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.
[0008] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.
[0009] Compared with the prior art, the embodiments of the present application have the following beneficial effects: the method in the embodiments of the present application determines the vehicle startup context during the vehicle startup process; obtains the target importance of each module to be self-checked in the vehicle, and determines the weight value of each module to be self-checked in the startup context according to the target importance of each module to be self-checked; obtains at least two self-checking sequences, each self-checking sequence is used to indicate the sequence of controlling multiple modules to be self-checked to perform self-checks; based on the weight value of each module to be self-checked in the startup context, calculates the detection cost of each self-checking sequence, and the detection cost is used to characterize the detection efficiency of the module to be self-checked; determines the target self-checking sequence according to the detection cost corresponding to each self-checking sequence, and controls each module to be self-checked based on the target self-checking sequence. Perform power-on self-test; wherein, the method dynamically determines the weight value of each module to be self-tested in the startup scenario according to the startup scenario and the importance of each module to be self-tested, and calculates the detection cost of each self-test sequence based on the weight value of each module to be self-tested in the startup scenario, thereby realizing dynamic calculation of the detection cost of each self-test sequence, and determining the target self-test sequence according to the detection to be tested, selecting a self-test sequence whose detection efficiency meets the requirements, reducing the time required for module self-test during the startup process, improving the startup efficiency of the vehicle, shortening the waiting time when the vehicle is started, and avoiding the problem in the related technology that during the power-on startup of the vehicle, each module can only perform self-test according to a pre-set detection process, resulting in low power-on self-test efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application, 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 some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0011] Figure 1 It is a flowchart of a vehicle power-on self-test method provided in an embodiment of the present application;
[0012] Figure 2 It is a flowchart of another vehicle power-on self-test method provided in an embodiment of the present application;
[0013] Figure 3 It is a flowchart of another vehicle power-on self-test method provided in an embodiment of the present application;
[0014] Figure 4 It is a flowchart of another vehicle power-on self-test method provided in an embodiment of the present application;
[0015] Figure 5 It is a flowchart of another vehicle power-on self-test method provided in an embodiment of the present application;
[0016] Figure 6 It is a flowchart of another optional vehicle power-on self-test method provided in an embodiment of the present application;
[0017] Figure 7 It is a flowchart of another optional vehicle power-on self-test method provided in an embodiment of the present application;
[0018] Figure 8 It is a flowchart of another optional vehicle power-on self-test method provided in an embodiment of the present application;
[0019] Fig. 9 It is a structural schematic diagram of a vehicle power-on self-test device provided in an embodiment of the present application;
[0020] Fig.10 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0021] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.
[0022] A vehicle power-on self-test method and device according to an embodiment of the present application will be described in detail below with reference to the accompanying drawings.
[0023] Figure 1 A vehicle power-on self-test method provided in an embodiment of the present application is as follows: Figure 1 As shown, the method includes:
[0024] S101, during the vehicle startup process, determining a vehicle startup scenario;
[0025] S102, obtaining the target importance of each module to be self-checked in the vehicle, and determining the weight value of each module to be self-checked in the startup scenario according to the target importance of each module to be self-checked;
[0026] S103, obtaining at least two self-checking sequences, each of which is used to indicate the sequence of controlling a plurality of modules to be self-checked to perform self-checking;
[0027] S104, calculating the detection cost of each self-checking sequence based on the weight value of each module to be self-checked in the startup scenario, where the detection cost is used to characterize the detection efficiency of the self-checking sequence;
[0028] S105 , determining a target self-test sequence according to the detection cost corresponding to each self-test sequence, and controlling each module to be self-tested to perform power-on self-test based on the target self-test sequence.
[0029] It can be understood that the vehicle power-on self-test method provided in this example is applied to vehicles, including vehicles with automatic driving or intelligent driving (including vehicles with passenger functions (such as cars, buses, large buses, minibuses, etc.), vehicles with cargo functions (such as ordinary trucks, vans, trailers, closed trucks, tank trucks, flatbed trucks, container trucks, dump trucks, trucks with special structures), special vehicles (such as logistics distribution vehicles, automatic guided transport vehicles AGV, patrol cars, cranes, cranes, excavators, bulldozers, forklifts, rollers, loaders, off-road engineering vehicles, armored engineering vehicles, sewage treatment vehicles, sanitation vehicles, vacuum trucks, floor washing vehicles, sprinkler trucks, sweeping robots, food delivery robots, shopping guide robots, lawn mowers, golf carts, etc.), vehicles with entertainment functions (such as entertainment vehicles, amusement park automatic driving devices, balance cars, etc.), rescue vehicles (such as fire trucks, ambulances, power repair vehicles, engineering rescue vehicles, etc.)), etc.
[0030] It can be understood that the vehicle includes multiple systems, and each system corresponds to multiple modules to be self-checked; for example, taking the vehicle including an electronic rearview mirror system as an example, the electronic rearview mirror system includes a power module, a hardware module, a software module, and a communication module. When the vehicle is started and powered on, it is necessary to perform a power self-check on the power module, a hardware self-check on the hardware module, a communication self-check on the communication module, and a fault self-check and a firmware version self-check on the software module.
[0031] Among them, different modules to be self-checked have different self-checking efficiencies under different starting environments; for example, in a low temperature environment, since the low temperature will have a greater impact on the battery, it is necessary to perform a more detailed inspection of the power module where the battery is located; based on the above reasons, during the vehicle startup process, this method will first determine the vehicle startup scenario, which includes but is not limited to: at least one of a low temperature startup scenario, a high temperature startup scenario, a night startup scenario, a sunny startup scenario, and a rainy startup scenario; how to determine the startup scenario will be described in detail later and will not be repeated here.
[0032] Continuing with the above example, in a low temperature environment, since low temperature will have a greater impact on the battery, the power module where the battery is located needs to be more carefully inspected in the low temperature startup scenario. The weight value of the power module in the low temperature startup scenario will be higher than the weight value of the power module in the high temperature or normal temperature startup scenario; in addition, the weight value of the module to be self-checked in the startup scenario is related to the target importance of the module to be self-checked itself. The higher the target importance of the module to be self-checked itself, the higher the weight value in the startup scenario; the lower the target importance of the module to be self-checked itself, the lower the weight value in the startup scenario.
[0033] Based on the above reasons, this example will first obtain the target importance of each module to be self-checked in the vehicle, and then determine the weight value of each module to be self-checked in the startup scenario according to the target importance of each module to be self-checked; among them, how to determine the target importance of each module to be self-checked will be described in detail later and will not be repeated here.
[0034] In some examples, the method will obtain at least two self-checking sequences, each of which is used to indicate the sequence of controlling multiple modules to be self-checked to perform self-checking; for example, when the vehicle is started, it includes three modules to be self-checked, namely A, B and C, and the self-checking sequences include the following: the first: A, B, C; the second: A, C, B; the third: B, A, C; the fourth: B, C, A; the fifth: C, B, A; the sixth: C, A, B. It can be understood that the number of self-checking sequences is related to the number of modules to be self-checked, wherein the upper limit of the number of self-checking sequences is the factorial of the number of modules to be self-checked.
[0035] It can be understood that different self-checking sequences will correspond to different detection costs, and the detection cost is used to characterize the detection efficiency of the self-checking sequence. The smaller the detection cost corresponding to the self-checking sequence, the higher the detection efficiency corresponding to the self-checking sequence; the larger the detection cost corresponding to the self-checking sequence, the lower the detection efficiency corresponding to the self-checking sequence; in order to determine the optimal target self-checking sequence from at least two self-checking sequences and achieve the effect of improving the detection efficiency of the module to be self-checked; this method calculates the detection cost of each self-checking sequence based on the weight value of each module to be self-checked in the startup scenario.
[0036] In some examples, after calculating the detection cost of each self-test sequence, this example also determines the target self-test sequence according to the detection cost corresponding to each self-test sequence; it can be understood that this step realizes the dynamic determination of the target self-test sequence according to the vehicle startup scenario. After determining the target self-test sequence, this method controls each module to be self-tested to perform power-on self-test based on the target self-test sequence.
[0037] According to the technical solution provided in the embodiment of the present application, during the vehicle startup process, the vehicle startup scenario is determined; the target importance of each module to be self-checked in the vehicle is obtained, and the weight value of each module to be self-checked in the startup scenario is determined according to the target importance of each module to be self-checked; at least two self-checking sequences are obtained, and each self-checking sequence is used to indicate the sequence of controlling multiple modules to be self-checked to perform self-checking; based on the weight value of each module to be self-checked in the startup scenario, the detection cost of each self-checking sequence is calculated, and the detection cost is used to characterize the detection efficiency of the module to be self-checked; according to the detection cost corresponding to each self-checking sequence, the target self-checking sequence is determined, and each module to be self-checked is controlled to perform power-on self-checking based on the target self-checking sequence; In the method, the weight value of each module to be self-checked in the startup scenario is dynamically determined according to the startup scenario and the importance of each module to be self-checked, and the detection cost of each self-checking sequence is calculated based on the weight value of each module to be self-checked in the startup scenario, so as to realize dynamic calculation of the detection cost of each self-checking sequence, determine the target self-checking sequence according to the detection to be checked, select the self-checking sequence whose detection efficiency meets the requirements, reduce the time required for module self-checking during the startup process, improve the startup efficiency of the vehicle, shorten the waiting time when the vehicle is started, and avoid the problem in the related technology that during the power-on startup of the vehicle, each module can only perform self-check according to the pre-set detection process, resulting in low power-on self-checking efficiency.
[0038] In some embodiments, Figure 2 As shown, based on the weight value of each module to be self-checked in the startup scenario, the detection cost of each self-check sequence is calculated, including:
[0039] S201, determining a self-checking cost of the module to be self-checked in the startup scenario based on a weight value of the module to be self-checked in the startup scenario;
[0040] S202, obtaining the impact cost of the first module to be self-checked on the second module to be self-checked in the order of two adjacent modules to be self-checked;
[0041] S203: taking the sum of each impact cost and the self-check cost of each module to be self-checked in the startup scenario as the detection cost of each self-check sequence.
[0042] Among them, this example will determine the self-test cost of the module to be self-tested in the startup scenario based on the weight value of the module to be self-tested in the startup scenario, and the self-test cost is used to characterize the detection efficiency of the module to be self-tested in the startup scenario, wherein the higher the self-test cost, the lower the detection efficiency of the module to be self-tested in the startup scenario, and the lower the self-test cost, the higher the detection efficiency of the module to be self-tested in the startup scenario; specifically, this example obtains the self-test depth of the module to be self-tested in the current startup scenario, the self-test time of the module to be self-tested in the current startup scenario, and then multiplies the weight value of the module to be self-tested in the startup scenario with the self-test depth and the self-test time to obtain the self-test cost of the module to be self-tested in the startup scenario.
[0043] For example, let the i-th module to be self-checked be ω i , the startup scenario is c, then the weight value of the i-th module to be self-checked in the startup scenario is ω i，c , the self-test depth of the i-th module to be self-tested in the startup scenario is d i , the self-test time of the i-th module to be self-tested in the startup scenario is t i , then the self-checking cost of the i-th module to be self-checked in the startup scenario = t i *ω i，c *d i .
[0044] It can be understood that after the module to be self-inspected in the vehicle performs self-inspection, it will affect the next module to be self-inspected. In order to more accurately obtain the detection cost of the self-inspection sequence, this example will also obtain the impact cost of the previous module to be self-inspected on the next module to be self-inspected in the two adjacent modules to be self-inspected in the self-inspection sequence. The impact cost is used to characterize the impact of the previous module to be self-inspected on the detection efficiency of the next module to be self-inspected after the self-inspection of the previous module to be self-inspected is completed; it can be understood that the impact cost of each module to be self-inspected on another module to be self-inspected is determined based on historical data, which will not be repeated here, wherein, assuming that the i-th (the value range of i is an integer greater than or equal to 1) module to be self-inspected in the self-inspection sequence is x i , then the next module to be self-checked is x i+1 , the impact cost of the i-th module to be self-checked on the i+1-th module to be self-checked is recorded as v i+1 ; If there are N modules to be self-checked, the total impact cost is v2 +v 3 +v 4 +…+v N .
[0045] In some examples, the sum of each impact cost and the self-test cost of each module to be self-tested in the startup scenario is used as the detection cost of each self-test sequence; specifically, the detection cost of the self-test sequence Among them, v i+1 is the impact cost of the i-th module to be self-checked on the i+1-th module to be self-checked, t i is the self-test time of the i-th module to be self-tested in the startup scenario, ω i , c is the weight value of the i-th module to be self-checked in the startup scenario, d i is the self-test depth of the i-th module to be self-tested in the startup scenario.
[0046] It can be understood that the self-inspection depth of the modules to be self-inspected in the vehicle can be adaptively adjusted as the starting scenario changes, ensuring that important modules to be self-inspected in specific starting scenarios are fully inspected, ensuring the reliability of key modules to be self-inspected in specific starting scenarios, improving the overall efficiency of self-inspection, and shortening unnecessary self-inspection time.
[0047] Specifically, the self-check depth of the module to be self-checked in the startup context is determined by the context urgency score of the startup context itself and the importance of the module to be self-checked in the startup context.
[0048] For example, let the starting situation be c, and the situation urgency score of the starting situation c be U c , where U c =eval_urgency(c), where eval_urgency() is a situational urgency scoring function, which may be determined based on historical data, or may be flexibly set by relevant personnel based on actual conditions.
[0049] Exemplarily, let the startup scenario be c, the module to be self-checked be ω, and the importance of the module to be self-checked in the startup scenario be I(ω,c), then I(ω,c)=eval_importance(ω,c), where eval_importance() is an importance evaluation function, which can be determined based on historical data, or can be flexibly set by relevant personnel based on actual conditions.
[0050] The self-check depth of the module to be self-checked in the startup scenario is determined by the scenario urgency score of the startup scenario itself and the importance of the module to be self-checked in the startup scenario, as follows:
[0051]
[0052] Among them, d i represents the self-check depth of the module to be self-checked i, I(ω,c) is the importance of the module to be self-checked ω in the startup scenario c, Emer threshold is the pre-set importance threshold, U c Score the situational urgency of the starting situation c, Imp threshold is a preset urgency threshold, A is a preset first self-check depth, and B is a preset second self-check depth, wherein A>B. Preferably, the value of A is 1 and the value of B is 0.
[0053] It can be understood that if the startup scenario changes during the startup of the vehicle, the self-test depth of the module to be self-checked can be re-determined according to the above method. When the self-test depth of the module to be self-checked changes, the vehicle can recalculate the detection cost of each self-check sequence, thereby realizing the redetermination of the target self-check sequence. The above method can automatically adjust the self-test depth of the module to be self-checked according to the urgency of the startup scenario and the importance of the module to be self-checked in the startup scenario, so that a more accurate target self-check module can be determined based on the adjusted self-check depth in the future, thereby improving the accuracy and efficiency of the detection of the module to be self-checked, ensuring that the various modules to be self-checked of the vehicle can respond quickly under various driving conditions, and shortening the overall self-check time while ensuring the normal operation of each module to be self-checked, greatly enhancing the driving experience and driving safety.
[0054] According to the technical solution provided by the embodiment of the present application, the self-test cost of the module to be self-tested in the startup scenario is determined based on the weight value of the module to be self-tested in the startup scenario; the influence cost of the previous module to be self-tested on the next module to be self-tested in the two adjacent modules to be self-tested in the self-test sequence is obtained; the sum of each influence cost and the self-test cost of each module to be self-tested in the startup scenario is used as the detection cost of each self-test sequence. The above method not only considers the self-test cost of each module to be self-tested, but also adds the influence cost between adjacent modules. This method can more accurately measure the actual detection cost of each self-test sequence, and effectively avoids the detection cost error caused by ignoring the mutual influence between the modules to be self-tested. In this way, the selection of the self-test sequence is more optimized, which improves the overall detection efficiency when the vehicle is started.
[0055] In some embodiments, Figure 3 As shown, a target self-test sequence is determined according to the detection cost corresponding to each self-test sequence, and each module to be self-tested is controlled to perform power-on self-test based on the target self-test sequence, including:
[0056] S301, according to the detection cost corresponding to each self-checking sequence, determining a self-checking sequence corresponding to the lowest detection cost from multiple self-checking sequences;
[0057] S302: Taking the self-test sequence corresponding to the lowest detection cost as the target self-test sequence, and controlling each module to be self-tested to perform power-on self-test based on the target self-test sequence.
[0058] Specifically, after determining the detection cost corresponding to each self-test sequence, in order to select the self-test sequence with the highest detection efficiency, this example determines the self-test sequence corresponding to the lowest detection cost from multiple self-test sequences; illustratively, the detection costs corresponding to all self-test sequences are sorted, and the self-test sequence corresponding to the lowest detection cost is determined according to the sorting results; for another example, the detection costs corresponding to all self-test sequences are traversed to determine the lowest detection cost.
[0059] In some examples, this example takes the self-test sequence corresponding to the lowest detection cost as the target self-test sequence, and controls each module to be self-tested to perform power-on self-test based on the target self-test sequence; wherein, the detection cost corresponding to the self-test sequence represents the detection efficiency of the module to be self-tested, and the smaller the detection cost corresponding to the self-test sequence, the higher the detection efficiency corresponding to the self-test sequence; the larger the detection cost corresponding to the self-test sequence, the lower the detection efficiency corresponding to the self-test sequence.
[0060] Continuing from the previous example, this example uses the self-test sequence corresponding to the lowest detection cost as the target self-test sequence, ensuring the minimization of the detection cost. Subsequently, each module to be self-tested is controlled to perform power-on self-test based on the target self-test sequence, thereby improving the overall detection efficiency when the vehicle is started, avoiding the limitations of traditional fixed-sequence self-tests, and improving the flexibility and adaptability of the self-test process.
[0061] According to the technical solution provided in the embodiment of the present application, based on the detection cost corresponding to each self-check sequence, a self-check sequence corresponding to the lowest detection cost is determined from multiple self-check sequences; the self-check sequence corresponding to the lowest detection cost is used as the target self-check sequence, and each module to be self-checked is controlled to perform power-on self-check based on the target self-check sequence, thereby ensuring the minimization of the detection cost, thereby improving the overall detection efficiency when the vehicle is started, avoiding the limitations of traditional fixed-sequence self-checks, and improving the flexibility and adaptability of the self-check process.
[0062] In some embodiments, Figure 4 As shown, the vehicle startup scenario is determined, including:
[0063] S401, obtaining temperature data through a temperature sensor provided on the vehicle, obtaining light intensity through a light intensity sensor provided on the vehicle, and obtaining rainfall value through a rainfall sensor provided on the vehicle;
[0064] S402, comparing the temperature data with a preset temperature threshold to obtain a temperature comparison result; comparing the light intensity with a preset light threshold to obtain a light comparison result; comparing the rainfall value with a preset rainfall threshold to obtain a rainfall comparison result;
[0065] S403: Determine a start-up scenario according to the temperature comparison result, the light comparison result, and the rainfall comparison result.
[0066] Specifically, the sensors installed on the vehicle are the basis for collecting data about the vehicle and its surrounding environment. The sensors installed on the vehicle, such as temperature sensors, photosensors, and rain sensors, are used to collect data about the internal and external environments of the vehicle, which are used to monitor the basic conditions of the environment in which the vehicle is located, including but not limited to temperature, humidity, light intensity, and other data. Each sensor will add a timestamp when collecting data to record the time point of data collection, which helps to identify the time period in which the vehicle is currently located, such as early morning, evening, and night, which is particularly important for judging lighting conditions. The temperature sensor is used to measure the temperature inside and outside the vehicle, and can determine the vehicle startup temperature, such as low temperature, normal temperature, and high temperature environment, to ensure that each module of the vehicle can operate effectively under extreme temperature conditions; the photosensor measures the external light intensity. It can be understood that when the vehicle starts, the temperature, humidity, light intensity, and other data can be obtained through the above-mentioned temperature sensor, photosensor, and rain sensor.
[0067] It is understandable that the above data such as temperature, humidity, and light intensity provide key information for subsequent startup scenario identification, ensuring that each system on the vehicle can intelligently adjust the self-test process according to the current startup scenario. By continuously monitoring scenario changes, such as a sudden drop in external temperature or a change in light intensity, the environmental data acquisition module provides real-time data support for the dynamic adjustment of the self-test sequence, ensuring that the system can respond quickly and provide immediate and accurate visual information, thereby enhancing the driving experience and driving safety.
[0068] Specifically, the method identifies the startup context of the vehicle based on the information provided by the sensor. The specific environmental conditions when the vehicle is started are determined by comprehensively analyzing the internal and external environmental data of the vehicle, including temperature, light intensity, rainfall, and timestamp information. For example, the temperature data T monitored by the temperature sensor and the light intensity L monitored by the light intensity sensor, combined with the timestamp T ime The rainfall sensor rainfall value R can be used to determine whether the vehicle is in a low-temperature start-up situation, a night start-up situation, or a rainy day start-up situation.
[0069] Specifically, the temperature data T, light intensity L, and rainfall value R are represented by the environmental parameter E, then E = {T, L, R ...}, and then the temperature data is compared with the preset temperature threshold to obtain the temperature comparison result; the light intensity is compared with the preset light threshold to obtain the light comparison result; the rainfall value is compared with the preset rainfall threshold to obtain the rainfall comparison result; illuminating the comparison process by means of a function, for example, the following function is used:
[0070] C=f(E,T ime );
[0071]
[0072] In the above function, C is the starting context, T ime represents the timestamp; T represents the temperature data; T thr,cold Indicates the temperature threshold corresponding to low temperature; T thr,hot represents the temperature threshold corresponding to high temperature; L represents the light intensity; T thr,night represents the light threshold; T thr,rain represents the rainfall threshold; if T <T thr,cold , then the vehicle start-up scenario includes a low-temperature start-up scenario; if T>T thr,hot , then the vehicle start-up scenario includes a low-temperature start-up scenario; if L <T thr,night , then the vehicle start-up scenario includes the night start-up scenario; if R>T thr,rain , the vehicle's starting scenario includes a rainy day starting scenario.
[0073] It can be understood that the relationship between the above-mentioned startup scenarios and environmental data is only used for illustrative purposes, and is not used to limit the startup scenarios in this method to only include the above-mentioned types; relevant personnel can flexibly set the environmental data collected by the vehicle according to actual conditions, and how to determine the corresponding startup scenario based on the environmental data.
[0074] According to the technical solution provided in the embodiment of the present application, temperature data is obtained by a temperature sensor arranged on the vehicle, light intensity is obtained by a photosensitivity sensor arranged on the vehicle, and rainfall value is obtained by a rain sensor arranged on the vehicle; the temperature data is compared with a preset temperature threshold to obtain a temperature comparison result; the light intensity is compared with a preset light threshold to obtain a light comparison result; the rainfall value is compared with a preset rainfall threshold to obtain a rainfall comparison result; the startup scenario is determined based on the temperature comparison result, the light comparison result and the rainfall comparison result. The above method realizes accurate determination of the startup environment of the vehicle.
[0075] In some embodiments, Figure 5 As shown, the target importance of each module to be self-checked in the vehicle is obtained, including:
[0076] S501, obtaining the function importance of the module to be self-checked, and obtaining the context sensitivity of the module to be self-checked;
[0077] S502: Obtain weight coefficients corresponding to function importance and context sensitivity, perform weighted summation of function importance and context sensitivity according to the weight coefficients corresponding to function importance and context sensitivity, and obtain target importance corresponding to the module to be self-checked.
[0078] In order to ensure that each system on the vehicle can quickly enter the working state when starting, the situational awareness and module importance are evaluated at the same time, and the power-on self-test sequence is adjusted according to different startup scenarios to improve the self-test efficiency and accuracy of the modules to be self-tested.
[0079] Specifically, the method obtains the contextual sensitivity of the module to be self-checked by obtaining the functional importance of the module to be self-checked, wherein the functional importance of the module to be self-checked is a pre-set value representing the importance of the module to be self-checked, and the contextual sensitivity of the module to be self-checked is a value representing the degree of influence of the module to be self-checked on the startup context; illustratively, when the module to be self-checked is a power module, it is more sensitive to the startup context because it is easily affected by the outside world (such as high temperature and / or low temperature will affect the power module); when the module to be self-checked is a communication module, the communication module is not easily affected by the outside world, and the contextual sensitivity of the power module is higher than that of the communication module; in some examples, the main function of the contextual sensitivity is to determine the criticality of the module to be self-checked in a specific context so as to give it a higher priority.
[0080] It can be understood that the functional importance and situational sensitivity of the module to be self-checked can be values set by relevant personnel based on the actual situation of the vehicle; the functional importance and situational sensitivity of the module to be self-checked can also be values determined by collecting historical data through a big data model.
[0081] This method also obtains the weight coefficients corresponding to the function importance and the situational sensitivity, and performs weighted summation of the function importance and the situational sensitivity according to the weight coefficients corresponding to the function importance and the situational sensitivity to obtain the target importance corresponding to the module to be self-checked.
[0082] For example, let the functional importance of the module to be self-checked be F, the context sensitivity of the module to be self-checked be T, the weight coefficient corresponding to the functional importance be θ1, and the weight coefficient corresponding to the context sensitivity be θ2, then the functional importance of the module to be self-checked is I=θ 1 *F+θ 2 *T.
[0083] According to the technical solution provided in the embodiment of the present application, the functional importance of the module to be self-checked is obtained, and the contextual sensitivity of the module to be self-checked is obtained; the weight coefficients corresponding to the functional importance and the contextual sensitivity are obtained, and the functional importance and the contextual sensitivity are weightedly summed according to the weight coefficients corresponding to the functional importance and the contextual sensitivity to obtain the target importance corresponding to the module to be self-checked. The above method takes into account the functional importance and contextual sensitivity of the module to be self-checked itself, so that the determined target importance is more in line with various startup scenarios.
[0084] In some embodiments, Figure 6 As shown, the weight value of each module to be self-checked in the startup scenario is determined according to the target importance of each module to be self-checked, including:
[0085] S601, obtaining a function score of the module to be self-checked in a startup scenario, and obtaining a scenario sensitivity score of the module to be self-checked in a startup scenario;
[0086] S602, obtaining weight coefficients corresponding to the function score, the scenario sensitivity score and the target importance, and performing weighted summation of the function score, the scenario sensitivity score and the target importance according to the weight coefficients corresponding to the function score, the scenario sensitivity score and the target importance to obtain the weight value of the module to be self-checked in the startup scenario.
[0087] It can be understood that the functional score of the module to be self-checked in the startup scenario is obtained, and the functional score is given by relevant personnel based on prior knowledge; in some examples, the functional score of the module to be self-checked in the startup scenario can also be determined by a big data model based on historical data, and the functional score of the module to be self-checked in the startup scenario represents the importance of the module to be self-checked in the current startup scenario.
[0088] Obtain a situational sensitivity score of the module to be self-checked in the startup scenario, where the situational sensitivity score of the module to be self-checked in the startup scenario is given by relevant personnel based on prior knowledge; in some examples, the situational sensitivity score of the module to be self-checked in the startup scenario can also be determined by a big data model based on historical data; it can be understood that the situational sensitivity score of the module to be self-checked in the startup scenario represents the impact of the current startup scenario on the module to be self-checked.
[0089] In some examples, the weight coefficients corresponding to the function score, the situational sensitivity score, and the target importance are obtained, and the function score, the situational sensitivity score, and the target importance are weighted and summed according to the weight coefficients corresponding to the function score, the situational sensitivity score, and the target importance to obtain the weight value of the module to be self-checked in the startup scenario. For example, the startup scenario is recorded as c, and the function score of the module to be self-checked in the startup scenario is recorded as E c, the situational sensitivity score of the module to be self-checked in the startup situation is recorded as S c , the target importance of the module to be self-checked is recorded as I, and the weight coefficients corresponding to the function score, situation sensitivity score and target importance are recorded as α, γ, and δ respectively. Then the weight value ω of the module to be self-checked in the startup situation is c =α*E c +γ*I+δ*S c ; In some examples, γ and δ are equal, then ω c =α*E c +γ*(I+S c ).
[0090] According to the technical solution provided in the embodiment of the present application, the function score of the module to be self-checked in the startup scenario is obtained, and the scenario sensitivity score of the module to be self-checked in the startup scenario is obtained; the weight coefficients corresponding to the function score, the scenario sensitivity score and the target importance are obtained, and the function score, the scenario sensitivity score and the target importance are weighted and summed according to the weight coefficients corresponding to the function score, the scenario sensitivity score and the target importance to obtain the weight value of the module to be self-checked in the startup scenario. The above method takes into account the function importance of the module to be self-checked itself, the function score of the module to be self-checked in the current startup scenario and the scenario sensitivity score of the module to be self-checked in the startup scenario, thereby achieving accurate acquisition of the weight value of the module to be self-checked in the startup scenario.
[0091] In some embodiments, Figure 7 As shown, after controlling each module to be self-tested to perform a power-on self-test based on the target self-test sequence, the method further includes:
[0092] S701, if any module to be self-checked has an abnormality in self-check, an abnormality detection result is generated;
[0093] S702: Determine the abnormality level of the vehicle according to the abnormality detection result. If the abnormality level is lower than a preset abnormality threshold, start the vehicle and issue an abnormality reminder.
[0094] Specifically, after the modules to be self-checked complete the power-on self-check according to the self-check sequence, if any module to be self-checked has an abnormality in the self-check, an abnormality detection result is generated; the abnormality degree of the vehicle is determined based on the abnormality detection result; if the abnormality degree is lower than a preset abnormality threshold, the vehicle is started and an abnormality reminder is issued.
[0095] It can be understood that there are multiple modules in each system of the vehicle. If the abnormality of some modules does not affect the safe driving of the vehicle, the vehicle can be started normally and an abnormal reminder will be issued to remind the user; if the abnormality of some modules will affect the safe driving of the vehicle, the vehicle will be stopped and an alarm will be issued; for example, taking the electronic rearview mirror as an example, the electronic rearview mirror includes a display module and a heating module. If the heating module of the electronic rearview mirror fails in self-check, since the user can still use the electronic rearview mirror, the heating module has little impact on the vehicle, and the abnormality of the vehicle is low, then the vehicle is started and an abnormal reminder is issued, so that the user can know that the heating module is abnormal and needs to be repaired as soon as possible; if the display module of the electronic rearview mirror fails, the user cannot use the electronic rearview mirror, and the electronic rearview mirror has a greater impact on the vehicle. At this time, the abnormality of the vehicle is higher than the preset abnormal threshold. Stop starting the vehicle and issue an alarm to remind the user.
[0096] It can be understood that the abnormality degree corresponding to the abnormal detection result of each module to be self-checked can be flexibly set by relevant personnel according to actual needs, and the abnormal threshold can also be flexibly set by relevant personnel according to actual needs.
[0097] In order to better understand the present method, this embodiment provides a more specific example for illustration. An electronic rearview mirror is provided on a vehicle, and a communication module, a heating module, a display module, etc. are provided in the electronic rearview mirror. Figure 8 As shown, when the vehicle is powered on and started, environmental data is first collected to obtain data such as temperature, light intensity, time, and rainfall. Then, the startup scenario is identified based on the above-mentioned temperature, light intensity, time, and rainfall data. Then, the target self-check sequence is determined based on the startup scenario. If the subsequent startup scenario changes, environmental data can be collected again and the target self-check sequence can be re-determined. It can be understood that this method continuously monitors the startup scenario of the vehicle. If the external temperature suddenly drops, it will trigger the self-check process optimization mechanism. According to the changes in the startup scenario, the weight value of each module to be self-checked is recalculated to obtain the target self-check sequence to ensure that the key modules to be self-checked are fully checked. The self-check sequence can be intelligently adjusted according to changes in the scenario, thereby improving the accuracy and efficiency of fault detection and ensuring that the system can respond quickly under various driving conditions to provide instant and accurate information.
[0098] It can be understood that the above-mentioned environmental data can also be used for subsequent control of the electronic rearview mirror. For example, by measuring the temperature inside and outside the vehicle, it can be determined whether the vehicle is in a low-temperature start-up scenario, a normal temperature start-up scenario or a high-temperature start-up scenario, and then determine whether additional heating or cooling measures are required when the electronic rearview mirror is started, to ensure that the electronic rearview mirror can operate effectively under extreme temperature conditions; for another example, a photosensor measures the external light intensity and is used to adjust the brightness of the electronic rearview mirror display to adapt to different lighting conditions.
[0099] According to the technical solution provided in the embodiment of the present application, if any module to be self-checked has an abnormality, an abnormality detection result is generated; the abnormality degree of the vehicle is determined based on the abnormality detection result; if the abnormality degree is lower than a preset abnormality threshold, the vehicle is started and an abnormality reminder is issued, so that the user can be informed of the vehicle's condition in a timely manner when the vehicle has an abnormality, thereby ensuring the user's driving safety.
[0100] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.
[0101] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.
[0102] This embodiment also provides a vehicle power-on self-test device, such as Fig. 9 As shown, the device comprises:
[0103] The environment module 901 is configured to determine the vehicle startup context during the vehicle startup process;
[0104] A weight module 902 is configured to obtain a target importance of each module to be self-checked in the vehicle, and determine a weight value of each module to be self-checked in the startup scenario according to the target importance of each module to be self-checked;
[0105] The self-test module 903 is configured to obtain at least two self-test sequences, each self-test sequence is used to indicate the order of controlling multiple modules to be self-tested to perform self-test; based on the weight value of each module to be self-tested in the startup scenario, the detection cost of each self-test sequence is calculated, and the detection cost is used to characterize the detection efficiency of the self-test sequence; according to the detection cost corresponding to each self-test sequence, a target self-test sequence is determined, and each module to be self-tested is controlled to perform power-on self-test based on the target self-test sequence.
[0106] In some examples, the self-test module 903 is also configured to determine the self-test cost of the module to be self-tested in the startup scenario based on the weight value of the module to be self-tested in the startup scenario, and the self-test cost is used to characterize the detection efficiency of the module to be self-tested in the startup scenario; obtain the impact cost of the previous module to be self-tested on the next module to be self-tested in the self-test sequence, and the impact cost is used to characterize the efficiency impact of the previous module to be self-tested on the detection efficiency of the next module to be self-tested after the self-test of the previous module to be self-tested is completed; and take the sum of each impact cost and the self-test cost of each module to be self-tested in the startup scenario as the detection cost of each self-test sequence.
[0107] In some examples, the self-test module 903 is also configured to determine a self-test sequence corresponding to a minimum detection cost from multiple self-test sequences based on the detection cost corresponding to each self-test sequence; use the self-test sequence corresponding to the minimum detection cost as the target self-test sequence, and control each module to be self-tested to perform power-on self-test based on the target self-test sequence.
[0108] In some examples, the environment module 901 is also configured to obtain temperature data through a temperature sensor provided on the vehicle, obtain light intensity through a photosensitivity sensor provided on the vehicle, and obtain rainfall value through a rain sensor provided on the vehicle; compare the temperature data with a preset temperature threshold to obtain a temperature comparison result; compare the light intensity with a preset light threshold to obtain a light comparison result; compare the rainfall value with a preset rainfall threshold to obtain a rainfall comparison result; and determine the startup scenario based on the temperature comparison result, the light comparison result, and the rainfall comparison result.
[0109] In some examples, the weight module 902 is also configured to obtain the functional importance of the module to be self-checked and the contextual sensitivity of the module to be self-checked; obtain the weight coefficients corresponding to the functional importance and the contextual sensitivity, and perform weighted summation of the functional importance and the contextual sensitivity according to the weight coefficients corresponding to the functional importance and the contextual sensitivity to obtain the target importance corresponding to the module to be self-checked.
[0110] In some examples, the weight module 902 is also configured to obtain a function score of the module to be self-checked in the startup scenario, and obtain a situational sensitivity score of the module to be self-checked in the startup scenario; obtain weight coefficients corresponding to the function score, the situational sensitivity score, and the target importance, and perform weighted summation of the function score, the situational sensitivity score, and the target importance according to the weight coefficients corresponding to the function score, the situational sensitivity score, and the target importance to obtain a weight value of the module to be self-checked in the startup scenario.
[0111] In some examples, the self-check module 903 is also configured to generate an abnormality detection result when any module to be self-checked has an abnormality; determine the degree of abnormality of the vehicle based on the abnormality detection result; if the degree of abnormality is lower than a preset abnormality threshold, start the vehicle and issue an abnormality reminder.
[0112] According to the technical solution provided in the embodiment of the present application, the power-on self-test device of the vehicle provided in the embodiment determines the startup scenario of the vehicle during the startup process of the vehicle; obtains the target importance of each module to be self-tested in the vehicle, and determines the weight value of each module to be self-tested in the startup scenario according to the target importance of each module to be self-tested; obtains at least two self-test sequences, each self-test sequence is used to indicate the order of controlling multiple modules to be self-tested to perform self-tests; based on the weight value of each module to be self-tested in the startup scenario, calculates the detection cost of each self-test sequence, and the detection cost is used to characterize the detection efficiency of the module to be self-tested; determines the target self-test sequence according to the detection cost corresponding to each self-test sequence, and controls each module to be self-tested based on the target self-test sequence. Perform power-on self-test; wherein, the method dynamically determines the weight value of each module to be self-tested in the startup scenario according to the startup scenario and the importance of each module to be self-tested, and calculates the detection cost of each self-test sequence based on the weight value of each module to be self-tested in the startup scenario, thereby realizing dynamic calculation of the detection cost of each self-test sequence, and determining the target self-test sequence according to the detection to be tested, selecting a self-test sequence whose detection efficiency meets the requirements, reducing the time required for module self-test during the startup process, improving the startup efficiency of the vehicle, shortening the waiting time when the vehicle is started, and avoiding the problem in the related technology that during the power-on startup of the vehicle, each module can only perform self-test according to a pre-set detection process, resulting in low power-on self-test efficiency.
[0113] Fig.10 Schematic diagram of an electronic device 10 provided in an embodiment of the present application. Fig.10 As shown, the electronic device 10 of this embodiment includes: a processor 1001, a memory 1002, and a computer program 1003 stored in the memory 1002 and executable on the processor 1001. When the processor 1001 executes the computer program 1003, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 1001 executes the computer program 1003, the functions of the modules / units in the above-mentioned device embodiments are implemented.
[0114] The electronic device 10 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 10 may include, but is not limited to, a processor 1001 and a memory 1002. Those skilled in the art will appreciate that Fig.10 The electronic device 10 is merely an example and does not limit the electronic device 10 . The electronic device 10 may include more or fewer components than shown in the figure, or different components.
[0115] Processor 1001 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
[0116] The memory 1002 may be an internal storage unit of the electronic device 10, for example, a hard disk or memory of the electronic device 10. The memory 1002 may also be an external storage device of the electronic device 10, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (FlashCard), etc. equipped on the electronic device 10. The memory 1002 may also include both an internal storage unit of the electronic device 10 and an external storage device. The memory 1002 is used to store computer programs and other programs and data required by the electronic device.
[0117] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.
[0118] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of regional requirements and patent practice. For example, in some areas, according to regional requirements and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.
[0119] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.
Claims
1. A vehicle power-on self-test method, characterized in that: The method comprises: During the vehicle startup process, determining the vehicle startup context; Obtaining a target importance of each module to be self-checked in the vehicle, and determining a weight value of each module to be self-checked in the startup scenario according to the target importance of each module to be self-checked; Acquire at least two self-test sequences, each of which is used to indicate the sequence of controlling the plurality of modules to be self-tested to perform self-test; Calculating the detection cost of each of the self-checking sequences based on the weight value of each of the modules to be self-checked in the startup scenario, wherein the detection cost is used to characterize the detection efficiency of the self-checking sequence; A target self-test sequence is determined according to the detection cost corresponding to each of the self-test sequences, and each of the modules to be self-tested is controlled to perform a power-on self-test based on the target self-test sequence.
2. The method according to claim 1, characterized in that: Calculating the detection cost of each of the self-checking sequences based on the weight value of each of the modules to be self-checked in the startup scenario includes: Determining a self-test cost of the module to be self-tested in the startup scenario based on a weight value of the module to be self-tested in the startup scenario, wherein the self-test cost is used to characterize a detection efficiency of the module to be self-tested in the startup scenario; Obtaining the impact cost of the previous module to be self-checked on the next module to be self-checked in the self-checking sequence, wherein the impact cost is used to characterize the efficiency impact of the previous module to be self-checked on the detection efficiency of the next module to be self-checked after the self-checking of the previous module to be self-checked is completed; The sum of each of the impact costs and the self-test cost of each of the modules to be self-tested in the startup scenario is used as the detection cost of each of the self-test sequences.
3. The method according to claim 1, characterized in that Determining a target self-test sequence according to the detection cost corresponding to each of the self-test sequences, and controlling each of the modules to be self-tested to perform a power-on self-test based on the target self-test sequence, including: According to the detection cost corresponding to each of the self-checking sequences, determining the self-checking sequence corresponding to the lowest detection cost from the plurality of the self-checking sequences; The self-test sequence corresponding to the lowest detection cost is used as the target self-test sequence, and each module to be self-tested is controlled to perform power-on self-test based on the target self-test sequence.
4. The method according to claim 1, characterized in that Determine the vehicle's start-up scenario, including: Acquire temperature data through a temperature sensor provided on the vehicle, acquire light intensity through a light-sensitive intensity sensor provided on the vehicle, and acquire rainfall value through a rainfall sensor provided on the vehicle; Compare the temperature data with a preset temperature threshold to obtain a temperature comparison result; compare the light intensity with a preset light threshold to obtain a light comparison result; compare the rainfall value with a preset rainfall threshold to obtain a rainfall comparison result; The activation scenario is determined according to the temperature comparison result, the illumination comparison result, and the rainfall comparison result.
5. The method according to claim 1, characterized in that Obtaining the target importance of each module to be self-checked in the vehicle, including: Obtaining the function importance of the module to be self-checked, and obtaining the context sensitivity of the module to be self-checked; Obtain weight coefficients corresponding to the function importance and the context sensitivity, and perform weighted summation of the function importance and the context sensitivity according to the weight coefficients corresponding to the function importance and the context sensitivity to obtain the target importance corresponding to the module to be self-checked.
6. The method according to claim 5, characterized in that Determining the weight value of each module to be self-checked in the startup scenario according to the target importance of each module to be self-checked includes: Obtaining a function score of the module to be self-checked in the startup scenario, and obtaining a context sensitivity score of the module to be self-checked in the startup scenario; Obtain weight coefficients corresponding to the function score, the scenario sensitivity score, and the target importance, and perform weighted summation of the function score, the scenario sensitivity score, and the target importance according to the weight coefficients corresponding to the function score, the scenario sensitivity score, and the target importance to obtain the weight value of the module to be self-checked in the startup scenario.
7. The method according to claim 6, characterized in that After controlling each module to be self-tested to perform a power-on self-test based on the target self-test sequence, the method further includes: If any of the modules to be self-checked has an abnormality in self-check, an abnormality detection result is generated; The abnormality level of the vehicle is determined according to the abnormality detection result. If the abnormality level is lower than a preset abnormality threshold, the vehicle is started and an abnormality reminder is issued.
8. A vehicle power-on self-test device, characterized in that: The device comprises: An environment module is configured to determine a startup context of the vehicle during startup of the vehicle; A weight module is configured to obtain a target importance of each module to be self-checked in the vehicle, and determine a weight value of each module to be self-checked in the startup scenario according to the target importance of each module to be self-checked; The self-test module is configured to obtain at least two self-test sequences, each of which is used to indicate the order of controlling the multiple modules to be self-tested to perform self-test; based on the weight value of each module to be self-tested in the startup scenario, the detection cost of each self-test sequence is calculated, and the detection cost is used to characterize the detection efficiency of the self-test sequence; according to the detection cost corresponding to each self-test sequence, a target self-test sequence is determined, and each module to be self-tested is controlled to perform power-on self-test based on the target self-test sequence.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium storing 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 7 are implemented.