Method, device and electronic equipment for monitoring the state of a vehicle microcontroller chip

Abstract

The application discloses a kind of vehicle microcontroller chip state monitoring method, device and electronic equipment.Therein, the method comprises: based on preset frequency signal acquisition instruction is sent to target vehicle;At least one vehicle state signal of target vehicle and the input and output signal of microcontroller chip on target vehicle are received based on signal acquisition instruction collection;Determine the current vehicle state of target vehicle based on at least one vehicle state signal;Call the preset fuzzy rule logic library corresponding to current vehicle state, and based on input and output signal and preset fuzzy rule logic library, the state of microcontroller chip is identified, and the target working state of microcontroller chip is obtained, wherein, preset fuzzy rule logic library is used to indicate the corresponding relationship between the input and output signal and working state of chip described by fuzzy semantic logic.The application solves the technical problem that the efficiency of vehicle microcontroller chip state monitoring is relatively low.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicles, in particular to a vehicle microcontroller chip state monitoring method and device and electronic equipment. BACKGROUND

[0002] With the continuous improvement of vehicle electronicization and intelligence, the demand for vehicle micro control chips is also growing. Micro control chips can help vehicles achieve more complex and intelligent control functions, promote the development of vehicle intelligence, while ensuring the safety of vehicles and passengers, improving vehicle safety, and playing a key role in collision prevention, theft prevention, network security, etc.

[0003] However, due to the complexity and variability of the vehicle working environment, the current state monitoring of the vehicle microcontroller chip usually needs to set up a chip state monitoring chip on the vehicle, which increases the manufacturing cost of the vehicle and needs to frequently update and upgrade the additionally set chip state monitoring chip, or needs to occupy part of the operation and storage resources of the vehicle microcontroller chip itself for state monitoring and analysis, which is difficult to monitor the state of the vehicle microcontroller chip in time and accurately, that is, the efficiency of monitoring the state of the vehicle microcontroller chip is low.

[0004] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0005] The embodiments of the present application provide a vehicle microcontroller chip state monitoring method, device and electronic equipment to at least solve the technical problem of low efficiency of monitoring the state of the vehicle microcontroller chip.

[0006] According to an aspect of an embodiment of the present application, a vehicle microcontroller chip state monitoring method applied to a cloud server is provided, comprising: sending a signal collection instruction to a target vehicle based on a preset frequency, wherein the target vehicle is used to represent a vehicle to be monitored for microcontroller chip state; receiving at least one vehicle state signal of the target vehicle and an input and output signal of the microcontroller chip on the target vehicle collected based on the signal collection instruction; determining a current vehicle state of the target vehicle based on the at least one vehicle state signal; calling a preset fuzzy rule logic library corresponding to the current vehicle state, and performing state recognition on the microcontroller chip based on the input and output signal and the preset fuzzy rule logic library to obtain a target working state of the microcontroller chip, wherein the preset fuzzy rule logic library is used to represent the corresponding relationship between the input and output signal and the working state of the chip described by fuzzy semantic logic.

[0007] Optionally, the target working state comprises fault type information, and the state of the microcontroller chip is identified based on the input and output signals and the preset fuzzy rule logic library to obtain the target working state of the microcontroller chip, comprising: identifying the fault of the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals by using a target chip fault identification model, to obtain the fault type information, wherein the target chip fault identification model is used to represent a machine learning model for identifying the fault of the microcontroller chip by taking the preset fuzzy rule logic library as a built-in fault identification condition.

[0008] Optionally, the microcontroller chip comprises a processor, and the fault type information comprises processor fault type information, and the fault of the microcontroller chip is identified based on the preset fuzzy rule logic library and the input and output signals by using the target chip fault identification model to obtain the fault type information, comprising: obtaining a processor fault rule sub-library in the preset fuzzy rule logic library, wherein the processor fault rule sub-library is used to represent a processor fault signal library established based on processor historical abnormal signals; screening the input and output signals by using the processor fault rule sub-library to obtain processor abnormal signals; and identifying the fault of the microcontroller chip based on a preset safety threshold and the processor abnormal signals to obtain the processor fault type information, wherein the preset safety threshold is used to represent a feasible domain threshold of the processor input and output signals preset in advance.

[0009] Optionally, the microcontroller chip comprises a storage unit, and the fault type information comprises storage unit fault type information, and the fault of the microcontroller chip is identified based on the preset fuzzy rule logic library and the input and output signals by using the target chip fault identification model to obtain the fault type information, comprising: obtaining a storage unit fault rule sub-library in the preset fuzzy rule logic library, wherein the storage unit fault rule sub-library is used to represent a storage unit fault signal library established based on storage unit historical abnormal signals; screening the input and output signals by using the storage unit fault rule sub-library to obtain storage unit abnormal signals; obtaining a signal response duration of the storage unit abnormal signals, wherein the signal response duration is used to represent a duration between input of a first input signal to the storage unit and output of a first response signal from the storage unit, and the first input signal is used to represent a storage unit input signal in the storage unit abnormal signals; and identifying the fault of the microcontroller chip based on the signal response duration to obtain the storage unit fault type information.

[0010] Optionally, the microcontroller chip comprises a peripheral device, the fault type information comprises peripheral device fault type information, and the fault identification of the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals by using the target chip fault identification model to obtain the fault type information comprises: obtaining a multi-modal fault rule sub-library in the preset fuzzy rule logic library, wherein the multi-modal fault rule sub-library is used to represent a peripheral device fault signal library established based on peripheral device historical abnormal signals; screening the input and output signals by using the multi-modal fault rule sub-library to obtain peripheral device abnormal signals; and identifying the fault of the microcontroller chip based on the peripheral device abnormal signals to obtain the peripheral device fault type information.

[0011] Optionally, the fault identification of the microcontroller chip based on the peripheral device abnormal signals to obtain the peripheral device fault type information comprises: obtaining a signal transmission interruption frequency, a signal transmission error rate and a signal timing error of the peripheral device abnormal signals; identifying the fault of the microcontroller chip based on the signal transmission interruption frequency to obtain power unit fault information; identifying the fault of the microcontroller chip based on the signal transmission error rate to obtain bus fault information; identifying the fault of the microcontroller chip based on the signal timing error to obtain clock fault information; and determining the peripheral device fault type information based on the power unit fault information, the bus fault information and the clock fault information.

[0012] Optionally, the receiving of the at least one vehicle state signal of the target vehicle and the input and output signals of the microcontroller chip on the target vehicle comprises: receiving initial input and output signals of the microcontroller chip, wherein the initial input and output signals are used to represent input signals and / or output signals of the microcontroller chip directly received; and performing feature extraction on the initial input and output signals based on preset signal features to obtain the input and output signals, wherein the preset signal features at least comprise one of the following: waveform features, frequency features and amplitude features.

[0013] According to another aspect of the embodiment of the present application, a vehicle microcontroller chip state monitoring device is further provided, comprising: an acquisition module configured to send a signal acquisition instruction to a target vehicle based on a preset frequency, wherein the target vehicle is used to represent a vehicle to be monitored for a microcontroller chip state; a receiving module configured to receive at least one vehicle state signal of the target vehicle and input and output signals of a microcontroller chip on the target vehicle acquired based on the signal acquisition instruction; a determination module configured to determine a current vehicle state of the target vehicle based on the at least one vehicle state signal; and a calling module configured to call a preset fuzzy rule logic library corresponding to the current vehicle state, and identify a state of the microcontroller chip based on the input and output signals and the preset fuzzy rule logic library to obtain a target working state of the microcontroller chip, wherein the preset fuzzy rule logic library is used to represent a corresponding relationship between input and output signals and working states of the chip described by fuzzy semantic logic.

[0014] According to another aspect of the embodiments of the present application, an electronic device is also provided, comprising a memory storing an executable program, and a processor configured to execute the program, wherein the program, when executed, performs the method for monitoring the state of the vehicle microcontroller chip.

[0015] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, comprising a stored executable program, wherein the executable program, when executed, controls a device in which the storage medium is located to perform the method for monitoring the state of the vehicle microcontroller chip.

[0016] According to another aspect of the embodiments of the present application, a computer program product is also provided, wherein the computer program, when executed by a processor, implements the method for monitoring the state of the vehicle microcontroller chip.

[0017] In the embodiments of the present application, a method for monitoring the state of a vehicle microcontroller chip applied to a cloud server is adopted, a signal acquisition instruction is sent to a target vehicle based on a preset frequency, wherein the target vehicle is used to represent a vehicle to be monitored for the state of the microcontroller chip; at least one vehicle state signal of the target vehicle and an input / output signal of the microcontroller chip on the target vehicle are received based on the signal acquisition instruction; a current vehicle state of the target vehicle is determined based on the at least one vehicle state signal; a preset fuzzy rule logic library corresponding to the current vehicle state is called, and the state of the microcontroller chip is identified based on the input / output signal and the preset fuzzy rule logic library, to obtain a target working state of the microcontroller chip, wherein the preset fuzzy rule logic library is used to represent the corresponding relationship between the input / output signal and the working state of the chip described by fuzzy semantic logic. It is easy to note that the preset fuzzy rule logic library corresponding to the current vehicle state is selected from a plurality of preset fuzzy rule logic libraries according to the vehicle state signal, which can improve the adaptation degree of the selected preset fuzzy rule logic library to the current vehicle state, so that when the selected preset fuzzy rule logic library is used to identify the state of the microcontroller chip based on the input / output signal of the microcontroller chip, the problem of the microcontroller chip can be more easily identified, thereby improving the fault identification accuracy of the vehicle microcontroller chip, and further solving the technical problem of low efficiency of monitoring the state of the vehicle microcontroller chip. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0019] Figure 1is a flow chart of a vehicle micro control chip state monitoring method according to an embodiment of the present application;

[0020] Figure 2 is a flow chart of an optional vehicle micro control chip state monitoring method according to an embodiment of the present application;

[0021] Figure 3 is a flow chart of an optional vehicle end and cloud server interaction in a state monitoring process according to an embodiment of the present application;

[0022] Figure 4 is a schematic diagram of a vehicle micro controller chip state monitoring device according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0025] Embodiment 1

[0026] According to an embodiment of the present application, an embodiment of a vehicle micro control chip state monitoring method is provided. It should be noted that the steps shown in the flow chart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flow chart, in some cases, the steps shown or described herein can be executed in an order different from that herein.

[0027] Figure 1 is a flow chart of a vehicle micro control chip state monitoring method according to an embodiment of the present application, such as Figure 1As shown, the method comprises the following steps:

[0028] In step S102, a signal acquisition instruction is sent to the target vehicle based on a preset frequency, wherein the target vehicle refers to a vehicle to be monitored for the state of the microcontroller chip.

[0029] The preset frequency in the above step is the frequency of the signal acquisition instruction sent in advance, which can represent the time interval of sending the signal acquisition instruction, and is used to periodically send the signal acquisition instruction to the target vehicle. The preset frequency can be determined according to the vehicle type, vehicle model of the target vehicle, or the type and number of microcontroller chips, which is not limited here.

[0030] The signal acquisition instruction in the above step is a command for instructing the target vehicle to collect signals, and collecting signals for the target vehicle can include but is not limited to collecting vehicle state signals or input and output signals of the microcontroller chip, etc. By sending the signal acquisition instruction, real-time state information of the target vehicle can be obtained, so as to perform state recognition and monitoring.

[0031] In an optional embodiment, the signal acquisition instruction can be issued by a cloud server. When setting the preset frequency of sending the signal acquisition instruction, it can be set according to the working characteristics of the microcontroller chip of the target vehicle and the state change frequency of the target vehicle. Generally speaking, when the state of the target vehicle changes frequently, a higher preset frequency can be set to improve the intensity of vehicle state collection, so as to ensure that the state of the vehicle and the working state of the microcontroller chip can be accurately obtained. However, at the same time, the energy consumption and resource consumption need to be considered. If the preset frequency is too high, it will increase the energy consumption and resource consumption of the cloud server. Therefore, the preset frequency and the energy consumption of the system need to be considered, and a suitable preset frequency needs to be selected.

[0032] Then, based on the preset frequency, the cloud server sends a signal acquisition instruction to the target vehicle to ensure that the state of the target vehicle and the working state of the microcontroller chip of the target vehicle are obtained in time and processed and recognized, so as to discover problems of the vehicle microcontroller chip in time and process them, and eliminate potential safety hazards.

[0033] In step S104, at least one vehicle state signal of the target vehicle and the input and output signals of the microcontroller chip on the target vehicle collected based on the signal acquisition instruction are received.

[0034] The vehicle state signal in the above step is a signal that can describe the current state of the vehicle, which can include but is not limited to vehicle speed, acceleration, steering angle, etc.

[0035] The microcontroller chip in the above step is an integrated circuit chip installed on the vehicle, used to control and manage various systems and functions of the vehicle. The microcontroller chip usually includes a processor, memory, input / output interface and other functional modules, which can be used to control the engine, vehicle electronic system, driving assistance system, vehicle entertainment system, etc. The microcontroller chip can be divided into driving assistance chip, vehicle safety chip, vehicle motion chip, entertainment information chip, vehicle body electronic chip, etc. according to function.

[0036] The input and output signals in the above step are signals transmitted between the microcontroller chip and external devices, used to control and monitor the running state of the device, which can include but not limited to sensor data, control instructions, etc.

[0037] In an optional embodiment, based on the signal acquisition instruction, the vehicle state signal of the target vehicle can be acquired, which can include but not limited to vehicle speed, steering angle, engine speed, etc. The input and output signals of the microcontroller chip on the target vehicle can also be acquired, wherein the input signal is from the vehicle sensor and is the vehicle parameter acquired by the vehicle sensor, and the output signal is the signal including the execution instruction after being calculated by the vehicle microcontroller.

[0038] The acquired at least one vehicle state signal of the target vehicle and the input and output signals of the microcontroller chip on the target vehicle are uploaded to the cloud server. The uploading method can be uploading the vehicle state signal and the input and output signal from the vehicle end to the cloud server through the fifth generation mobile communication technology (5G), or uploading the vehicle state signal and the input and output signal from the vehicle end to the cloud server through Bluetooth technology, or uploading the vehicle state signal and the input and output signal from the vehicle end to the cloud server through wireless network (Wi-Fi), but the uploading method is not limited to this.

[0039] The at least one vehicle state signal of the target vehicle and the input and output signals of the microcontroller chip on the target vehicle are received by the cloud server, and the vehicle state signal and the input and output signal are preprocessed, so that the vehicle state signal and the input and output signal can better reflect the state of the vehicle and the working state of the microcontroller chip. When preprocessing, the vehicle state signal and the input and output signal can be filtered to eliminate noise and interference in the vehicle state signal and the input and output signal. The filtering method can use low-pass filtering, high-pass filtering or band-pass filtering, but is not limited to this. Then the weak signal is amplified to strengthen the signal strength, and the sampling rate conversion is determined according to the signal amplification effect, the signal is converted from the original sampling rate to a higher sampling rate, and the number of collected signals is increased.

[0040] The preprocessed vehicle state signal and the input and output signal are stored in a cloud server for further processing and analysis, so as to complete the state monitoring and identification of the vehicle microcontroller chip.

[0041] In step S106, the current vehicle state of the target vehicle is determined based on at least one vehicle state signal.

[0042] The current vehicle state in the above step refers to the overall running state of the target vehicle at the current time, which can be determined by the vehicle state signal. The current vehicle state can be described by the speed of the current vehicle, the steering angle of the current vehicle, or the acceleration of the current vehicle, but is not limited thereto.

[0043] In an optional embodiment, feature extraction can be performed on the vehicle state signal to determine the current vehicle state. In feature extraction, statistical feature extraction, frequency domain feature extraction, or time domain feature extraction can be used, but the extraction method is not limited thereto. After extracting features from the vehicle state signal, a model is established to predict the current vehicle state of the target vehicle. Various machine learning algorithms can be selected when establishing the model, such as support vector machines, decision trees, and deep neural network models, but the application is not limited thereto. The model is trained, and the features extracted from the vehicle state signal are input into the model to obtain the current vehicle state of the target vehicle.

[0044] In step S108, a preset fuzzy rule logic library corresponding to the current vehicle state is called, and the input and output signals and the preset fuzzy rule logic library are used to identify the state of the microcontroller chip to obtain the target working state of the microcontroller chip. The preset fuzzy rule logic library is used to represent the corresponding relationship between the input and output signals and the working state of the chip described by fuzzy semantic logic.

[0045] Considering that the input and output signals of the vehicle microcontroller chip will have great differences when the vehicle is in different running states, it is difficult to determine a unified chip state identification library for accurate state monitoring of the vehicle microcontroller chip. The present application proposes that the current vehicle state of the target vehicle can be determined based on at least one vehicle state signal of the target vehicle, and a preset fuzzy rule logic library corresponding to the current vehicle state of the target vehicle can be called or selected based on the current vehicle state of the target vehicle. Different preset fuzzy rule logic libraries can correspond to different current vehicle states. By determining the current vehicle state first and then calling the corresponding preset fuzzy rule logic library, the determined preset fuzzy rule logic library can respond more quickly to changes in the vehicle state, and can more timely and accurately match the input and output signals of the vehicle microcontroller chip, thereby ensuring the safe and stable operation of the vehicle.

[0046] Considering the limited computing power and storage space of the vehicle end, it is difficult to completely and accurately monitor the state of the vehicle micro control chip by means of the algorithm and data processing capacity of the vehicle micro control chip. Compared with the traditional way of monitoring the state of the vehicle micro control chip, the vehicle micro control chip state monitoring chip proposed in the application can be applied to the cloud server, without the need to additionally set a chip state monitoring chip on the vehicle end, thereby reducing the manufacturing cost of the vehicle. The cloud server can simultaneously monitor the state of multiple micro control chips of a target vehicle or the micro control chips of multiple target vehicles, thereby avoiding the need to update and upgrade the chip state monitoring chip additionally set on each target vehicle. Based on the cloud server, the monitoring can save hardware cost and maintenance cost. Compared with the limited computing power and storage space of the vehicle end, the state monitoring based on the cloud server can provide more functions and services, such as remote diagnosis and remote upgrade, thereby improving the intelligent level of the vehicle.

[0047] The preset fuzzy rule logic library in the above step is a preset fuzzy rule logic library for describing the correspondence between the input and output signals of the micro control chip and the working state of the micro control chip. The preset fuzzy rule logic library has a corresponding relationship with the vehicle state. Different vehicle states correspond to different preset fuzzy rule logic libraries. Using the preset fuzzy rule logic library corresponding to the current vehicle state to process the input and output signals can improve the accuracy of state recognition of the micro control chip. The preset fuzzy rule logic library can be constructed based on a large amount of historical data or according to expert experience, but is not limited thereto.

[0048] The target working state in the above step is the working state of the micro control chip obtained by state recognition of the micro control chip based on the input and output signals and the preset fuzzy rule logic library. The working state of the micro control chip can include, but is not limited to, a normal running state, a preset high-load running state, a fault state, etc. When the target working state is a fault state, the target working state includes fault type information of the micro control chip fault.

[0049] In an optional embodiment, the preset fuzzy rule logic library can be constructed according to a large amount of historical data, wherein the historical data can be historical input and output signals and historical working states of the microcontroller chip, that is, when the microcontroller chip of the vehicle fails in the past, the input and output signals and the working state of the microcontroller chip. The historical data in the preset fuzzy rule logic library can be trained by machine learning to obtain the corresponding relationship between the input and output signals of the microcontroller chip and the working state of the microcontroller chip, and the preset fuzzy rule logic library can be optimized using expert experience, so that the preset fuzzy rule logic library can describe the mapping relationship between the input and output signals and the working state of the microcontroller chip.

[0050] Since the preset fuzzy rule logic library contains a large amount of historical data, and needs to be distinguished according to the vehicle state, different vehicle states correspond to different preset fuzzy rule logic libraries, therefore, the preset fuzzy rule logic library occupies a large storage space, so a cloud server with a large storage space is used to store multiple preset fuzzy rule logic libraries corresponding to multiple vehicle states.

[0051] According to the mapping relationship between the multiple vehicle states and the multiple preset fuzzy rule logic libraries, the preset fuzzy rule logic library corresponding to the current vehicle state is determined from the multiple preset fuzzy rule logic libraries. Then the input and output signals of the microcontroller chip are standardized to convert them into the same dimension or range, so that different types of feature data are comparable, and the processed input and output signals are stored in the memory of the cloud server.

[0052] The processed input and output signals are input into the preset fuzzy rule logic library corresponding to the current vehicle state, and according to the corresponding relationship between the input and output signals and the working state of the microcontroller chip, the target working state of the microcontroller chip is determined.

[0053] In the embodiment of the present application, a vehicle microcontroller chip state monitoring method applied to a cloud server is adopted. A signal acquisition instruction is sent to a target vehicle based on a preset frequency, wherein the target vehicle represents a vehicle to be monitored for microcontroller chip state; at least one vehicle state signal of the target vehicle and an input / output signal of the microcontroller chip on the target vehicle are received based on the signal acquisition instruction; the current vehicle state of the target vehicle is determined based on the at least one vehicle state signal; the preset fuzzy rule logic library corresponding to the current vehicle state is called, and the state of the microcontroller chip is identified based on the input / output signal and the preset fuzzy rule logic library to obtain the target working state of the microcontroller chip, wherein the preset fuzzy rule logic library represents the corresponding relationship between the input / output signal and the working state of the chip described by fuzzy semantic logic. It is easy to note that the cloud server is used to store the preset fuzzy rule logic library corresponding to multiple vehicle states, and the preset fuzzy rule logic library corresponding to the current vehicle state is selected from the multiple preset fuzzy rule logic libraries according to the vehicle state signal. The adaptation degree of the selected preset fuzzy rule logic library to the current vehicle state can be improved, so that when the selected preset fuzzy rule logic library is used to identify the state of the microcontroller chip based on the input / output signal of the microcontroller chip, the problems of the microcontroller chip can be more easily identified, thereby improving the fault identification accuracy of the vehicle microcontroller chip, and further solving the technical problem of low efficiency of monitoring the state of the vehicle microcontroller chip.

[0054] Optionally, the target working state includes fault type information, and the state of the microcontroller chip is identified based on the input / output signal and the preset fuzzy rule logic library to obtain the target working state of the microcontroller chip, including: using a target chip fault identification model to identify the fault of the microcontroller chip based on the preset fuzzy rule logic library and the input / output signal to obtain the fault type information, wherein the target chip fault identification model represents a machine learning model that uses the preset fuzzy rule logic library as a built-in fault identification condition to identify the fault of the microcontroller chip.

[0055] The target chip fault identification model in the above step is a machine learning model that uses the preset fuzzy rule logic library as a built-in fault identification condition to identify the fault of the microcontroller chip. The target chip fault identification model can automatically identify the fault type of the microcontroller chip according to the input / output signal and the preset rule logic library, and give the corresponding diagnosis result.

[0056] The fault type information in the above step is information about the chip fault type obtained during the microcontroller chip fault identification process. The fault type information includes but is not limited to circuit short circuit, circuit open circuit, input and output signal abnormality and other possible fault types of microcontroller chip. By identifying the fault type information, the fault problem of the microcontroller chip can be quickly located and solved, and the stability and reliability of the system can be improved.

[0057] In an optional embodiment, a preset fuzzy rule logic library is built into the target chip fault identification model as a fault identification condition, so that the target chip fault identification model can identify the fault of the microcontroller chip according to the input and output signals. When building the preset fuzzy rule logic library, a programming language can be used to convert the preset fuzzy rule logic library into executable code, integrate the converted code into the code of the target chip fault identification model, ensure that the code can correctly call and execute the preset fuzzy rule logic library, and add logic to the target chip fault identification model to call the preset fuzzy rule logic library for judgment and decision when identifying faults. The preset fuzzy rule logic library built into the target chip fault identification model can also be updated and optimized according to the input and output signals collected during the fault identification process and the fault type of the microcontroller chip, so as to improve the fault identification performance of the target chip fault identification model.

[0058] The target vehicle is equipped with a visualization device. In the case of normal vehicle state, the visualization state remains in the default state. Once the target working state of the microcontroller chip contains fault type information, the fault type information is sent from the cloud server to the target vehicle. Based on the fault type information, the target vehicle visualizes and outputs the vehicle fault state, reminding the driver that the vehicle is in an unsafe state, and taking safety measures according to the fault type information to ensure the safety of the target vehicle and the users inside the vehicle.

[0059] Optionally, the microcontroller chip includes a processor, and the fault type information includes processor fault type information. The target chip fault identification model identifies the fault of the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals to obtain the fault type information, including: obtaining a processor fault rule sub-library in the preset fuzzy rule logic library, wherein the processor fault rule sub-library is used to represent a processor fault signal library established based on processor historical abnormal signals; filtering the input and output signals using the processor fault rule sub-library to obtain processor abnormal signals; identifying the fault of the microcontroller chip based on the preset safety threshold and the processor abnormal signals to obtain the processor fault type information, wherein the preset safety threshold is used to represent a feasible domain threshold of the processor input and output signals.

[0060] The processor in the above step is a part of the microcontroller chip, which is used to execute instructions and process data.

[0061] The processor abnormal signal in the above step is an abnormal signal obtained by screening the input and output signals according to the processor fault rule sub-library, which can help identify whether the processor in the microcontroller chip has failed.

[0062] The preset safety threshold in the above step is a feasible domain threshold of the processor input and output signal, and when the processor abnormal signal exceeds the preset safety threshold, it can indicate that the processor in the microcontroller chip has failed.

[0063] The processor fault type information in the above step is information obtained by identifying the fault of the microcontroller chip based on the preset safety threshold and the processor abnormal signal, which describes the specific fault type of the processor in the microcontroller chip.

[0064] In an optional embodiment, the processor fault rule sub-library in the preset fuzzy rule logic library is created, the rules and signal definitions in the processor fault rule sub-library are determined according to the multiple fault types of the processor and the input and output signals corresponding to the fault types, that is, the processor historical abnormal signals, and the screening algorithm in the processor fault rule sub-library is obtained by machine learning training, so that the processor fault rule sub-library can screen the signals suspected to represent the processor abnormality from the input and output signals.

[0065] The processor fault rule sub-library is selected from the preset fuzzy rule logic library, and the processor fault rule sub-library is used to confirm whether the microcontroller chip has a processor fault. The input and output signals are input into the processor fault rule sub-library, and the processor abnormal signal suspected to represent the processor abnormality is screened out. Then the processor abnormal signal is further confirmed, the preset safety threshold is used to confirm whether the processor really has a fault, and the processor fault type information is obtained.

[0066] In the fault identification of the microcontroller chip based on the preset safety threshold and the processor abnormal signal, the processor abnormal signal is compared with the preset safety threshold, and if the processor abnormal signal exceeds the preset safety threshold, it indicates that the processor in the microcontroller chip has failed, and the processor fault type information is obtained from the processor abnormal signal.

[0067] Optionally, the microcontroller chip comprises a storage unit, and the fault type information comprises storage unit fault type information; and the fault identification of the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals to obtain the fault type information comprises: obtaining a storage unit fault rule sub-library in the preset fuzzy rule logic library, wherein the storage unit fault rule sub-library is used to represent a storage unit fault signal library established based on storage unit historical abnormal signals; screening the input and output signals by using the storage unit fault rule sub-library to obtain storage unit abnormal signals; obtaining a signal response duration of the storage unit abnormal signals, wherein the signal response duration is used to represent a duration between a first input signal input to the storage unit and a first response signal output by the storage unit, and the first input signal is used to represent a storage unit input signal in the storage unit abnormal signals; and identifying the fault of the microcontroller chip based on the signal response duration to obtain the storage unit fault type information.

[0068] The storage unit in the above steps refers to a unit for storing data in the microcontroller chip, and the storage unit can include but is not limited to a register, a cache, etc.

[0069] The storage unit fault type information in the above steps refers to information of a fault type generated by the storage unit when a fault occurs, and can include but is not limited to storage unit read / write abnormality, storage unit data damage, etc.

[0070] The storage unit abnormal signal in the above steps is an abnormal signal obtained by screening the input and output signals according to the storage unit fault rule sub-library, which can help identify whether the storage unit in the microcontroller chip has a fault.

[0071] The signal response duration in the above steps refers to a time interval experienced by the storage unit from receiving an input signal to outputting a response signal, and is used to represent a response speed and a state of the storage unit.

[0072] The first response signal in the above steps is a response signal output by the storage unit after the first input signal is input to the storage unit.

[0073] In an optional embodiment, the storage unit fault rule sub-library in the preset fuzzy rule logic library is created, the rules and signal definitions in the storage unit fault rule sub-library are determined according to a plurality of fault types of the storage unit and input and output signals corresponding to the fault types, i.e., storage unit historical abnormal signals, and a screening algorithm in the storage unit fault rule sub-library is obtained by machine learning training, so that the storage unit fault rule sub-library can screen out signals suspected to represent storage unit abnormalities, i.e., storage unit abnormal signals, from the input and output signals.

[0074] The storage unit fault rule sub-library is selected from the preset fuzzy rule logic library, and the storage unit fault rule sub-library is used to confirm whether the storage unit of the microcontroller chip has a fault. The input and output signals are input into the storage unit fault rule sub-library, and a storage unit abnormal signal suspected of indicating a storage unit abnormality is screened out. Then, the storage unit abnormal signal is further confirmed, and whether the storage unit has a fault is confirmed by using the signal response duration, and storage unit fault type information is obtained.

[0075] When confirming whether the storage unit has a fault by using the signal response duration, since the input signal and the output signal of the storage unit will have response delay, response error, or be unable to respond when the storage unit has a fault, the fault state of the storage unit in the microcontroller chip is determined according to the signal response duration of the storage unit abnormal signal. The duration from when the storage unit abnormal signal is input from the first input signal to when the first response signal of the storage unit is output is obtained as the signal response duration, which is compared with a standard signal response duration to determine whether response delay, response error, or being unable to respond occurs. If so, it indicates that the storage unit in the microcontroller chip has a fault, and storage unit fault type information is obtained from the storage unit abnormal signal.

[0076] Optionally, the microcontroller chip includes a peripheral device, and the fault type information includes peripheral device fault type information. The target chip fault identification model is used to identify a fault of the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals to obtain the fault type information, including: obtaining a multi-modal fault rule sub-library in the preset fuzzy rule logic library, where the multi-modal fault rule sub-library is used to represent a peripheral device fault signal library established based on a peripheral device historical abnormal signal; screening the input and output signals by using the multi-modal fault rule sub-library to obtain a peripheral device abnormal signal; and identifying a fault of the microcontroller chip based on the peripheral device abnormal signal to obtain the peripheral device fault type information.

[0077] The peripheral device in the above steps refers to an external device connected to the microcontroller chip, which is other components of the microcontroller chip except for the processor and the memory, including but not limited to a sensor, an actuator, a communication module, a power supply, a bus, a clock, a serial communication, a reset element, etc., and is used to input and output signals to the microcontroller chip or perform a specific function.

[0078] The peripheral device fault type information in the above steps refers to various fault types that the peripheral device can have, including but not limited to open circuit, short circuit, failure, etc., and is used to identify a fault condition of the peripheral device.

[0079] The peripheral device fault signal library in the above step is a library established based on peripheral device historical abnormal signals, containing various abnormal signals that the peripheral device can have, and is used to identify the fault type of the peripheral device.

[0080] The peripheral device abnormal signal in the above step refers to an abnormal signal related to the peripheral device, and is also a signal identified as a suspected abnormal signal after comparison and screening with the multi-modal fault rule sub-library in the preset fuzzy rule logic library. The peripheral device abnormal signal can indicate that the peripheral device has a suspected fault, which needs to be further diagnosed and repaired.

[0081] In an optional embodiment, the multi-modal fault rule sub-library in the preset fuzzy rule logic library is created, the rules and signal definitions in the peripheral device fault rule sub-library are determined according to the multiple fault types of the peripheral device and the input and output signals corresponding to the fault types, i.e. the historical abnormal signals of the peripheral device, and the screening algorithm in the multi-modal fault rule sub-library is obtained through machine learning training, so that the multi-modal fault rule sub-library can screen out signals suspected to represent peripheral device abnormalities, i.e. peripheral device abnormal signals, from the input and output signals.

[0082] The multi-modal fault rule sub-library is selected from the preset fuzzy rule logic library, and the multi-modal fault rule sub-library is used to confirm whether the microcontroller chip has a peripheral fault. The input and output signals are input into the multi-modal fault rule sub-library, and the peripheral device abnormal signals suspected to represent peripheral device abnormalities are screened out. Then the peripheral device abnormal signals are further confirmed, the microcontroller chip is fault-identified based on the peripheral device abnormal signals, and the storage unit fault type information is obtained.

[0083] Optionally, the microcontroller chip is fault-identified based on the peripheral device abnormal signals, and the peripheral device fault type information is obtained, including: obtaining the signal transmission interruption times, signal transmission error rate and signal timing error of the peripheral device abnormal signal; fault-identifying the microcontroller chip based on the signal transmission interruption times to obtain power unit fault information; fault-identifying the microcontroller chip based on the signal transmission error rate to obtain bus fault information; fault-identifying the microcontroller chip based on the signal timing error to obtain clock fault information; and determining the peripheral device fault type information based on the power unit fault information, bus fault information and clock fault information.

[0084] The signal transmission interruption times in the above step refer to the number of interruptions occurring during signal transmission, indicating the frequency of interruptions of the peripheral device abnormal signal during transmission.

[0085] The signal transmission error rate in the above step refers to the ratio of errors occurring during signal transmission, indicating the probability of errors of the peripheral device abnormal signal during transmission.

[0086] The signal timing error in the above step refers to the timing deviation of the signal in the signal transmission process, indicating that the peripheral device abnormal signal has a timing deviation in the transmission.

[0087] The power unit failure information in the above step refers to the information of the power unit failure in the microcontroller chip, which may cause an increase in the number of signal transmission interruptions of the peripheral device abnormal signal.

[0088] The bus failure information in the above step refers to the information of the bus failure in the microcontroller chip, which may cause an increase in the error rate of the peripheral device abnormal signal transmission.

[0089] The clock failure information in the above step refers to the information of the clock failure in the microcontroller chip, which may cause an increase in the signal timing error of the peripheral device abnormal signal transmission.

[0090] In an optional embodiment, when obtaining the number of signal transmission interruptions, the signal transmission error rate and the signal timing error of the peripheral device abnormal signal, a monitoring tool can be used to obtain, or the log file of the peripheral device can be analyzed to obtain, or a test instrument can be used for testing, but the way of obtaining the number of signal transmission interruptions, the signal transmission error rate and the signal timing error is not limited thereto.

[0091] The power failure in the peripheral device abnormality will affect the generation, amplification and transmission of the input signal and the output signal of the vehicle microcontroller, and in severe cases, the signal transmission will be interrupted. Therefore, based on the number of signal transmission interruptions, the microcontroller chip is identified for failure, and when the number of signal transmission interruptions is greater than a preset number, it is determined that the peripheral device failure type is a power unit failure, and the power unit failure information is obtained from the peripheral device abnormal signal. It should be noted that the preset number can be preset according to the specific application, and the specific value of the preset number is not limited herein.

[0092] The bus failure in the peripheral device abnormality will cause the input signal and the output signal of the vehicle microcontroller to be disturbed and chaotic, and in severe cases, the signal transmission will be erroneous. Therefore, based on the signal transmission error rate, the microcontroller chip is identified for failure, and when the signal transmission error rate is greater than a preset probability, it is determined that the peripheral device failure type is a bus failure, and the bus failure information is obtained from the peripheral device abnormal signal. It should be noted that the preset probability can be preset according to the specific application, and the specific value of the preset probability is not limited herein.

[0093] The clock failure in the peripheral device exception can cause the vehicle microcontroller input signal and output signal timing error, and in a serious case, the signal transmission is unresponsive. Therefore, the microcontroller chip is identified based on the signal timing error. When the signal timing error is greater than the preset error, it is determined that the peripheral device failure type is clock failure, and the clock failure information is obtained from the peripheral device exception signal. It should be noted that the preset error can be preset according to the specific application, and the specific value of the preset error is not limited here.

[0094] Optionally, receiving the at least one vehicle state signal of the target vehicle and the input and output signals of the microcontroller chip on the target vehicle includes: receiving initial input and output signals of the microcontroller chip, wherein the initial input and output signals are used to represent the input and / or output signals of the microcontroller chip directly received; and performing feature extraction on the initial input and output signals based on preset signal features to obtain the input and output signals, wherein the preset signal features at least include one of the following: waveform features, frequency features, and amplitude features.

[0095] The initial input and output signals in the above steps are the input and / or output signals of the microcontroller chip directly received, that is, the original signals without processing or feature extraction, which can be used to obtain the input and output signals.

[0096] The preset signal features in the above steps refer to some feature parameters determined in advance, which are used for feature extraction and analysis of the initial input and output signals to obtain the input and output signals. The preset signal features can include but are not limited to waveform features, frequency features, and amplitude features. The waveform features can be waveform shape or waveform period, but are not limited thereto. The frequency features can be signal frequency or frequency spectrum distribution, but are not limited thereto. The amplitude features can be signal amplitude or peak value, but are not limited thereto.

[0097] In an optional embodiment, the initial input and output signals of the microcontroller chip received can be various forms of electrical signals, which can be digital signals or analog signals, but are not limited thereto. The initial input signal can include the input signal of the microcontroller chip from an external sensor or other device, and the initial output signal can be the control signal output by the microcontroller chip. In the feature extraction stage, the initial input and output signals can be analyzed based on the waveform features, frequency features, and amplitude features using signal processing techniques.

[0098] When extracting waveform features, the shape and fluctuation of the signal can be described by calculating waveform features such as peak value, mean value, and variance. Time-domain analysis methods, such as Fourier transform and wavelet transform, can then be used to extract these features, although the methods are not limited to these. Similarly, when extracting frequency features, the frequency distribution of the signal can be described by calculating frequency features such as spectral energy, peak value, and bandwidth. Frequency-domain analysis methods, such as Fast Fourier Transform (FFT), can then be used to extract these features, although the methods are not limited to these. Likewise, when extracting amplitude features, the magnitude and variation of the signal's amplitude can be described by calculating amplitude features such as maximum amplitude, minimum amplitude, and mean amplitude. Amplitude analysis methods, such as envelope analysis and peak detection, can then be used to extract these features, although the methods are not limited to these. After extracting the features of the initial input and output signals, the extracted signal features constitute the input and output signals.

[0099] The following description uses a preferred embodiment. Figure 2 This is a flowchart of an optional vehicle microcontroller chip state monitoring method according to an embodiment of the present invention, such as... Figure 2 As shown, firstly, based on cloud-based signal acquisition, the vehicle status signals of the target vehicle and the initial input / output signals of the microcontroller chip on the target vehicle are acquired according to signal acquisition commands. Then, the signals are processed modularly, preprocessing the initial input / output signals. The preprocessing process includes filtering, signal amplification, sampling rate conversion, feature extraction, and data standardization. Afterward, the preprocessed input / output data is stored and transmitted to a fuzzy logic database for status monitoring. An adaptive fuzzy logic database is then established, which is the preset fuzzy rule logic library mentioned above. During the establishment of the fuzzy logic database, machine learning processing is performed on the vehicle safety data to obtain processor fault sub-libraries, memory fault sub-libraries, and multimodal fault sub-libraries, which are also the processor fault rule sub-libraries, storage unit fault rule sub-libraries, and multimodal fault rule sub-libraries mentioned above. Finally, the established fuzzy logic database is used to identify the input / output signals, monitoring whether the microcontroller chip stores faults. If a fault exists, the fault status is visualized and output.

[0100] Figure 3 This is a flowchart illustrating the interaction between the vehicle and the cloud server during an optional status monitoring process according to an embodiment of the present invention, such as... Figure 3As shown, the cloud service performs machine learning processing on the vehicle safety data, constructs a fuzzy logic rule library, i.e., the preset fuzzy rule logic library mentioned above. Then cloud signal collection is performed, i.e., the initial input and output signals of the vehicle micro control chip at the vehicle end are obtained, the vehicle micro control chip at the vehicle end uploads the initial input and output signals to the cloud server, the cloud server module processes the initial input and output signals, sends the obtained input and output signals to the fuzzy logic rule library, uses the fuzzy logic rule library to identify the input and output signals, if a fault is identified in the vehicle micro control chip, sends the obtained fault information to the vehicle end, and the vehicle end visually outputs the fault state to inform the driver of the current fault and fault state of the vehicle micro control chip.

[0101] Embodiment 2

[0102] According to an embodiment of the present application, an embodiment of a vehicle remote login verification device is provided, which can perform the vehicle micro controller chip state monitoring method provided in Embodiment 1 described above, and the specific implementation and preferred application scenarios are the same as those of Embodiment 1, which will not be repeated here.

[0103] Figure 4 is a schematic diagram of a vehicle micro controller chip state monitoring device according to an embodiment of the present application, as shown in Figure 4

[0104] The acquisition module 40 is configured to send a signal acquisition instruction to a target vehicle based on a preset frequency, wherein the target vehicle refers to a vehicle to be monitored for the state of the micro controller chip.

[0105] The receiving module 42 is configured to receive at least one vehicle state signal of the target vehicle and an input and output signal of the micro controller chip on the target vehicle based on the signal acquisition instruction.

[0106] The determination module 44 is configured to determine a current vehicle state of the target vehicle based on the at least one vehicle state signal.

[0107] The calling module 46 is configured to call a preset fuzzy rule logic library corresponding to the current vehicle state, and perform state identification on the micro controller chip based on the input and output signal and the preset fuzzy rule logic library, to obtain a target working state of the micro controller chip, wherein the preset fuzzy rule logic library refers to a corresponding relationship between the input and output signals and the working state of the chip described by fuzzy semantic logic.

[0108] ​Optionally, the calling module comprises an identifying unit configured to identify the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals to obtain fault type information, wherein the target chip fault identification model is used to represent a machine learning model for identifying the microcontroller chip based on the preset fuzzy rule logic library as a built-in fault identification condition.

[0109] Optionally, the identifying unit is further configured to obtain a processor fault rule sub-library in the preset fuzzy rule logic library, wherein the processor fault rule sub-library is used to represent a processor fault signal library established based on processor historical abnormal signals; filter the input and output signals based on the processor fault rule sub-library to obtain processor abnormal signals; and identify the microcontroller chip based on a preset safety threshold and the processor abnormal signals to obtain processor fault type information, wherein the preset safety threshold is used to represent a feasible domain threshold of the processor input and output signals.

[0110] Optionally, the identifying unit is further configured to obtain a storage unit fault rule sub-library in the preset fuzzy rule logic library, wherein the storage unit fault rule sub-library is used to represent a storage unit fault signal library established based on storage unit historical abnormal signals; filter the input and output signals based on the storage unit fault rule sub-library to obtain storage unit abnormal signals; obtain a signal response duration of the storage unit abnormal signals, wherein the signal response duration is used to represent a duration between a first input signal input to the storage unit and a first response signal output by the storage unit, and the first input signal is used to represent a storage unit input signal in the storage unit abnormal signals; and identify the microcontroller chip based on the signal response duration to obtain storage unit fault type information.

[0111] Optionally, the identifying unit is further configured to obtain a multi-modal fault rule sub-library in the preset fuzzy rule logic library, wherein the multi-modal fault rule sub-library is used to represent a peripheral device fault signal library established based on peripheral device historical abnormal signals; filter the input and output signals based on the multi-modal fault rule sub-library to obtain peripheral device abnormal signals; and identify the microcontroller chip based on the peripheral device abnormal signals to obtain peripheral device fault type information.

[0112] Optionally, the identifying unit is further configured to obtain a signal transmission interruption frequency, a signal transmission error rate, and a signal timing error of the peripheral device abnormal signals; identify the microcontroller chip based on the signal transmission interruption frequency to obtain power unit fault information; identify the microcontroller chip based on the signal transmission error rate to obtain bus fault information; identify the microcontroller chip based on the signal timing error to obtain clock fault information; and determine the peripheral device fault type information based on the power unit fault information, the bus fault information, and the clock fault information.

[0113] Optionally, the receiving module comprises: a receiving unit, configured to receive an initial input / output signal of the microcontroller chip, wherein the initial input / output signal is used to represent an input signal and / or an output signal of the microcontroller chip received directly; and an extracting unit, configured to perform feature extraction on the initial input / output signal based on preset signal features to obtain the input / output signal, wherein the preset signal features at least include one of the following: waveform features, frequency features and amplitude features.

[0114] Embodiment 3

[0115] According to the embodiments of the present application, an electronic device is further provided, comprising: a memory storing an executable program; and a processor configured to run the program, wherein the program is configured to perform the state monitoring method of the vehicle microcontroller chip in the embodiment 1 when running.

[0116] Embodiment 4

[0117] According to the embodiments of the present application, a computer readable storage medium is further provided, comprising a stored executable program, wherein the computer readable storage medium is configured to control a device where the computer readable storage medium is located to perform the state monitoring method of the vehicle microcontroller chip in the embodiments of the present application when the executable program is running.

[0118] Embodiment 5

[0119] According to the embodiments of the present application, a computer program product is further provided, comprising a computer program, wherein the computer program is configured to implement the state monitoring method of the vehicle microcontroller chip in the embodiments of the present application when executed by a processor.

[0120] Embodiment 6

[0121] According to the embodiments of the present application, a computer program product is further provided, comprising a non-volatile computer readable storage medium, wherein the non-volatile computer readable storage medium is configured to store a computer program, and the computer program is configured to implement the state monitoring method of the vehicle microcontroller chip in the embodiments of the present application when executed by a processor.

[0122] The above-mentioned serial numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0123] In the above-mentioned embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0124] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented by other means. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division mode, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0125] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0126] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0127] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0128] The above is only the preferred embodiment of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method of state monitoring of a vehicle microcontroller chip, characterized by, The application is applied to a cloud server, and comprises: sending a signal collection instruction based on a preset frequency to a target vehicle, wherein the target vehicle represents a vehicle to be monitored by a microcontroller chip; receiving at least one vehicle state signal of the target vehicle collected based on the signal collection instruction and an input / output signal of the microcontroller chip on the target vehicle; determining a current vehicle state of the target vehicle based on the at least one vehicle state signal; calling a preset fuzzy rule logic library corresponding to the current vehicle state, and performing state recognition on the microcontroller chip based on the input / output signal and the preset fuzzy rule logic library to obtain a target working state of the microcontroller chip, wherein the preset fuzzy rule logic library represents a corresponding relationship between input / output signals and working states of the chip described by fuzzy semantic logic; wherein the target working state comprises fault type information, and the state recognition on the microcontroller chip based on the input / output signal and the preset fuzzy rule logic library to obtain the target working state of the microcontroller chip comprises: performing fault recognition on the microcontroller chip based on the preset fuzzy rule logic library and the input / output signal by using a target chip fault recognition model, to obtain the fault type information, wherein the target chip fault recognition model represents a machine learning model for performing fault recognition on the microcontroller chip by taking the preset fuzzy rule logic library as a built-in fault recognition condition; the microcontroller chip comprises a processor, the fault type information comprises processor fault type information, and the fault recognition on the microcontroller chip based on the preset fuzzy rule logic library and the input / output signal by using the target chip fault recognition model to obtain the fault type information comprises: obtaining a processor fault rule sub-library in the preset fuzzy rule logic library, wherein the processor fault rule sub-library represents a processor fault signal library established based on processor historical abnormal signals; performing screening on the input / output signal by using the processor fault rule sub-library to obtain processor abnormal signals; and performing fault recognition on the microcontroller chip based on a preset safety threshold and the processor abnormal signals to obtain the processor fault type information, wherein the preset safety threshold represents a feasible domain threshold of processor input / output signals preset in advance.

2. The method of claim 1, wherein, the microcontroller chip comprises a storage unit, the fault type information comprises storage unit fault type information, and the fault recognition on the microcontroller chip based on the preset fuzzy rule logic library and the input / output signal by using the target chip fault recognition model to obtain the fault type information comprises: obtaining a storage unit fault rule sub-library in the preset fuzzy rule logic library, wherein the storage unit fault rule sub-library represents a storage memory fault signal library established based on storage unit historical abnormal signals; performing screening on the input / output signal by using the storage unit fault rule sub-library to obtain storage unit abnormal signals; and acquire a signal response duration of the storage unit abnormal signal, wherein the signal response duration is used to represent a duration between input of a first input signal into the storage unit and output of a first response signal from the storage unit, and the first input signal is used to represent a storage unit input signal in the storage unit abnormal signal; perform fault identification on the microcontroller chip based on the signal response duration to obtain the storage unit fault type information.

3. The method of claim 1, wherein, The microcontroller chip includes a peripheral device, and the fault type information includes peripheral device fault type information. The fault identification model of the target chip is used to perform fault identification on the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals to obtain the fault type information, including: acquire a multi-modal fault rule sub-library in the preset fuzzy rule logic library, wherein the multi-modal fault rule sub-library is used to represent a peripheral device fault signal library established based on a peripheral device historical abnormal signal; filter the input and output signals based on the multi-modal fault rule sub-library to obtain a peripheral device abnormal signal; perform fault identification on the microcontroller chip based on the peripheral device abnormal signal to obtain the peripheral device fault type information.

4. The method of claim 3, wherein, Performing fault identification on the microcontroller chip based on the peripheral device abnormal signal to obtain the peripheral device fault type information includes: acquiring a signal transmission interruption frequency, a signal transmission error rate, and a signal timing error of the peripheral device abnormal signal; performing fault identification on the microcontroller chip based on the signal transmission interruption frequency to obtain power unit fault information; performing fault identification on the microcontroller chip based on the signal transmission error rate to obtain bus fault information; performing fault identification on the microcontroller chip based on the signal timing error to obtain clock fault information; determining the peripheral device fault type information based on the power unit fault information, the bus fault information, and the clock fault information.

5. The method of claim 1, wherein, receive at least one vehicle state signal of the target vehicle and input and output signals of the microcontroller chip on the target vehicle, including: receive initial input and output signals of the microcontroller chip, wherein the initial input and output signals are used to represent input signals and / or output signals of the microcontroller chip received directly; extract features of the initial input and output signals based on preset signal features to obtain the input and output signals, wherein the preset signal features at least include one of the following: waveform features, frequency features, and amplitude features.

6. A device for monitoring the state of a vehicle microcontroller chip for implementing the method for monitoring the state of a vehicle microcontroller chip as claimed in claim 1, characterized in that including: The acquisition module is configured to send a signal acquisition instruction to a target vehicle based on a preset frequency, wherein the target vehicle is used to represent a vehicle to be monitored for a microcontroller chip state. The receiving module is configured to receive at least one vehicle state signal of the target vehicle and input and output signals of the microcontroller chip on the target vehicle based on the signal acquisition instruction. The determination module is configured to determine a current vehicle state of the target vehicle based on the at least one vehicle state signal. The calling module is configured to call a preset fuzzy rule logic library corresponding to the current vehicle state, and perform state recognition on the microcontroller chip based on the input and output signals and the preset fuzzy rule logic library to obtain a target working state of the microcontroller chip, wherein the preset fuzzy rule logic library is used to represent a corresponding relationship between input and output signals and working states of the chip described by fuzzy semantic logic. The target working state includes fault type information, and the calling module is further configured to perform fault recognition on the microcontroller chip based on the preset fuzzy rule logic library and the input and output signals by using a target chip fault recognition model to obtain the fault type information, wherein the target chip fault recognition model is used to represent a machine learning model for performing fault recognition on the microcontroller chip by taking the preset fuzzy rule logic library as a built-in fault recognition condition. The microcontroller chip includes a processor, and the fault type information includes processor fault type information. The calling module is further configured to obtain a processor fault rule sub-library in the preset fuzzy rule logic library, wherein the processor fault rule sub-library is used to represent a processor fault signal library established based on processor historical abnormal signals. The calling module is further configured to filter the input and output signals by using the processor fault rule sub-library to obtain processor abnormal signals, and perform fault recognition on the microcontroller chip based on a preset safety threshold and the processor abnormal signals to obtain the processor fault type information, wherein the preset safety threshold is used to represent a feasible domain threshold of processor input and output signals that is preset in advance.

7. An electronic device, comprising: The computer readable storage medium includes a stored executable program, wherein the executable program, when executed, controls a device where the storage medium is located to perform the state monitoring method of the vehicle microcontroller chip according to any one of claims 1 to 5. The computer readable storage medium includes a stored executable program, wherein the executable program, when executed, controls a device where the storage medium is located to perform the state monitoring method of the vehicle microcontroller chip according to any one of claims 1 to 5. The computer readable storage medium includes a stored executable program, wherein the executable program, when executed, controls a device where the storage medium is located to perform the state monitoring method of the vehicle microcontroller chip according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium includes a stored executable program, wherein the executable program, when executed, controls a device where the storage medium is located to perform the state monitoring method of the vehicle microcontroller chip according to any one of claims 1 to 5.

9. A computer program product, characterised in that, ​

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