Data security storage method and system based on emergency power failure of vehicle-mounted network engine terminal

Abstract

The invention provides a data security storage method and system based on emergency power failure of a vehicle-mounted network engine terminal, and the key point of the technical scheme comprises the steps: obtaining historical normal data, and setting each threshold parameter; detecting various vehicle information in real time, and obtaining the necessity of reordering at the current moment; when the necessity of reordering is smaller than a set threshold value, the priority ordering code at the current moment is not changed; when the reordering necessity is greater than or equal to a set threshold value, reordering the priorities of the vehicle data to generate a new priority ordering code; triggering a data protection mechanism in response to the condition that the necessity of reordering is greater than or equal to a set threshold value or the vehicle power supply is abnormal, and sequentially storing various vehicle information data according to the priority sequence of the ordering codes at the current moment; according to the method, dynamic rapid priority ranking can be achieved, the storage efficiency of key data is improved, and it is ensured that abnormal data can be stored preferentially.

Description

Technical Field

[0001] The present invention relates to the technical field of data storage of in-vehicle network engine terminals, and particularly relates to a data security storage method and system based on emergency power-off of in-vehicle network engine terminals. Background Art

[0002] With the rapid development of intelligent connected vehicles, in-vehicle terminal systems play an increasingly important role, involving not only functions such as navigation and entertainment, but also key tasks such as vehicle status monitoring and safety warning. However, in the event of a vehicle accident, battery failure, or extreme environment leading to abnormal or emergency power-off of the vehicle power system, important data in the in-vehicle terminal, such as vehicle information data like driving records and fault logs, faces the risk of loss, which not only affects subsequent accident analysis and vehicle maintenance, but may also be involved in the determination of legal liability.

[0003] For vehicles with abnormal or emergency power-off of the vehicle power system due to sudden situations, compared with the vehicle information in the normal state, the key sensor data with higher abnormal values is very important for subsequent vehicle fault or accident analysis. However, due to the existing way of storing data in in-vehicle network engine terminals, which often stores various vehicle information data in sequence according to a set order, the priority of each data is fixed, and it is impossible to preferentially store the key sensor data with higher abnormal values according to the actual situation of the vehicle. In the case of abnormal or sudden power-off of the vehicle power system, it is difficult to quickly store and save the key abnormal vehicle information data in a timely manner, which is likely to cause the loss of important abnormal data and have an adverse impact on subsequent vehicle fault or accident analysis. Therefore, it is particularly important to develop a technical solution that can effectively protect the key in-vehicle network engine terminal data with higher abnormal values in the event of abnormal or emergency power-off of the vehicle power system. Summary of the Invention

[0004] In order to ensure that at the moment of abnormal or emergency power-off of the vehicle power system, the key data with higher abnormal values in the in-vehicle network engine terminal is preferentially, quickly, and completely saved to the non-volatile memory to avoid the loss of important data, the present invention provides a data security storage method and system based on emergency power-off of in-vehicle network engine terminals.

[0005] In the first aspect, the present invention provides a data security storage method based on emergency power-off of in-vehicle network engine terminals, and its technical solution is as follows: A data security storage method based on emergency power-off of in-vehicle network engine terminals, the steps of which include: Obtain historical normal data and set various threshold parameters; detect various vehicle information in real time, obtain outliers, and calculate the necessity of reordering at the current moment; when the necessity of reordering is less than the set threshold, the priority sorting code at the current moment remains unchanged; when the necessity of reordering is greater than or equal to the set threshold, reorder the priority of vehicle data to generate a new priority sorting code; in response to the necessity of reordering being greater than or equal to the set threshold or the vehicle power being abnormal, trigger the data protection mechanism; in response to the data protection mechanism being triggered, store each vehicle information data in sequence according to the priority order of the sorting code at the current moment.

[0006] Preferably, the obtaining historical normal data and setting various threshold parameters includes: obtaining various vehicle information data in the normal state, setting the threshold parameters corresponding to various vehicle information respectively according to the historical normal data, and numbering various vehicle information and the sensors corresponding to various vehicle information from 1 to N according to the urgency of troubleshooting vehicle faults for various vehicle information.

[0007] Preferably, the detecting various vehicle information in real time includes: detecting and receiving various vehicle information at the current moment and classifying them into the corresponding numbers respectively, and the corresponding sensor devices on the vehicle detect and collect various vehicle information at the current moment in real time to obtain multi-dimensional acquisition data, and the data collected by the sensors are associated with the numbers of the sensors respectively.

[0008] Preferably, based on the multi-dimensional acquisition data, obtaining the outliers of various vehicle information at the current moment includes: using a neural network algorithm or a machine learning algorithm to perform outlier detection and analysis on each sensing information data to obtain the outliers of various vehicle information at the current moment; calculating the ratio of the outliers of various vehicle information to the corresponding threshold parameters respectively to normalize the outlier data and obtain the normalized outlier feature values.

[0009] Preferably, based on the outlier feature values, obtaining the necessity of reordering at the current moment includes: at the first moment, sorting the priority of vehicle information in descending order of the sensor outlier feature values; starting from the second moment, calculating the change amount of the outlier feature value of each sensor and performing a positive relationship mapping as the weight coefficient, and taking the product of the outlier feature value of the sensor at the current moment and the corresponding weight coefficient as the sorting necessity of the sensor at the current moment; calculating the ratio of the priority ranking number of the sensor corresponding to the maximum sorting necessity at the current moment at the previous moment to the total number of sensors; taking the product of the maximum value of the sorting necessity of all sensors at the current moment and the ratio as the necessity of reordering at the current moment.

[0010] Preferably, based on the necessity of reordering at the current moment, it is determined whether to change the priority arrangement order of each vehicle information, including: setting a threshold according to the actual vehicle condition. When the necessity of reordering is less than the set threshold, it means that priority reordering is not required at the current moment, and the sorting code at the current moment is the same as that at the previous moment before the current moment. When the necessity of reordering is greater than or equal to the set threshold, it means that priority reordering is required at the current moment.

[0011] Preferably, based on the necessity of reordering being greater than or equal to the set threshold, the priority of vehicle data is reordered, including: calculating the difference between the abnormal eigenvalue of the sensor with an increasing abnormal eigenvalue and the abnormal eigenvalue of the sensor with a previous arrangement serial number; taking the sum of the product of the sorting necessity corresponding to the current sensor and the change amount of the abnormal eigenvalue and the abnormal eigenvalue difference as the insertion necessity of the priority of the current sensor in the insertion sorting process.

[0012] Preferably, based on the insertion necessity of the sensor priority, the priority arrangement order of each sensor data is determined in sequence, including: calculating the insertion necessity corresponding to the sensor with an increasing abnormal eigenvalue and the sensor with a previous arrangement serial number in sequence from front to back according to the arrangement serial number of the priority at the previous moment before the current moment, and comparing with the set threshold in sequence. When the insertion necessity is less than or equal to the set threshold, it means that the priority of the current sensor does not need to be inserted before the corresponding sensor. When the insertion necessity is greater than the set threshold, it means that the priority of the current sensor needs to be inserted before the corresponding sensor, so as to determine the sorting position of the current sensor; until the sorting of all sensors with increasing abnormal eigenvalues is completed, a new priority sorting code is generated.

[0013] In a second aspect, the present invention provides a data security storage system based on the emergency power-off of an in-vehicle network engine terminal, and its technical solution is as follows: A data security storage system based on the emergency power-off of an in-vehicle network engine terminal, used to run and implement the above data security storage method, and its hardware structure includes: one or more processors for running computing programs, a data cache register for caching each vehicle information, a hard disk memory for storing each vehicle information for a long time, and a backup power supply for supplying power to the system in an emergency when the vehicle power system is abnormal. The processor is electrically connected to the data cache register, the hard disk memory, and the backup power supply respectively. The data cache register is electrically connected to the data cache device of the in-vehicle network engine terminal and various associated sensor devices through a communication bus.

[0014] Preferably, the data security storage system can be directly embedded and integrated into the existing vehicle network engine terminal. The processor, the data cache register, and the hard disk memory are respectively the processor, the data cache device, and the memory of the vehicle network engine terminal, and the backup power supply is the battery of the vehicle network engine terminal or an additionally provided power supply path.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. A data security storage method based on emergency power-off of a vehicle network engine terminal according to the present invention, by realizing the dynamic and rapid sorting of the priorities of various vehicle information, improves the data storage efficiency while ensuring that abnormal data can be preferentially stored. At the moment when the vehicle power supply system is abnormal or there is an emergency power-off, the key data with a higher abnormal value in the vehicle network engine terminal is preferentially, rapidly, and completely saved to a safe memory to avoid the loss of important data, which is beneficial to data restoration in abnormal situations, thereby providing strong guarantee for subsequent vehicle fault or accident analysis and other situations.

[0016] 2. A data security storage system based on emergency power-off of a vehicle network engine terminal according to the present invention can be designed as an independent storage device, communicate with the vehicle network engine terminal for data and power connection through a data line, and can also be directly embedded and integrated into the existing vehicle network engine terminal. Moreover, it is provided with a backup power supply and can form a dual-power supply system with the normal power supply circuit system, so as to ensure that in the extreme case where the vehicle power supply system is severely damaged, the system can support the storage and preservation of key data. Description of the Drawings

[0017] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become easily understandable. In the drawings, several embodiments of the present invention are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, where: Figure 1 is the operation flowchart of the data security storage method; Figure 2 is the structural block diagram of the data security storage system; In the figure: 1 is the processor; 2 is the data cache register; 3 is the hard disk memory; 4 is the backup power supply. Detailed Embodiments

[0018] The technical features of the present invention will be further described in detail below with reference to the accompanying drawings so that those skilled in the art can understand.

[0019] A data security storage method based on emergency power-off of in-vehicle network terminals. Its application scenario is that when a vehicle encounters an accident, battery failure, or extreme environment, resulting in abnormal or emergency power-off of the vehicle's power system, various emergencies often occur, making it impossible to ensure the safe storage of all vehicle data even with a backup power supply. Therefore, it is necessary to prioritize various vehicle data. The abnormal vehicle data is often the key to scene restoration. So, abnormal data needs to be stored preferentially for troubleshooting emergencies during subsequent processing. Therefore, the main purpose of this data security storage method is to achieve dynamic priority quick sorting, improve the storage efficiency of critical data, and ensure that abnormal data can be stored preferentially. The specific operation logic is as Figure 1 shown, and its operation steps are as follows: Step S1: Obtain various vehicle information data in the normal state, set threshold parameters for each item of vehicle information respectively, and number each item of vehicle information and the corresponding sensors for each item of vehicle information; Specifically, obtain various vehicle information data in the normal state, set the corresponding threshold parameters for each item of vehicle information according to historical normal data, and number each item of vehicle information and the corresponding sensors for each item of vehicle information from 1 to N according to the urgency of troubleshooting vehicle failure factors for each item of vehicle information. Assume there are N items of vehicle information and they correspond to N sensors respectively. Then N is the number of the last item of vehicle information and the last sensor, and at the same time, N represents the total number of sensors and N is a positive integer.

[0020] Step S2: Detect and receive various vehicle information at the current moment, and classify them into the corresponding numbers respectively; Specifically, the corresponding sensor device on the vehicle detects and collects various vehicle information at the current moment in real time, obtaining acquisition data in multiple dimensions. The data collected by the nth sensor is , since there are N sensors in total, the value range of n is from 1 to N. The data collected by the sensors is associated and corresponding to the sensor numbers respectively. Since each sensor detects in real time, is a continuous time-series data sequence. Furthermore, the data collected by the nth sensor at time t is .

[0021] Step S3: Obtain the abnormal values of each item of vehicle information, and perform normalization of the abnormal value data to obtain the abnormal characteristic values of each item of vehicle information at the current moment; Specifically, use the model in neural network algorithm or machine learning algorithm to realize the abnormal detection and analysis of each item of sensing information data, so as to calculate the abnormal values of each item of vehicle information respectively. Among them, the abnormal value of the acquisition data corresponding to the nth sensor at time t can be obtained as , The numerical value range is from 0 to 1; among them, neural network anomaly detection algorithms such as the LSTM time series anomaly detection model or the anomaly detection method of LOF, etc. Preferably, this solution uses the LSTM time series anomaly detection model to perform anomaly detection calculations on the vehicle information collected by each sensor. In addition, since the data unit amounts detected by different sensing devices are different, the meanings represented are different, and the corresponding anomaly value calculation methods are different, it is necessary to standardize and unify the anomaly values of each vehicle information. The normalization method is to calculate the ratio of the anomaly value of each vehicle information to the corresponding threshold parameter respectively, so as to obtain the normalized anomaly feature value. Among them, the anomaly feature value of the data collected by the nth sensor at time t is , and the anomaly thresholds for the data collected by different sensor devices are not the same, and this solution will not give examples.

[0022] Step S4: Calculate the necessity of reordering at the current moment, and determine whether to change the priority arrangement order of each vehicle information. Specifically, there are two reasons for calculating the necessity of reordering. One is that if real-time sorting is always carried out, a large amount of computing resources are required, and the time spent on each sorting is not fixed, which may cause subsequent sorting congestion and affect timely sorting. The other is that the current vehicle may be in a normal state or the anomaly value of the current vehicle information data is very small, and there is no need for real-time sorting. Therefore, after obtaining the unified anomaly feature values of the data collected by each sensor , it is necessary to calculate to determine whether to reorder to avoid wasting computing resources. The specific calculation process of ; When t = 1, directly sort the vehicle information corresponding to each sensor in descending order of its anomaly feature value, and output the sorting code as the priority sorting result at the first moment. When t ≥ 2, start to calculate the necessity of reordering according to the sorting result of the previous moment ; Among them, the necessity of real-time sorting of the data corresponding to the nth sensor at time t is , and the calculation formula is , in the formula, represents the anomaly feature value of the nth sensor at time t, represents the anomaly feature value of the nth sensor at time t - 1, is and The difference between them represents the change amount of the abnormal feature value of the nth sensor at time t. The calculation formula is , where k is a hyperparameter used to amplify the calculation result. In this solution, the value of k is set to 1.3. represents the exponential function with the natural constant e as the base. Since is 0, it will affect the calculation of the remaining parameters for , and then use the natural exponential function to map the change amount of the abnormal feature value. The value range of n is from 1 to N. By changing the value of n in turn, the necessity of real-time sorting of each sensor data at the current moment can be calculated. When ≤0, it means that the abnormal value of the nth sensor at time t decreases. When >0, it means that the abnormal value of the nth sensor at time t increases. The larger the change amount of the abnormal feature value, the greater the increase amplitude of the abnormal value. Furthermore, if the abnormal feature value of the corresponding data of this sensor is also relatively large itself, it means that the sorting necessity of this sensor data is greater. On the contrary, it means that the sorting necessity of this sensor data is lower. Therefore, The calculation formula needs to include as a calculation factor. In addition, although the necessity of real-time sorting of each sensor data at time t can be calculated through the above steps, if the largest abnormal part in all sensor data has an overall high priority in the previous sorting result, the necessity of updating the sorting result is not great. On the contrary, the more backward the priority of the sensor data with abnormal increase is in the previous sorting result, the greater the necessity of updating the sorting result. That is to say, for the sensor data with abnormal increase, the greater the number of positions its priority needs to change, the greater the necessity of re-sorting. On the contrary, the smaller the number of positions its priority needs to change, the smaller the necessity of re-sorting. Therefore, after calculating the necessity of real-time sorting of all sensors at time t, the maximum value among them needs to be taken to participate in the calculation of . Here, the maximum value is selected not for data distribution analysis, but because this scenario requires high real-time performance. The calculation formula of is: In the formula, represents the necessity of re-sorting at time t, represents the maximum value acquisition function, represents the sorting necessity of the first sensor at time t, represents the sorting necessity of the nth sensor at time t, represents the sorting necessity of the Nth sensor at time t. Indicates the influence factor of the sorting result at time t - 1 on the necessity of sorting at time t, , Indicates the priority ranking number of the sensor corresponding to the maximum necessity at time t at time t - 1, The larger the value, the stronger the necessity of updating the sorting. In the formula for calculating , t ≥ 2, and N represents the total number of sensors; After obtaining the necessity of re - sorting at time t , compare the necessity with the set threshold F, then it can be judged whether to re - sort the priority of vehicle data and generate a new priority sorting code. When <F, it means that there is no need to re - sort the priority at the current moment, and the priority sorting code at the current moment is the same as that at the previous moment. When ≥F, it means that there is a need to re - sort the priority at the current moment, and at the same time trigger the data protection mechanism. After generating a new sorting result and a new priority sorting code, each vehicle information data will be stored according to the newly generated priority sorting code at the current moment. Among them, the value range of the threshold F is 0.60 - 0.85; The value of the threshold F is related to the usage status of the vehicle. The shorter the service life of the vehicle and the better the vehicle condition, the larger the value of F. The worse the vehicle condition, the smaller the value of F. Preferably, for a normal - driving vehicle with a service life within 3 years, the set value of the threshold F in this scheme is 0.76. The better the vehicle condition, the smaller the probability of a malfunction during driving, and the smaller the impact of minor anomalies on vehicle safety. Therefore, the larger the value of the threshold F. On the contrary, the worse the vehicle condition, even minor anomalies may have a greater impact on vehicle safety. Therefore, for abnormal data, it is necessary to be more sensitive, and the value of the threshold F needs to be smaller.

[0023] Step S5: When the necessity of re - sorting is greater than or equal to the set threshold, re - sort the priority of vehicle data based on the sorting result at the previous moment and generate a new priority sorting code; Specifically, when the calculated value is greater than or equal to the threshold F, based on the previous sorting result, for the corresponding vehicle data with an increased abnormal value, re - sort its priority in an insert - type manner. Insert - type sorting is based on the original sorting result and optimizes the sorting on the basis of the previous sorting result, which can improve the sorting efficiency and reduce the probability of sorting jams. At the same time, based on the above - mentioned calculation process of the necessity of re - sorting, when the abnormal value rises Then, when the priority is in descending order, that is, the priority is arranged from high to low, the corresponding sensor data will only be inserted from the back row to the front row for a new priority sorting. >0, indicating abnormal rise, ≤0 means that the abnormal value remains unchanged or decreases. The calculation formula characteristics, so only need to consider >0, that is, the sensor data whose priority needs to be inserted forward; The specific sorting process includes following the order of priority from high to low according to the sequence number of the last sorting result. > 0, perform insertion sorting on the priority of the sensor data. When performing insertion sorting, it is necessary to determine whether the data priority of the nth sensor needs to be inserted before the data priority of the mth sensor, and then it is necessary to combine the abnormal characteristic values ​​of the nth sensor and the mth sensor at time t. and The difference between the values ​​of and the increase in the abnormal value of the nth sensor at time t , calculate the necessity of priority insertion between the nth sensor and the mth sensor , The calculation formula is: , In the formula, Represents the abnormal characteristic value of the nth sensor and the mth sensor at time t and The difference between , where 2≤n≤N, 1≤m≤n-1, and m takes values ​​from 1 to n-1. Starting from 1, m means starting from the sensor with the highest priority at the previous moment and then moving backwards to calculate the necessity of inserting the priority of the nth sensor data at the current moment. ; In calculation In the formula of The associated hyperparameters are used to achieve anomaly amplification so that becomes the effective change, The larger it is, the more it needs to be inserted forward, but There may be negative values. Since the outlier data changes at different times, we need to rely on The value of the nth sensor is used to measure the change in the sensor. and Adding together can give a simple estimate result. At the same time, due to The value can only represent the change of outliers of the same sensor information at adjacent moments. However, the impacts caused by the anomalies represented by different sensor information are different. Therefore, according to to scale it. Although also has , it has been scaled through the function, and then the value of can be used as the effective change amount; According to the value rule of m from 1 to n - 1, in the order of decreasing priority, calculate the corresponding insertion necessity in turn, and at the same time compare it with the set threshold r in turn. When ≤r, it means that the data priority of the nth sensor does not need to be inserted before the mth sensor. Then, change the value of m in turn to calculate the of the next position, and compare it with the set threshold r again until >r, which means that the data priority of the nth sensor needs to be inserted before the priority of the mth sensor at this time, so as to determine the data priority position of the nth sensor. Among them, the value range of the threshold r is 0.10 - 0.30; Among them, the value of the threshold r is related to the usage condition of the vehicle. The shorter the service life of the vehicle and the better the vehicle condition, the larger the value of r. The worse the vehicle condition, the smaller the value of r. Preferably, for a normal driving vehicle with a service life within 3 years, the set threshold r value of this scheme is 0.22. The better the vehicle condition, the smaller the probability of failure during driving, and the smaller the impact of minor anomalies on vehicle safety. Therefore, the value of the threshold r is larger. On the contrary, the worse the vehicle condition, even minor anomalies may have a greater impact on vehicle safety. Therefore, for data with an increasing outlier value, it is necessary to be more sensitive, and the value of the threshold r needs to be reduced; After that, according to the serial numbers of the previous sorting results in the order of decreasing priority, for the >0 sensor data, change the value of n in turn to calculate the of the next sensor data until the insertion positions of the priorities of all sensor data with increasing outlier values are determined. This insertion - type priority sorting is completed. Finally, a new priority sorting code is generated according to the numbers of each sensor data in the order of decreasing priority.

[0024] In addition, after the above - mentioned insertion - type sorting, different weight ratios can also be set according to the urgency of troubleshooting vehicle fault factors for each vehicle information item. Multiply the abnormal characteristic values by the corresponding weights in the sorting order in turn, and then for the abnormal characteristic value size or the outlier value change range Perform secondary sorting adjustment on the size to improve the abnormal eigenvalue The priority of large vehicle data or the change range of abnormal values The priority of large vehicle data; for abnormal eigenvalues through the existing sorting method The size or the change range of abnormal values Perform secondary sorting on the size, which can maintain the regularity of data sorting. However, the secondary sorting can only be performed from a single angle of abnormal eigenvalues Or the change range of abnormal values Sorting may deviate from the actual needs because a lower feature may correspond to a larger abnormal change. Therefore, it should be considered to be arranged in a relatively more forward position in the priority. Therefore, although there will be a situation where lower eigenvalues are sorted in the front without secondary sorting, it will be more in line with the actual situation and make the data sorting more reasonable.

[0025] Step S6: Trigger the data protection mechanism in response to the necessity of re-sorting being greater than or equal to the set threshold or vehicle power supply abnormality. In response to the triggering of the data protection mechanism, store each vehicle information data in sequence according to the priority order of the sorting code at the current moment; Specifically, the vehicle power supply voltage is detected in real time by a sensor, and the detected vehicle power supply voltage information is compared with the corresponding voltage threshold parameter. If the vehicle power supply voltage detected in real time by the sensor is within the set threshold parameter range, it means that the vehicle power supply system is in a normal state. If the vehicle power supply voltage detected in real time by the sensor exceeds the set threshold parameter range, the backup power supply is immediately started and the data protection mechanism is triggered; When the vehicle power supply system has an abnormality, or the abnormal value of a certain vehicle information increases sharply, making the necessity of re-sorting Greater than or equal to the threshold F, the data protection mechanism will be triggered. The data protection mechanism is the process of urgently storing each vehicle information data cached in the data cache register 2 into the hard disk memory 3 for preservation in the order of priority when triggered; If the data protection mechanism is triggered due to an abnormality in the vehicle power supply system, the system continues to run the subsequent steps to obtain the necessity of re-sorting , to determine the priority sorting code at the current moment. If a new priority sorting code is generated at the current moment, the current sorting code is the new code after re-sorting at the current moment. If there is no need to re-sort the priority at the current moment, the sorting code remains unchanged, and the sorting code at the current moment is the same as the sorting code at the previous moment; Therefore, if a new priority sorting code is generated at the current moment, each vehicle information data is stored in sequence according to the priority order of the newly generated sorting code. If there is no need to re-sort the priority at the current moment, each vehicle information data is stored in sequence according to the priority order of the previous sorting code.

[0026] A data security storage system based on emergency power-off of in-vehicle network engine terminals, as Figure 2 shown, is used to run and implement the above data security storage method. Its hardware structure includes one or more processors 1 for running computing programs, a data cache register 2 for caching various vehicle information, a hard disk memory 3 for storing various vehicle information in the long term, and a backup power supply 4 for powering the system in the event of an emergency when the vehicle power system is abnormal. The processor 1 is electrically connected to the data cache register 2, the hard disk memory 3, and the backup power supply 4 respectively. The data cache register 2 is electrically connected to the data cache device of the in-vehicle network engine terminal and various associated sensor devices through a communication bus. This system can be designed as an independent storage device, communicate with the in-vehicle network engine terminal for data and power connection through a data cable, and can also be directly embedded and integrated into the existing in-vehicle network engine terminal.

[0027] Specifically, this data security storage system can be directly embedded and integrated into the existing in-vehicle network engine terminal. The processor 1, the data cache register 2, and the hard disk memory 3 are respectively the processor, data cache device, and memory of the in-vehicle network engine terminal. The backup power supply 4 is the battery of the in-vehicle network engine terminal or an additional power supply path set. The backup power supply 4 can form a dual-power supply system with the normal power supply circuit system, so as to ensure that in the extreme case where the vehicle power system is severely damaged, it supports the system to complete the storage and preservation of key data.

[0028] The embodiments described in the present invention are only descriptions of the preferred embodiments of the present invention, and are not limited to the exact structure already described and shown in the drawings. Various modifications and changes can be made without departing from its protection scope; without departing from the design concept of the present invention, various variations and improvements made by those skilled in the art to the technical solutions of the present invention shall fall within the protection scope of the present invention.

Claims

1. A data security storage method based on emergency power off of a vehicle-mounted network engine terminal, characterized in that: Obtain historical normal data and set various threshold parameters; detect various vehicle information in real time, obtain abnormal values, and calculate the necessity of reordering at the current moment; when the necessity of reordering is less than the set threshold, the priority sorting code at the current moment remains unchanged; When the necessity of re-ordering is greater than or equal to a set threshold, the priority of the vehicle data is re-ordered to generate a new priority ordering code; In response to the necessity of reordering being greater than or equal to a set threshold or the vehicle power supply being abnormal, the data protection mechanism is triggered, and each vehicle information data is stored in sequence according to the priority order of the sorting code at the current moment.

2. The data security storage method according to claim 1, characterized in that: The obtaining of historical normal data and setting of various threshold parameters include: obtaining various vehicle information data under normal conditions, setting threshold parameters corresponding to various vehicle information according to the historical normal data, and numbering various vehicle information and sensors corresponding to various vehicle information from 1 to N according to the importance of various vehicle information to troubleshooting vehicle failure factors.

3. The data security storage method according to claim 2, characterized in that: The real-time detection of various vehicle information includes: detecting and receiving various vehicle information at the current moment, and classifying them into corresponding numbers respectively, and having corresponding sensor devices on the vehicle detect and collect various vehicle information at the current moment in real time to obtain collected data in multiple dimensions, and the data collected by the sensors are respectively associated with the sensor numbers.

4. The data security storage method according to claim 3, characterized in that: Based on the collected data of the multiple dimensions, abnormal values ​​of various vehicle information at the current moment are obtained, including: using a neural network algorithm or a machine learning algorithm to perform abnormal detection analysis on various sensor information data to obtain abnormal values ​​of various vehicle information at the current moment; calculating the ratio of the abnormal values ​​of various vehicle information to corresponding threshold parameters, normalizing the abnormal value data, and obtaining normalized abnormal feature values.

5. The data security storage method according to claim 4, characterized in that: Based on the abnormal characteristic value, the necessity of reordering at the current moment is obtained, including: at the first moment, the priority of vehicle information is sorted in descending order according to the abnormal characteristic value of the sensor; from the second moment on, the change in the abnormal characteristic value of each sensor is calculated and forward relationship mapping is performed as a weight coefficient, and the product of the abnormal characteristic value of the sensor at the current moment and the corresponding weight coefficient is used as the necessity of reordering the sensor at the current moment; the ratio of the priority arrangement number of the sensor corresponding to the maximum value of the necessity of sorting at the current moment to the total number of sensors at the previous moment of the current moment is calculated; and the product of the maximum value of the necessity of sorting all sensors at the current moment and the ratio is used as the necessity of reordering at the current moment.

6. The data security storage method according to claim 5, characterized in that: Based on the necessity of reordering at the current moment, determine whether to change the priority order of each vehicle information, including: setting a threshold value according to the actual vehicle condition of the vehicle; when the necessity of reordering is less than the set threshold value, it means that no priority reordering is required at the current moment; the sorting code at the current moment is consistent with the sorting code at the moment before the current moment; when the necessity of reordering is greater than or equal to the set threshold value, it means that priority reordering is required at the current moment.

7. The data security storage method according to claim 6, characterized in that: Based on the necessity of reordering being greater than or equal to a set threshold, the priority of the vehicle data is reordered, including: calculating the difference in abnormal characteristic values ​​corresponding to the sensor with an increased abnormal characteristic value and the sensor with a preceding arrangement number; and taking the product of the necessity of sorting corresponding to the current sensor and the change in the abnormal characteristic value and the sum of the abnormal characteristic value difference as the necessity of insertion of the current sensor priority in the insertion sorting process.

8. The data security storage method according to claim 7, characterized in that: Based on the necessity of inserting the sensor priority, the priority arrangement order of each sensor data is determined in sequence, including: according to the arrangement sequence number of the priority at the previous moment before the current moment, the corresponding insertion necessity between the sensor with increased abnormal characteristic value and the sensor with the previous arrangement sequence number is calculated from front to back, and compared with the set threshold value in sequence. When the insertion necessity is less than or equal to the set threshold, it means that the priority of the current sensor does not need to be inserted before the corresponding sensor. When the insertion necessity is greater than the set threshold, it means that the priority of the current sensor needs to be inserted before the corresponding sensor, thereby determining the sorting position of the current sensor; until the sorting of all sensors with increased abnormal characteristic values ​​is completed, a new priority sorting code is generated.

9. A data security storage system based on emergency power off of a vehicle-mounted network engine terminal, used to implement the data security storage method according to any one of claims 1 to 8, characterized in that: include: One or more processors (1) for running a computing program, a data cache register (2) for caching various vehicle information, a hard disk storage device (3) for long-term storage of various vehicle information, and a backup power supply (4) for supplying power to the vehicle power supply system in an emergency situation when the vehicle power supply system is abnormal, wherein the processor (1) is electrically connected to the data cache register (2), the hard disk storage device (3) and the backup power supply (4), respectively, and the data cache register (2) is electrically connected to a data cache device of an onboard network engine terminal and various associated sensor devices via a communication bus.

10. The data security storage system according to claim 9, characterized in that: The data security storage system can be directly embedded and integrated into an existing vehicle-mounted network engine terminal. The processor (1), the data cache register (2) and the hard disk storage (3) are respectively the processor, data cache device and storage of the vehicle-mounted network engine terminal. The backup power supply (4) is a battery of the vehicle-mounted network engine terminal or a separately provided power supply path.

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