Data Security Storage Method and System Based on Emergency Power Off of In-Vehicle Network Engine Terminal

Abstract

The present invention provides a data security storage method and system based on emergency power-off of an in-vehicle network engine terminal. The key points of its technical solution include: obtaining historical normal data and setting various threshold parameters; detecting various vehicle information in real time and obtaining 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 supply being abnormal, trigger a data protection mechanism, and store each vehicle information data in sequence according to the priority order of the sorting code at the current moment; the present invention can achieve dynamic priority fast sorting, improve the storage efficiency of critical data, and ensure 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 resulting in 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 method of storing data in in-vehicle network engine terminals, which often stores various vehicle information data in sequence according to the set order, and the priority of each data is fixed, 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 easily leads to the loss of important abnormal data and has 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:

[0006] A data security storage method based on emergency power-off of in-vehicle network engine terminals, and its steps include:

[0007] 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 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.

[0008] 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 failure factors for various vehicle information.

[0009] Preferably, the detecting various vehicle information in real time includes: detecting and receiving various vehicle information at the current moment and classifying them into 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 collected data, and the data collected by the sensors are associated with the numbers of the sensors respectively.

[0010] Preferably, based on the multi-dimensional collected data, obtaining the abnormal values of various vehicle information at the current moment includes: using a neural network algorithm or a machine learning algorithm to perform abnormal detection and analysis on each sensing information data to obtain the abnormal values of various vehicle information at the current moment; calculating the ratio of the abnormal values of various vehicle information to the corresponding threshold parameters respectively to normalize the abnormal value data and obtain the normalized abnormal feature values.

[0011] Preferably, based on the abnormal 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 according to the abnormal feature values of the sensors; starting from the second moment, calculating the change amount of the abnormal feature value of each sensor and performing a positive relationship mapping as the weight coefficient, and taking the product of the abnormal 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 serial number of the priority arrangement 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.

[0012] Preferably, based on the necessity of reordering at the current moment, it is judged 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.

[0013] 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 in abnormal eigenvalue between the sensor with an increasing abnormal eigenvalue and the sensor corresponding to the 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 difference in abnormal eigenvalue as the insertion necessity of the priority of the current sensor in the insertion sorting process.

[0014] 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.

[0015] In a second aspect, the present invention provides a data security storage system based on emergency power-off of an in-vehicle network engine terminal, and its technical solution is as follows:

[0016] A data security storage system based on 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.

[0017] Preferably, the data security storage system can be directly embedded and integrated into the existing in-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 in-vehicle network engine terminal, and the backup power supply is the battery of the in-vehicle network engine terminal or an additional power supply path set up.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0019] 1. A data security storage method based on emergency power-off of an in-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 system is abnormal or in an emergency power-off situation, the key data with a higher abnormal value in the in-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, thus providing strong guarantee for subsequent vehicle fault or accident analysis and other situations.

[0020] 2. A data security storage system based on emergency power-off of an in-vehicle network engine terminal according to the present invention 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. 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 situation where the vehicle power system is severely damaged, the system can support the storage and preservation of key data. Description of the Drawings

[0021] 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:

[0022] Figure 1 is the operation flowchart of the data security storage method;

[0023] Figure 2 is the structural block diagram of the data security storage system;

[0024] 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

[0025] The following further elaborates on the technical features of the present invention with reference to the accompanying drawings for the convenience of those skilled in the art to understand.

[0026] 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. Often due to various emergencies, even if there is a backup power supply, it may not be possible to ensure the secure storage of all vehicle data. Therefore, it is necessary to prioritize various vehicle data. Among them, the abnormal vehicle data is often the key to scene restoration. So, abnormal data needs to be preferentially stored 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 preferentially stored. The specific operation logic is as Figure 1 shown, and its operation steps are as follows:

[0027] Step S1: Obtain various vehicle information data in the normal state, respectively set threshold parameters for each vehicle information, and number each vehicle information and the corresponding sensor for each vehicle information;

[0028] Specifically, obtain various vehicle information data in the normal state, respectively set the threshold parameters corresponding to each vehicle information according to historical normal data, and number each vehicle information and the corresponding sensor for each vehicle information from 1 to N according to the urgency of troubleshooting vehicle fault factors for each vehicle information. Assume there are N vehicle information items and they respectively correspond to N sensors. Then N is the number of the last vehicle information item and the last sensor, and at the same time, N represents the total number of sensors and N is a positive integer.

[0029] Step S2: Detect and receive various vehicle information at the current moment, and classify them into the corresponding numbers respectively;

[0030] Specifically, the corresponding sensor device on the vehicle real-time detects and collects various vehicle information at the current moment to obtain acquisition data in multiple dimensions. Among them, 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 respectively associated and corresponding to the numbers of the sensors. Since each sensor is real-time detected, therefore is a continuous time-series data sequence. Furthermore, the data collected by the nth sensor at time t is .

[0031] Step S3: Obtain the abnormal values of each vehicle information, and perform normalization of the abnormal value data to obtain the abnormal characteristic values of each vehicle information at the current moment;

[0032] Specifically, the model in the neural network algorithm or machine learning algorithm is used to implement the anomaly detection and analysis of various sensing information data, so as to calculate the anomaly values of various vehicle information respectively. Among them, the anomaly value of the data collected by the nth sensor at time t can be obtained as , The numerical value range of is 0~1; Among them, neural network anomaly detection algorithms such as: LSTM time series anomaly detection model, or anomaly detection methods such as 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;

[0033] 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 various vehicle information. The normalization method is to calculate the ratio of the anomaly values of various vehicle information to the corresponding threshold parameters respectively, so as to obtain the normalized anomaly feature values. 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. This solution will not give examples.

[0034] Step S4: Calculate the necessity of reordering at the current moment, and judge whether to change the priority arrangement order of various vehicle information;

[0035] 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 judge whether to reorder to avoid wasting computing resources;

[0036] The specific calculation process of includes obtaining the necessity of real-time sorting of the data of each sensor at the current moment, and then obtaining the necessity of reordering at the current moment ;

[0037] 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 ;

[0038] 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 , where in the formula represents the abnormal feature value of the nth sensor at time t, represents the abnormal 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 of is , k is a hyperparameter used to amplify the calculation result. In this scheme, 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 . Therefore, the natural exponential function is used 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;

[0039] When ≤0, it means that the abnormal value of the nth sensor decreases at time t. When >0, it means that the abnormal value of the nth sensor increases at time t. 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 data corresponding to the sensor itself is also relatively large, it means that the sorting necessity of this sensor data is greater, otherwise it means that the sorting necessity of this sensor data is lower. Therefore, The calculation formula of needs to include as a calculation factor;

[0040] 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 of 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 whose priority needs to be changed, the greater the necessity of re-sorting, and vice versa, the smaller the number of positions whose priority needs to be changed, the smaller the necessity of re-sorting;

[0041] 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 is as follows:

[0042] ,

[0043] In the formula, represents the necessity of reordering at time t, represents the maximum value obtaining function, represents the necessity of sorting for the first sensor at time t, represents the necessity of sorting for the nth sensor at time t, represents the necessity of sorting for the Nth sensor at time t, represents the influence factor of the sorting result at time t - 1 on the necessity of sorting at time t, , represents 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. When calculating in the formula, t≥2, and N represents the total number of sensors;

[0044] After obtaining the necessity of reordering at time t Compare the necessity with the set threshold F, and it can be judged whether to re - prioritize the vehicle data and generate a new priority sorting code. When <F, it means that there is no need to re - prioritize 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 re - prioritization is required at the current moment, and the data protection mechanism is triggered. 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;

[0045] The value of the threshold F 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 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 failure 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.

[0046] Step S5: When the necessity for re - sorting is greater than or equal to the set threshold, re - sort the priorities of the vehicle data based on the previous - moment sorting result and generate a new priority - sorting code;

[0047] 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 increasing outlier, perform an insertion - type re - sorting on its priority. Insertion - 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 for re - sorting when the outlier rises will be large. Furthermore, under the condition that the priority sorting is in descending order, that is, the priorities are arranged from high to low, the corresponding sensor data will only be inserted from the back row to the front row for the new priority sorting. Since > 0 indicates an abnormal increase, ≤0 indicates that the outlier remains unchanged or decreases. Among them, due to the calculation - formula characteristics of the real - time sorting necessity of single - item sensing information only the sensor data with > 0 needs to be considered, that is, the relevant sensor data whose priority needs to be inserted forward;

[0048] The specific sorting process includes, according to the serial numbers of the previous sorting result, in the order of priority from high to low, for > 0 sensor data, perform insertion - type sorting on its priority in turn. When performing insertion - type sorting, it is necessary to judge whether the priority of the data of the nth sensor needs to be inserted forward before the priority of the data of the mth sensor. Furthermore, it is necessary to comprehensively consider the difference between the outlier - feature values and of the nth sensor and the mth sensor at time t, and the increase amplitude of the outlier of the nth sensor at time t, and calculate the necessity for inserting the priority between the nth sensor and the mth sensor The calculation formula of

[0049] is:

[0050] In the formula, represents the difference between the outlier - feature values and of the nth sensor and the mth sensor at time t, , 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 continuing to take values in sequence to calculate the necessity of inserting the priority of the nth sensor data at the current moment. ;

[0051] In calculation In the formula as The associated hyperparameters are used to achieve anomaly amplification so that becomes the effective variation, The larger it is, the more forward insertion is required, but There may be negative values. Since the outlier data changes at different times, it is necessary to rely on The value of the nth sensor is used to measure the change of the value of the nth sensor. and Adding them together can give a simple estimate. At the same time, due to The value can only represent the change of abnormal value of the same sensor information at adjacent moments, and the impact of abnormality represented by different sensor information is different, so it can be based on right To scale, though There are also , but has passed The function is scaled to obtain The value of can be used as the effective change;

[0052] According to the value rule of m from 1 to n-1, the corresponding insertion necessity is calculated in order from high to low priority. , and then compare it with the set threshold r. ≤r, indicating that the data priority of the nth sensor does not need to be inserted before the mth sensor, and then the value of m is changed in turn to calculate the next priority , and then compare it with the set threshold r until >r, it 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 of the nth sensor. The value range of the threshold r is 0.10~0.30;

[0053] 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 threshold r set in this solution is 0.22. The better the vehicle condition, the smaller the probability of a malfunction occurring during driving, and the smaller the impact of a minor anomaly on vehicle safety. Therefore, the value of the threshold r is larger. On the contrary, the worse the vehicle condition, even a minor anomaly may have a greater impact on vehicle safety. Therefore, for data with an increasing outlier, it is necessary to be more sensitive, and the value of the threshold r needs to be reduced;

[0054] After that, according to the sequence numbers of the previous sorting results in descending order of priority, for sensor data with > 0, the value of n is sequentially changed to calculate the of the next sensor data until the insertion positions of the priorities of all sensor data with increasing outliers are determined, and this insertion - type priority sorting is completed. Finally, a new priority sorting code is generated according to the numbers of each sensor data in descending order of priority.

[0055] In addition, after the above - mentioned insertion - type sorting, different weight ratios can also be set according to the importance of troubleshooting vehicle failure factors for each vehicle information. The abnormal characteristic values are sequentially multiplied by the corresponding weights according to the sorting order, and then, for the abnormal characteristic values in terms of magnitude or the magnitude of the change in the outlier value a secondary sorting adjustment is performed to increase the priority of vehicle data with large abnormal characteristic values or the priority of vehicle data with a large magnitude of change in the outlier value ; By using the existing sorting method to perform a secondary sorting on the magnitude of the abnormal characteristic value or the magnitude of the change in the outlier value it is possible to maintain the regularity of data sorting. However, the secondary sorting can only be performed from a single angle of the abnormal characteristic value or the magnitude of the change in the outlier value and may deviate from the actual needs. Because a low - characteristic value may correspond to a larger abnormal change, it should be considered to be arranged in a relatively more forward position in the priority. Therefore, although there may be a situation where low - characteristic values are sorted in the front without performing secondary sorting, it will be more in line with the actual situation and make the data sorting more reasonable.

[0056] Step S6: In response to the necessity of re - sorting being greater than or equal to the set threshold or vehicle power supply anomaly, trigger the data protection mechanism. 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;

[0057] 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 by the sensor in real time is within the set threshold parameter range, it indicates that the vehicle power supply system is in a normal state. If the vehicle power supply voltage detected by the sensor in real time exceeds the set threshold parameter range, the backup power supply is immediately activated and the data protection mechanism is triggered;

[0058] When the vehicle power supply system is abnormal, or the abnormal value of a certain vehicle information increases sharply, making the necessity of reordering 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 the vehicle information data cached in the data cache register 2 into the hard disk memory 3 in the order of priority when triggered;

[0059] 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 reordering , 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 reordering at the current moment. If there is no need to reorder 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, the vehicle information data is stored in sequence according to the priority order of the newly generated sorting code. If there is no need to reorder the priority at the current moment, the vehicle information data is stored in sequence according to the priority order of the previous sorting code.

[0060] A data security storage system based on the emergency power-off of an in-vehicle network engine terminal, 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 for a long time, and a backup power supply 4 for powering the system in the event of an emergency in the vehicle power supply system. 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 related sensor devices through a communication bus. This system can be designed as a separate 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.

[0061] Specifically, the data security storage system can be directly embedded and integrated into the existing vehicle network engine terminal. The processor 1, the data cache register 2, and the hard disk memory 3 are respectively the processor, the data cache device, and the memory of the vehicle network engine terminal. The backup power supply 4 is the battery of the vehicle network engine terminal or an additional power supply path provided. 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, the system can support the storage and preservation of critical data.

[0062] 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 structures 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 should fall within the protection scope of the present invention.

Claims

1. A data security storage method based on emergency power-off of in-vehicle network engine terminals, 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 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 supply being abnormal, trigger a data protection mechanism, and store each vehicle information data in sequence according to the priority order of the sorting code at the current moment; Among them, the calculation of the necessity of reordering at the current moment is as follows: Use neural network algorithms or machine learning algorithms to perform abnormal detection and analysis on each sensing information data to obtain abnormal values of each vehicle information at the current moment; calculate the ratio of the abnormal values of each vehicle information to the corresponding threshold parameters respectively to normalize the abnormal value data and obtain normalized abnormal characteristic values; At the first moment, sort the priority of vehicle information in descending order of the abnormal characteristic values of the sensors; starting from the second moment, calculate the change amount of the abnormal characteristic values of each sensor and perform a positive relationship mapping as the weight coefficient, and take the product of the abnormal characteristic value of the sensor at the current moment and the corresponding weight coefficient as the necessity of sorting of the sensor at the current moment; calculate the ratio of the priority arrangement serial number of the sensor corresponding to the maximum value of the necessity of sorting at the current moment at the previous moment of the current moment to the total number of sensors; take the product of the maximum value of the necessity of sorting of all sensors at the current moment and the ratio as the necessity of reordering at the current moment.

2. The data security storage method according to claim 1, wherein The obtaining of historical normal data and setting of various threshold parameters includes: obtaining various vehicle information data in the normal state, setting the threshold parameters corresponding to each vehicle information according to the historical normal data, and numbering each vehicle information and the corresponding sensor of each vehicle information from 1 to N according to the urgency of troubleshooting vehicle failure factors for each vehicle information.

3. The data security storage method according to claim 2, wherein The real-time detection of each vehicle information includes: detecting and receiving each 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 each vehicle information at the current moment in real time to obtain multi-dimensional collected data, and the data collected by the sensors are respectively associated with the numbers of the sensors.

4. The data security storage method according to claim 3, characterized in that Based on the necessity of reordering at the current moment, judge whether to change the priority arrangement order of each vehicle information, including: setting a threshold according to the actual vehicle condition of the vehicle. 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 the sorting code at the previous moment of 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.

5. The data security storage method according to claim 4, wherein Based on the necessity of the reordering being greater than or equal to a set threshold, reorder the priorities of vehicle data, including: calculating the difference in abnormal eigenvalue between the sensor with an increasing abnormal eigenvalue and the abnormal eigenvalue corresponding to the sensor with a previous sequence 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 difference in abnormal eigenvalue as the insertion necessity of the priority of the current sensor in the insertion sorting process.

6. The data security storage method according to claim 5, characterized in that Based on the insertion necessity of the sensor priority, sequentially determine the priority arrangement order of each item of sensor data, including: calculating the insertion necessity corresponding to the sensor with an increasing abnormal eigenvalue and the sensor with a previous sequence number from front to back according to the sequence number of the priority at the previous moment of the current moment, and sequentially comparing it with the set threshold. 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, generate a new priority sorting code.

7. A data security storage system based on emergency power-off of in-vehicle network engine terminals, used to implement the data security storage method described in any one of claims 1 to 6, characterized in that, Including: One or more processors (1) for running calculation 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 in the vehicle power system. 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.

8. The data security storage system according to claim 7, wherein 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 set power supply path.

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