ECU unauthorized swiping early warning method and system and motor vehicle

Abstract

The invention relates to an ECU fraud-swiping early warning method and system and a motor vehicle, and the method comprises the steps: obtaining a corresponding CVN value and related information during the change when an ECU has an unexpected change; comparing the CVN value when the ECU is subjected to the unexpected change with the CVN value when the ECU is subjected to the unexpected change last time, and if the difference between the two values exceeds a set value, storing the CVN value corresponding to the change and associated information; when the stored CVN value does not belong to the engine factory CVN standard library, the unexpected change of the ECU at this time is'single fraud ', and whether the unexpected change of the ECU at this time is'centralized fraud' or not is further determined according to the corresponding time and position when the CVN value is acquired for two adjacent times; and further judging whether the NOx emission data is'increased 'compared with the NOx emission data before the ECU unauthorized swiping, and if the NOx emission data is'increased' and does not meet the current emission requirement, outputting an early warning signal of'illegal emission '. According to the invention, recognition and monitoring of the ECU fraud-brushing phenomenon are realized, and early warning when NOx emission violation occurs after fraud-brushing is carried out is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of engine control, and in particular to an ECU fraud warning method and system and a motor vehicle. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] ECU flashing involves illegally tampering with or copying a vehicle's electronic control unit (ECU) data to gain unauthorized functionality or services. After a flash, the ECU can be modified to improve performance, alter the odometer, and tamper with the emissions system. These functions can damage the engine and related components, and can also pollute the environment. ECU flashing is also a violation of regulations.

[0004] Existing technology generally determines whether an ECU has been fraudulently reset by changes in the CVN value (Calibration Verification Number), but it is unable to determine whether the changes in NOx emissions caused by the ECU being fraudulently reset will damage the environment (i.e., emission violations). Summary of the Invention

[0005] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides an ECU fraud warning method, system and motor vehicle, which combine CVN jump and NOx emissions to accurately identify fraudulent use and issue a warning.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A first aspect of the present invention provides an ECU fraud warning method, comprising the following steps:

[0008] When an unexpected change occurs in the ECU, the corresponding CVN value and related information are obtained, including the time and location of the unexpected change, the type of ECU that experienced the unexpected change, the corresponding engine type information, and NOx emission data;

[0009] Compare the CVN value when the ECU undergoes an unexpected change with the CVN value when the ECU undergoes an unexpected change last time. If the difference between the two exceeds the set value, save the CVN value and related information corresponding to this change.

[0010] If the saved CVN value does not belong to the standard CVN library of the engine factory, the unexpected change of the ECU is a "single fraud". The time and location corresponding to the two consecutive CVN values ​​are further used to determine whether the unexpected change of the ECU is a "collective fraud".

[0011] When the unexpected change in the ECU is a "single fraud" or "collective fraud", the NOx emission data corresponding to the CVN value, combined with the engine information and vehicle status information, is used to determine whether the NOx emission data has "increased" compared to before the ECU fraud. If it has "increased" and does not meet the current emission requirements, an "emission violation" warning signal is output.

[0012] Furthermore, when the saved CVN value does not belong to the engine factory CVN standard library, and within the set calculation cycle, the corresponding time and location of two consecutive CVN values ​​are different, and at the same time, the CVN values ​​corresponding to other vehicles with the same ECU type as the current vehicle are the same, then the unexpected change in the ECU this time is "centralized fraud."

[0013] Furthermore, when the saved CVN value belongs to the standard database, and within the set calculation cycle, the corresponding positions of two consecutive CVN values ​​are the same, and the time deviation is within the set range, and at the same time, the CVN values ​​corresponding to other vehicles with the same ECU type as the current vehicle are the same, then the unexpected change of the ECU this time is "centralized flashing", that is, the ECU is flashed through legal channels.

[0014] Furthermore, when the saved CVN value belongs to the standard database, and within the set calculation cycle, the corresponding positions of two consecutive CVN values ​​are the same, and the time deviation is within the set range, then the unexpected change that occurred in the ECU this time is a "single flash", that is, the ECU was flashed through a legal channel.

[0015] Furthermore, situations that do not fall under the categories of “collective theft”, “single theft”, “collective swiping” and “single swiping” are all classified as “others”.

[0016] Furthermore, when the unexpected change in the ECU is "single theft", "collective theft" or "other", it is determined whether the NOx emission data is "increased" compared to before the ECU theft. If it is "increased" and does not meet the current emission requirements, an "emission violation" warning signal is output.

[0017] Furthermore, it is determined whether the NOx emission data is "increased" compared to before the ECU was stolen. If it is "increased" but still meets the current emission requirements, no warning signal is issued.

[0018] Furthermore, it is determined whether the NOx emission data is "increased" compared to before the ECU was stolen. If it is "decreased", no warning signal is issued.

[0019] A second aspect of the present invention provides an ECU fraud warning system, comprising:

[0020] The first module is configured to: when an unexpected change occurs in the ECU, obtain the corresponding CVN value and related information at the time of the change, including the time and location of the unexpected change, the type of the ECU that has undergone the unexpected change, the corresponding engine type information, and NOx emission data;

[0021] The second module is configured to compare the CVN value when the ECU undergoes an unexpected change with the CVN value when the ECU undergoes an unexpected change last time, and if the difference between the two exceeds a set value, save the CVN value corresponding to the current change and related information;

[0022] The CVN jump classification processing module is configured to: when the stored CVN value does not belong to the engine factory CVN standard library, the unexpected change of the ECU is a "single fraud"; further, based on the corresponding time and location of two consecutive CVN values, it is determined whether the unexpected change of the ECU is a "collective fraud";

[0023] The NOx classification module is configured as follows: when the unexpected change in the ECU is a "single fraud" or "collective fraud", based on the NOx emission data corresponding to the CVN value, combined with the engine information and vehicle status information, it determines whether the NOx emission data is "increased" compared to before the ECU fraud. If it is "increased" and does not meet the current emission requirements, it outputs an "emission violation" warning signal.

[0024] A third aspect of the present invention provides a motor vehicle having an onboard computer, which executes the steps in the above-mentioned ECU fraud warning method.

[0025] Compared with the existing technology, one or more of the above technical solutions have the following beneficial effects:

[0026] By utilizing the currently mature Internet of Vehicles technology, we can fully mine the network data, build the relationship between CVN jumps and NOx emission data, accurately identify ECU theft, and classify the identified ECU theft. When emissions exceed the standard due to ECU theft, an early warning will be issued. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 This is a schematic diagram of building a database during an ECU fraud warning period provided by one or more embodiments of the present invention;

[0029] Figure 2Schematic diagram of monitoring CVN jumps during ECU fraud warning period provided by one or more embodiments of the present invention;

[0030] Figure 3 This is a schematic diagram of classifying CVN jumps and NOx during ECU fraud warning provided by one or more embodiments of the present invention;

[0031] Figure 4 Schematic diagram of the principle of a mean regression algorithm for monitoring NOx emission data during ECU fraud warning provided by one or more embodiments of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0033] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0034] It should be noted that the terms used herein are intended only to describe specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0035] Explanation of terms:

[0036] A CVN jump refers to an unexpected change in the Calibration Verification Number (CVN) in the vehicle's electronic control unit (ECU). The CVN is used to verify whether the calibration data in the ECU has been tampered with, ensuring its integrity and legitimacy.

[0037] After the ECU is stolen, the ECU parameters can be modified to achieve functions such as performance improvement, odometer tampering, and emission system tampering.

[0038] For example, it is possible to bypass manufacturer restrictions and improve performance by increasing engine power or torque, but this performance improvement method will consume the engine life too quickly.

[0039] The mileage data in the ECU can also be modified so that the vehicle's displayed mileage is lower than the actual mileage, in order to increase the selling price of used cars.

[0040] It is also possible to modify emission-related parameters so that the vehicle passes the inspection, but the actual emissions exceed the standard; that is, after the ECU is stolen, it may cause emission violations.

[0041] Therefore, the following embodiments provide an ECU fraud warning method, system, and motor vehicle. Based on networked data, a CVN standard library and a vehicle-transmitted CVN and NOx-related database are constructed, a CVN jump data classification algorithm is designed, a NOx emission classification algorithm is designed, and an ECU fraud warning system is established to identify and monitor ECU fraud.

[0042] Example 1:

[0043] The ECU fraud warning method includes the following steps:

[0044] When an unexpected change occurs in the ECU, the corresponding CVN value and related information are obtained, including the time and location of the unexpected change, the type of ECU that experienced the unexpected change, the corresponding engine type information, and NOx emission data;

[0045] Compare the CVN value when the ECU undergoes an unexpected change with the CVN value when the ECU undergoes an unexpected change last time. If the difference between the two exceeds the set value, save the CVN value and related information corresponding to this change.

[0046] If the saved CVN value does not belong to the standard CVN library of the engine factory, the unexpected change of the ECU is a "single fraud". The time and location corresponding to the two consecutive CVN values ​​are further used to determine whether the unexpected change of the ECU is a "collective fraud".

[0047] When the unexpected change in the ECU is a "single fraud" or "collective fraud", the NOx emission data corresponding to the CVN value, combined with the engine information and vehicle status information, is used to determine whether the NOx emission data has "increased" compared to before the ECU fraud. If it has "increased" and does not meet the current emission requirements, an "emission violation" warning signal is output.

[0048] Furthermore, when the saved CVN value does not belong to the engine factory CVN standard library, and within the set calculation cycle, the corresponding time and location of two consecutive CVN values ​​are different, and at the same time, the CVN values ​​corresponding to other vehicles with the same ECU type as the current vehicle are the same; then the unexpected change of the ECU this time is considered to be "concentrated fraud".

[0049] In this embodiment, a standard library of engine factory CVNs is constructed, which includes engine numbers and preset CVN values ​​of corresponding engines when they leave the factory. When the CVN value belongs to the library, it is considered to meet the emission requirements and is not recorded as fraudulent use.

[0050] In this embodiment, the constructed CVN jump library includes the vehicle number, engine number, engine type information, ECU type information, and the time, location, corresponding CVN value and NOx emission information when the CVN changes unexpectedly.

[0051] Among them, the data sources required for the constructed CVN jump library are the CVN value generated when the ECU undergoes unexpected changes during the operation of the vehicle, as well as the time when the change occurred, the location of the vehicle (location information, generally longitude and latitude), vehicle number, engine number, engine type information, ECU type information, and corresponding NOx emission information; the vehicle forms a CVN jump library by continuously transmitting CVN and related data.

[0052] The engine factory CVN standard library and CVN jump library are associated through the engine number to form the following Figure 1 The data format shown.

[0053] During the operation of the vehicle, the CVN value will be continuously transmitted back. When the ECU undergoes unexpected changes, the CVN value will "jump". The corresponding CVN value, time, location and other related information will be saved in the CVN jump library.

[0054] like Figure 2 As shown, during vehicle operation, when an unexpected change occurs in the ECU, the CVN value at the time of the change is obtained, and the CVN value at the time of the unexpected change is compared with the CVN value at the time of the last unexpected change. If the difference between the two exceeds the set value, it is considered that the current CVN value is inconsistent with the previous CVN value, and the current CVN value is recorded. The "current CVN value" is used as the basis for CVN jump classification processing;

[0055] If the difference between the current CVN value and the previous CVN value does not exceed the set value, the two are considered to be consistent and no CVN jump classification processing is performed.

[0056] CVN jump classification processing process, such as Figure 3 The system obtains information related to the "current CVN value," including engine type, time and location of the unexpected change, and conducts classification analysis of CVN jumps, which are divided into five types: centralized flashing, single flashing, centralized fraudulent flashing, single fraudulent flashing, and others.

[0057] After the CVN jump, the value still belongs to the standard CVN library, indicating that the CVN jump is not a fraudulent flash situation. The aggregation classification algorithm can be combined with the ECU software version number, the value after the CVN change, the flashing time (the time when the CVN changes), and the position information (the position when the CVN changes). By setting the weight of the CVN value after the change to 50%, and dividing the other weights equally, the output can be used as the input for the subsequent NOx emission aggregation classification. The design of the above weight values ​​can be derived from a large amount of measured data.

[0058] If the CVN value is in the standard database, and the jump times and positions of two consecutive CVN values ​​obtained within 24 hours are close, and the CVN values ​​of other vehicles with the same ECU type as the current vehicle are the same, then the unexpected ECU change is considered a "centralized flash," meaning the ECU was flashed through a legitimate channel and not "stealth flash." This may be due to an ECU firmware upgrade or similar operation.

[0059] If the CVN value is within the standard database and the corresponding jump time and position are different when the CVN value is obtained twice within 24 hours, the unexpected ECU change is considered a "single flash", that is, the ECU was flashed through a legitimate channel and not "ECU theft". This may be due to an ECU firmware upgrade or similar action.

[0060] When the CVN value does not belong to the standard database, and the jump time and position of two consecutive CVN values ​​obtained within 24 hours are close; at the same time, the CVN values ​​corresponding to other vehicles with the same ECU type as the current vehicle are the same; then the unexpected change of the ECU is considered to be "concentrated fraud".

[0061] When the CVN value does not belong to the standard database, and the jump time and position corresponding to two consecutive CVN value acquisitions within 24 hours are different, the unexpected change of the ECU is considered to be "single fraud".

[0062] If the situation does not belong to the above four types, it is considered "other".

[0063] In this embodiment, the "standard database" refers to a pre-established engine factory CVN standard library.

[0064] In this embodiment, the “last acquired CVN value” refers to the CVN value acquired when the ECU last experienced an unexpected change. Correspondingly, the “currently acquired CVN value” refers to the CVN value acquired when the ECU experienced an unexpected change.

[0065] In this embodiment, "close transition times within 24 hours" means that, with a 24-hour calculation cycle, the difference between the times at which the CVN values ​​are obtained for two consecutive times within the calculation cycle does not exceed 10%. For example, if a 24-hour calculation cycle is 10%, 2.4 hours is 10%. If the last CVN value was obtained at 4:00 PM and the current CVN value is 17:00 PM, 17 - 16 = 1 hour. Since 1 hour does not exceed 2.4 hours, the current CVN value is considered close to the previous CVN value, i.e., "close transition times within 24 hours."

[0066] In this embodiment, the calculation period is not limited to 24 hours, and can be other time ranges. Accordingly, the time difference is not limited to 10%, and can be adjusted according to the model of the ECU.

[0067] like Figure 3 As shown, when the results of the CVN jump classification processing are concentrated fraud, single fraud and others, NOx classification is performed, and the corresponding CVN jump data is extracted, including the engine type, time, location, vehicle speed, status and NOx emission data corresponding to the CVN value. Through correlation analysis, the NOx emission data is divided into three types: increase to meet emission regulations, increase to damage emission regulations and decrease.

[0068] Increase - meet emission regulations, which means that the vehicle's NOx emission data has increased compared to before the ECU was stolen, but it still meets the current emission requirements and the emissions are still compliant.

[0069] Increased-damaged emission regulations means that the vehicle's NOx emission data has increased compared to before the ECU was stolen and does not meet the current emission requirements, outputting an "emission violation" warning signal.

[0070] Reduction means that the vehicle's NOx emission data has decreased compared to before the ECU was stolen.

[0071] NOx emissions data has corresponding standards and regulations, and can be classified as either meeting or not meeting them. This solution compares NOx emissions within a certain range of mileage before and after a CVN change to determine whether it falls outside the standard. This process uses the data corresponding to single fraudulent transactions, group fraudulent transactions, and other scenarios as input, which is fed into the NOx cluster classifier one by one to achieve the desired result.

[0072] In this embodiment, the monitoring interval of NOx emission data is 500 km of driving data before and after the CVN change, and the data is divided into 10 intervals (i.e., 5 km is a detection interval, considering that acceleration, deceleration, starting and sudden braking may affect NOx emission data during driving). Each data point in each interval is subjected to the mean regression algorithm, such as Figure 4As shown, the calculation range is narrowed to the 1.5 confidence interval of the standard regulations (to discard outliers), with a weight of 0.8 within the 1.2 confidence interval and 0.8 within the 1.2-1.5 confidence interval. The difference between NOx emissions and the standard regulations is calculated for each segment. Finally, a cluster classifier is used to output results in three categories: emissions decreased compared to the previous period, emissions increased compared to the previous period but met regulatory requirements, and emissions increased compared to the previous period but did not meet emission regulations. Ultimately, warnings are only issued for emissions that increased compared to the previous period and did not meet emission regulations.

[0073] The above process establishes a method for monitoring ECU fraud. Leveraging currently mature Internet of Vehicles (IoV) technology, it fully mines connected data, constructs a relationship between CVN jumps and NOx emissions, and designs a progressive judgment relationship between the two, combining the mechanism and purpose of the fraud. Initially, suspected fraud is identified based on the jump data. Suspected fraud directly affects NOx emissions, and setting a reasonable confidence interval and weight within that interval is crucial. In practice, data acquisition and rapid calculation are also challenging. This solution accurately identifies ECU fraud by analyzing data from over 10,000 vehicles to obtain confidence intervals and weights. It then categorizes identified ECU fraud and issues a warning when emissions exceed standards due to ECU fraud.

[0074] Example 2:

[0075] A second aspect of the present invention provides an ECU fraud warning system, comprising:

[0076] The first module is configured to: when an unexpected change occurs in the ECU, obtain the corresponding CVN value and related information at the time of the change, including the time and location of the unexpected change, the type of the ECU that has undergone the unexpected change, the corresponding engine type information, and NOx emission data;

[0077] The second module is configured to compare the CVN value when the ECU undergoes an unexpected change with the CVN value when the ECU undergoes an unexpected change last time, and if the difference between the two exceeds a set value, save the CVN value corresponding to the current change and related information;

[0078] The CVN jump classification processing module is configured to: when the stored CVN value does not belong to the engine factory CVN standard library, the unexpected change of the ECU is a "single fraud"; further, based on the corresponding time and location of two consecutive CVN values, it is determined whether the unexpected change of the ECU is a "collective fraud";

[0079] The NOx classification module is configured as follows: when the unexpected change in the ECU is a "single fraud" or "collective fraud", based on the NOx emission data corresponding to the CVN value, combined with the engine information and vehicle status information, it determines whether the NOx emission data is "increased" compared to before the ECU fraud. If it is "increased" and does not meet the current emission requirements, it outputs an "emission violation" warning signal.

[0080] By establishing an ECU fraud monitoring method and utilizing currently mature Internet of Vehicles technology, we can fully mine the Internet data, build the relationship between CVN jumps and NOx, accurately identify ECU fraud, and classify the identified ECU fraud. When emissions exceed the standard due to ECU fraud, an early warning will be issued.

[0081] Example 3:

[0082] A motor vehicle is provided with an onboard computer, which executes the steps of the above-mentioned ECU fraud warning method.

[0083] By loading the ECU fraud monitoring method and utilizing the currently mature Internet of Vehicles technology, we can fully mine the Internet data, build the relationship between CVN jumps and NOx, accurately identify ECU fraud, and classify the identified ECU fraud. When the emission exceeds the standard due to ECU fraud, an early warning will be issued.

[0084] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. ECU fraud warning method, characterized by: The following steps are involved: When an unexpected change occurs in the ECU, the corresponding CVN value and related information are obtained, including the time and location of the unexpected change, the type of ECU that experienced the unexpected change, the corresponding engine type information, and NOx emission data; Compare the CVN value when the ECU undergoes an unexpected change with the CVN value when the ECU undergoes an unexpected change last time. If the difference between the two exceeds the set value, save the CVN value and related information corresponding to this change. If the saved CVN value does not belong to the standard CVN library of the engine factory, the unexpected change of the ECU is a "single fraud". The time and location corresponding to the two consecutive CVN values ​​are further used to determine whether the unexpected change of the ECU is a "collective fraud". When the unexpected change in the ECU is a "single fraud" or "collective fraud", the NOx emission data corresponding to the CVN value, combined with engine information and vehicle status information, is used to determine whether the NOx emission data has "increased" compared to before the ECU fraud. If it has "increased" and does not meet the current emission requirements, an "emission violation" warning signal is output.

2. The ECU fraud warning method according to claim 1, characterized in that: If the saved CVN value does not belong to the engine factory CVN standard library, and the time and location corresponding to two consecutive CVN value acquisitions within the set calculation cycle are different, and at the same time, the CVN values ​​corresponding to other vehicles with the same ECU type as the current vehicle are the same, then the unexpected change in the ECU this time is "collective fraud." 3. The ECU fraud warning method according to claim 1, characterized in that: If the saved CVN value belongs to the standard database, and within the set calculation cycle, the corresponding positions of two consecutive CVN values ​​are the same, and the time deviation is within the set range, and at the same time, the CVN values ​​corresponding to other vehicles with the same ECU type as the current vehicle are the same, then the unexpected ECU change is a "centralized flash", that is, the ECU was flashed through a legal channel.

4. The ECU fraud warning method according to claim 1, characterized in that: If the saved CVN value belongs to the standard database, and within the set calculation cycle, the corresponding positions of two consecutive CVN values ​​are the same, and the time deviation is within the set range, then the unexpected change to the ECU is a "single flash", which means that the ECU was flashed through a legal channel.

5. The ECU fraud warning method according to claim 1, characterized in that: Situations that do not fall under "collective theft", "single theft", "collective fraud" and "single fraud" are all classified as "other".

6. The ECU fraud warning method according to claim 1, characterized in that: When the unexpected change in the ECU is "single fraud", "collective fraud" or "other", the system determines whether the NOx emission data has increased compared to before the ECU fraud. If it has increased and does not meet the current emission requirements, an "emission violation" warning signal is output.

7. The ECU fraud warning method according to claim 1, characterized in that: Determine whether the NOx emission data is "increased" compared to before the ECU was stolen. If it is "increased" but still meets the current emission requirements, no warning signal will be issued.

8. The ECU fraud warning method according to claim 1, characterized in that: Determine whether the NOx emission data has increased compared to before the ECU was stolen. If it has decreased, no warning signal will be issued. 9.ECU fraud warning system, characterized by: include: The first module is configured to: when an unexpected change occurs in the ECU, obtain the corresponding CVN value and related information at the time of the change, including the time and location of the unexpected change, the type of the ECU that has undergone the unexpected change, the corresponding engine type information, and NOx emission data; The second module is configured to compare the CVN value when the ECU undergoes an unexpected change with the CVN value when the ECU undergoes an unexpected change last time, and if the difference between the two exceeds a set value, save the CVN value corresponding to the current change and related information; The CVN jump classification processing module is configured to: if the stored CVN value does not belong to the engine factory CVN standard library, the unexpected change of the ECU is a "single fraud"; further, based on the corresponding time and location of two consecutive CVN values, it is determined whether the unexpected change of the ECU is a "group fraud"; The NOx classification module is configured to determine whether the NOx emission data has increased compared to before the ECU theft, based on the NOx emission data corresponding to the CVN value, combined with engine information and vehicle status information, when the unexpected change in the ECU is "single fraud" or "collective fraud". If the NOx emission data has increased and does not meet the current emission requirements, an "emission violation" warning signal will be output.

10. A motor vehicle, characterized in that: The vehicle-mounted computer is provided, and the vehicle-mounted computer executes the steps in the ECU fraud warning method according to any one of claims 1 to 8.

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