ECU integration evaluation method and computer readable storage medium

Abstract

The invention discloses an ECU integration evaluation method and a computer readable storage medium, and the method comprises the steps: carrying out the statistics of a message time interval corresponding to each ECU according to the message arrival time corresponding to each to-be-evaluated ECU, and carrying out the calculation of a message time interval corresponding to each ECU according to the message time interval corresponding to each ECU, a message theoretical period and a preset minimum message period, calculating a normalized standard deviation corresponding to each ECU; sorting is carried out according to the message ID of each ECU, and a first sorting sequence number corresponding to each ECU is determined; sorting is carried out according to the normalized standard deviation corresponding to each ECU, and a second sorting sequence number corresponding to each ECU is determined; and evaluating each ECU according to the first sorting sequence number and the second sorting sequence number corresponding to each ECU. When the ECU is integrated, the message sending period stability of the ECU can be accurately evaluated, so that the research and development quality of the ECU can be accurately evaluated.

Description

Technical Field

[0001] This invention relates to the field of electronic control unit (ECU) evaluation technology, and more particularly to an ECU integrated evaluation method and a computer-readable storage medium. Background Technology

[0002] With the continuous development of automotive intelligence, the number of in-vehicle electronic control units (ECUs) is increasing. These ECUs are connected via a CAN bus and communicate by sending CAN bus messages at fixed intervals. Individual ECUs are often developed, designed, and manufactured by OEMs (Original Equipment Manufacturers), and then integrated and tested by the vehicle manufacturer. During integration, due to the contention mechanism of the CAN bus, the periodic messages from different ECUs compete for priority. According to the CAN bus protocol, theoretically, messages with higher priority have the best real-time delivery guarantee, and therefore, their message transmission cycle is more stable. However, in reality, the R&D and manufacturing levels of different ECU OEMs vary, and CAN message transmission is often affected by unreasonable service scheduling, system lag delays, channel delays, power supply interference, etc., which may prevent them from maintaining a stable message transmission cycle.

[0003] When evaluating the stability of ECU message transmission cycles, OEMs can often guarantee stability during single-ECU testing because there is no bus contention. However, during integration testing, with numerous ECUs and intensified bus contention, the stability of ECU messages will inevitably decrease generally. Therefore, how to evaluate the cycle stability of ECU messages during integration testing has become a pressing issue and a key measure of an ECU OEM's R&D and manufacturing capabilities. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an ECU integration evaluation method and a computer-readable storage medium, which can accurately evaluate the stability of the message transmission cycle of the ECU during ECU integration, thereby accurately evaluating the R&D quality of the ECU.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: an ECU integration evaluation method, comprising:

[0006] Based on the message arrival time of each ECU to be evaluated, the message time interval of each ECU is statistically analyzed, and the normalized standard deviation of each ECU is calculated based on the message time interval, the theoretical message period, and the preset minimum message period.

[0007] Sort the messages according to the message ID of each ECU and determine the first sorting number corresponding to each ECU;

[0008] Sort the ECUs according to their normalized standard deviation and determine the second sorting number for each ECU.

[0009] Based on the first and second sorting numbers corresponding to each ECU, the message cycle stability of each ECU is evaluated.

[0010] The present invention also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0011] The beneficial effects of this invention are as follows: by determining the first sorting number based on ID priority and the second sorting number based on message cycle stability, by comparing the first sorting number and the second sorting number, it can be determined whether there is an ECU with high priority but low message cycle stability, thereby providing a basis for evaluating the quality of ECU development. Attached Figure Description

[0012] Figure 1 This is a flowchart of an ECU integration evaluation method according to the present invention;

[0013] Figure 2 This is a flowchart of the method according to Embodiment 1 of the present invention. Detailed Implementation

[0014] To explain the technical content, objectives, and effects of the present invention in detail, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0015] Please see Figure 1 An ECU integration evaluation method, comprising:

[0016] Based on the message arrival time of each ECU to be evaluated, the message time interval of each ECU is statistically analyzed, and the normalized standard deviation of each ECU is calculated based on the message time interval, the theoretical message period, and the preset minimum message period.

[0017] Sort the messages according to the message ID of each ECU and determine the first sorting number corresponding to each ECU;

[0018] Sort the ECUs according to their normalized standard deviation and determine the second sorting number for each ECU.

[0019] Each ECU is evaluated based on its first and second sorting numbers.

[0020] As can be seen from the above description, the beneficial effect of the present invention is that it can accurately evaluate the stability of the message transmission cycle of the ECU during ECU integration, thereby accurately evaluating the R&D quality of the ECU.

[0021] Furthermore, the ECUs to be evaluated are connected via a CAN bus;

[0022] The step of calculating the message time interval for each ECU based on the message arrival time of each ECU to be evaluated includes:

[0023] The CAN messages of each ECU to be evaluated are monitored by a bus listener, and the arrival time of each CAN message is obtained.

[0024] Based on the arrival time of each CAN message from the same ECU, the time interval between adjacent arrival times is calculated to obtain the message time interval corresponding to the same ECU.

[0025] As described above, the CAN bus enables the integration of various ECUs and facilitates the monitoring and statistical analysis of the time intervals of CAN messages from each ECU.

[0026] Further, the step of calculating the normalized standard deviation for each ECU based on the message time interval, theoretical message period, and preset minimum message period includes:

[0027] Calculate the average time interval for each ECU based on the message time interval for each ECU.

[0028] The normalized standard deviation is calculated for each ECU according to the formula for calculating the normalized standard deviation. The formula for calculating the normalized standard deviation is as follows:

[0029]

[0030] Where, σ i This represents the normalized standard deviation corresponding to the i-th ECU, sqrt() represents the square root calculation, and Te i T represents the theoretical message period corresponding to the i-th ECU. min T represents the preset minimum message period. ij This represents the time interval of the j-th message corresponding to the i-th ECU, where M represents the total number of message time intervals, and μ i This represents the average time interval corresponding to the i-th ECU.

[0031] As described above, calculating the normalized standard deviation helps to accurately assess the stability of the message cycle.

[0032] Furthermore, the step of sorting according to the message ID of each ECU to determine the first sorting sequence number corresponding to each ECU specifically involves:

[0033] Based on the decimal value of each ECU's message ID, sort each ECU from smallest to largest to obtain the first sorting number corresponding to each ECU.

[0034] As can be seen from the above description, the smaller the decimal value of the ID, the higher the ID priority.

[0035] Further, the step of sorting according to the normalized standard deviation corresponding to each ECU to determine the second sorting number corresponding to each ECU includes:

[0036] Based on the normalized standard deviation of each ECU, the ECUs are sorted from smallest to largest to obtain the second sorting number for each ECU.

[0037] Furthermore, the step of sorting according to the normalized standard deviation of each ECU to determine the second sorting number corresponding to each ECU also includes:

[0038] If there are two or more ECUs with the same normalized standard deviation, then the two or more ECUs are sorted according to the first sorting number corresponding to the two or more ECUs.

[0039] As described above, the second sorting number of each ECU is guaranteed to be unique.

[0040] Further, the evaluation of each ECU based on its corresponding first and second sorting numbers includes:

[0041] The tolerance value corresponding to the first ECU is determined based on the number of ECUs whose first sorting number differs from the first ECU by 1 and whose theoretical message cycle is the same.

[0042] If the first sorting number corresponding to the ECU is less than its corresponding second sorting number, and the difference between the second sorting number and the first sorting number corresponding to the ECU is greater than the tolerance value corresponding to the ECU, then the R&D quality of the ECU is determined to be unqualified.

[0043] As described above, by determining the tolerance value, it is possible to accommodate message IDs with similar priorities and the same cycle that may be missorted due to system noise or error; by determining whether the ECU has a high ID priority but low message cycle stability, a basis for evaluating the ECU development quality can be provided.

[0044] The present invention also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0045] Example 1

[0046] Please refer to Figure 2 The first embodiment of the present invention is: an ECU integration evaluation method, which can be used to evaluate the stability of the message transmission cycle of the ECU, thereby providing a basis for evaluating the quality of ECU development.

[0047] like Figure 2 As shown, it includes the following steps:

[0048] S1: Based on the message arrival time of each ECU to be evaluated, calculate the message time interval for each ECU.

[0049] Specifically, each ECU to be evaluated is physically connected via a CAN bus. After integration, the ECU is powered on and all CAN messages on the bus are monitored by a bus listener. The arrival time of each CAN message is buffered according to the ID in the CAN message (i.e., the ID of the CAN message sent by the ECU, which corresponds to the ECU). The time interval between CAN messages with the same ID is counted sequentially according to the arrival order of the messages, thus obtaining the message time interval corresponding to the same ECU.

[0050] S2: Calculate the normalized standard deviation for each ECU based on the message time interval, theoretical message period, and preset minimum message period.

[0051] Specifically, the average time interval for each ECU is calculated based on the message time interval for each ECU. The formula for calculating the average time interval is as follows:

[0052]

[0053] Where, μ i T represents the average time interval corresponding to the i-th ECU. ij M represents the time interval of the j-th message corresponding to the i-th ECU (equivalent to the duration of the j-th cycle), and M represents the total number of message time intervals.

[0054] Then, the normalized standard deviation of each ECU's message after conversion to the minimum cycle time is calculated. The formula for calculating the normalized standard deviation is:

[0055]

[0056] Where, σ i This represents the normalized standard deviation corresponding to the i-th ECU, sqrt() represents the square root calculation, and Te i T represents the theoretical message period corresponding to the i-th ECU. min This indicates the preset minimum message period (usually 10ms).

[0057] S3: Sort according to the message ID of each ECU and determine the first sorting number corresponding to each ECU.

[0058] Specifically, based on the CAN ID contention principle, the IDs are sorted first according to their priority (the smaller the decimal value of the ID, the higher the priority), thus obtaining the first sorting number Rank1 for each CAN message ID. i .

[0059] S4: Sort according to the normalized standard deviation of each ECU and determine the second sorting number for each ECU.

[0060] Specifically, based on the normalized standard deviation calculated in step S2, a second sorting is performed from smallest to largest to obtain the first sorting number Rank2 for the priority of each CAN message ID. i .

[0061] Furthermore, if there are IDs with the same normalized standard deviation, then the IDs with the same normalized standard deviation are sorted in the second sort according to the first sorting number (i.e. ID priority), and the ID with higher priority is sorted first in the second sort.

[0062] S5: Evaluate each ECU based on its first and second sorting numbers.

[0063] Specifically, the tolerance value for each ECU is first determined. For example, for the i-th ECU, the number of ECUs whose first sorting number differs from its first sorting number by 1 and whose theoretical message cycle is the same is obtained, and this number is taken as its corresponding tolerance value C. i Determining the tolerance value is to ensure compatibility with message IDs of similar priority and the same period caused by sorting errors due to measurement system noise or errors.

[0064] Then, based on the following rules, determine whether there is a problem with the message cycle stability level of the i-th ECU:

[0065] Rank1 i <Rank2 i And Rank2 i -Rank1 i >C i

[0066] If this condition is met, it indicates that the priority of this CAN ID is lower than that of other IDs in the vehicle. It should have an advantage in bus competition, but it is not as good as other low-priority IDs in terms of message cycle stability. Therefore, there are problems with the R&D and design of the bus transceiver of this ECU, and it needs to be returned to the OEM for optimization and modification to improve the message cycle stability.

[0067] This embodiment utilizes bus contention priority to compare message cycle stability. During the vehicle ECU integration testing phase, it statistically analyzes the relationship between bus message cycle stability and message priority over a period of time to determine whether there are ECUs with high priority but low stability, thus providing a basis for evaluating ECU development quality. This helps identify ECUs with design problems from a large number of messages with varying cycles during ECU integration, thereby urging ECU OEMs to make improvements.

[0068] Example 2

[0069] This embodiment is a computer-readable storage medium corresponding to the above embodiments, on which a computer program is stored. When the program is executed by a processor, it implements the various steps of an ECU integration evaluation as described in the above embodiments and can achieve the same technical effect, which will not be repeated here.

[0070] In summary, the ECU integration evaluation method and computer-readable storage medium provided by this invention determine a first sorting number based on ID priority and a second sorting number based on message cycle stability. By comparing the first and second sorting numbers, it can determine whether there are ECUs with high priority but low stability, thereby providing a basis for evaluating the quality of ECU development. This helps to identify ECUs with design problems from a large number of messages with different cycles during ECU integration, thereby urging ECU OEMs to make improvements.

[0071] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An ECU integration evaluation method, characterized in that, include: Based on the message arrival time of each ECU to be evaluated, the message time interval of each ECU is statistically analyzed, and the normalized standard deviation of each ECU is calculated based on the message time interval, the theoretical message period, and the preset minimum message period. Sort the messages according to the message ID of each ECU and determine the first sorting number corresponding to each ECU; Sort the ECUs according to their normalized standard deviation and determine the second sorting number for each ECU. Each ECU is evaluated based on its first and second sorting numbers.

2. The ECU integration evaluation method according to claim 1, characterized in that, The ECUs to be evaluated are connected via a CAN bus; The step of calculating the message time interval for each ECU based on the message arrival time of each ECU to be evaluated includes: The CAN messages of each ECU to be evaluated are monitored by a bus listener, and the arrival time of each CAN message is obtained. Based on the arrival time of each CAN message from the same ECU, the time interval between adjacent arrival times is calculated to obtain the message time interval corresponding to the same ECU.

3. The ECU integration evaluation method according to claim 1, characterized in that, The step of calculating the normalized standard deviation for each ECU based on the message time interval, theoretical message period, and preset minimum message period includes: Calculate the average time interval for each ECU based on the message time interval for each ECU. The normalized standard deviation is calculated for each ECU according to the formula for calculating the normalized standard deviation. The formula for calculating the normalized standard deviation is as follows: Where, σ i This represents the normalized standard deviation corresponding to the i-th ECU, sqrt() represents the square root calculation, and Te i T represents the theoretical message period corresponding to the i-th ECU. min T represents the preset minimum message period. ij This represents the time interval of the j-th message corresponding to the i-th ECU, where M represents the total number of message time intervals, and μ i This represents the average time interval corresponding to the i-th ECU.

4. The ECU integration evaluation method according to claim 1, characterized in that, The step of sorting according to the message ID of each ECU to determine the first sorting sequence number corresponding to each ECU is as follows: Based on the decimal value of each ECU's message ID, sort each ECU from smallest to largest to obtain the first sorting number corresponding to each ECU.

5. The ECU integration evaluation method according to claim 1, characterized in that, The step of sorting according to the normalized standard deviation of each ECU to determine the second sorting number for each ECU includes: Based on the normalized standard deviation of each ECU, the ECUs are sorted from smallest to largest to obtain the second sorting number for each ECU.

6. The ECU integration evaluation method according to claim 5, characterized in that, The step of sorting according to the normalized standard deviation of each ECU and determining the second sorting number for each ECU also includes: If there are two or more ECUs with the same normalized standard deviation, then the two or more ECUs are sorted according to the first sorting number corresponding to the two or more ECUs.

7. The ECU integration evaluation method according to claim 1, characterized in that, The evaluation of each ECU based on its first and second sorting numbers includes: The tolerance value corresponding to the first ECU is determined based on the number of ECUs whose first sorting number differs from that of the first ECU by 1 and whose theoretical message cycle is the same. If the first sorting number corresponding to the ECU is less than its corresponding second sorting number, and the difference between the second sorting number and the first sorting number corresponding to the ECU is greater than the tolerance value corresponding to the ECU, then the R&D quality of the ECU is determined to be unqualified.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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