Diagnostic communication separation time optimization method and device, receiving end and sending end

Abstract

The invention relates to the technical field of communication, in particular to a diagnostic communication partition time optimization method and device, a receiving end and a sending end, and the method comprises the steps: obtaining historical data transmitted by the sending end at the current partition time in a diagnostic communication process; generating target segmentation time according to the current processing capability of the receiving end and historical data; the target segmentation time is fed back to the sending end, and the sending end optimizes the current segmentation time based on the target segmentation time. Therefore, the problems of low communication efficiency, poor stability and the like existing in the prior art in which the data is received and processed by setting the fixed minimum separation time are solved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device, receiving end, and transmitting end for optimizing diagnostic communication separation time. Background Art

[0002] With the increasing complexity of automotive diagnostic functions and the increasing number of ECUs (Electronic Control Units), diagnostic communication protocols have become widely used in automotive electronic systems. These protocols transmit large amounts of data over the network, ensuring timely vehicle function diagnosis and fault handling. However, due to differences in the hardware capabilities and operating loads of different ECUs, the fixed minimum separation time (STmin) configuration in related technologies is difficult to adapt to all scenarios, which may lead to inefficient data transmission or overload on the receiving end. Summary of the Invention

[0003] The present application provides a diagnostic communication separation time optimization method, device, receiving end and transmitting end to solve the problems of low communication efficiency and poor stability in the related art of receiving and processing data by setting a fixed minimum separation time.

[0004] The first aspect of the present application provides a method for optimizing the separation time of diagnostic communications, which is applied to a receiving end and includes the following steps: obtaining historical data sent by a sending end at a current separation time during a diagnostic communication process; generating a target separation time based on the current processing capability of the receiving end and the historical data; and feeding back the target separation time to the sending end, wherein the sending end optimizes the current separation time based on the target separation time.

[0005] Optionally, the target segmentation time is generated based on the current processing capacity of the receiving end and historical data, including: extracting the processing time of each data frame in the historical data; calculating the mean and standard deviation based on the processing time of each data frame; and determining the target segmentation time based on the current processing capacity, mean and standard deviation.

[0006] Optionally, the target segmentation time is directly proportional to the current processing capacity.

[0007] Optionally, before generating the target segmentation time based on the current processing capability of the receiving end and historical data, it also includes: counting the total number of records of the processing time of data frames in the historical data; if the total number of records is greater than the number threshold, generating the target segmentation time based on the current processing capability of the receiving end and historical data.

[0008] Optionally, before generating the target split time according to the current processing capability of the receiving end and historical data, the method further includes: acquiring load data and hardware configuration data of the receiving end; and determining the current processing capability of the receiving end according to the load data and hardware configuration data.

[0009] The second aspect of the present application provides a method for optimizing the separation time of diagnostic communications, which is applied to a transmitting end and includes the following steps: sending historical data to a receiving end at a current separation time during a diagnostic communication process, wherein the receiving end generates a target separation time based on the current processing capability of the receiving end and the historical data; obtaining the target separation time sent by the receiving end; and optimizing the current separation time based on the target separation time.

[0010] The third aspect of the present application provides a diagnostic communication separation time optimization device, which is applied to a receiving end and includes: a first acquisition module, used to obtain historical data sent by a sending end at a current separation time during a diagnostic communication process; a generation module, used to generate a target separation time based on the current processing capability of the receiving end and historical data; a feedback module, used to feed back the target separation time to the sending end, wherein the sending end optimizes the current separation time based on the target separation time.

[0011] Optionally, the generation module is further used to extract the processing time of each data frame in the historical data; calculate the mean and standard deviation based on the processing time of each data frame; determine the target segmentation time based on the current processing capacity, mean and standard deviation

[0012] Optionally, the target segmentation time is directly proportional to the current processing capacity.

[0013] Optionally, the diagnostic communication separation time optimization device also includes: a statistical module, which is used to count the total number of records of the processing time of data frames in the historical data before generating the target separation time based on the current processing capability of the receiving end and the historical data; if the total number of records is greater than the quantity threshold, the target separation time is generated based on the current processing capability of the receiving end and the historical data.

[0014] Optionally, the diagnostic communication separation time optimization device also includes: a determination module, which is used to obtain the load data and hardware configuration data of the receiving end before generating the target separation time based on the current processing capacity and historical data of the receiving end; and determine the current processing capacity of the receiving end based on the load data and hardware configuration data.

[0015] The fourth aspect of the present application provides a diagnostic communication separation time optimization device, which is applied to the sending end and includes: a sending module, which is used to send historical data to the receiving end at the current separation time during the diagnostic communication process, wherein the receiving end generates a target separation time based on the current processing capability of the receiving end and the historical data; a second acquisition module, which is used to obtain the target separation time sent by the receiving end; and an optimization module, which is used to optimize the current separation time based on the target separation time.

[0016] The fifth aspect of the present application provides a receiving end, including: a memory, a processor, and a computer program stored in the memory and runnable on the processor, and the processor executes the program to implement the diagnostic communication separation time optimization method as described in the above embodiment.

[0017] The sixth aspect of the present application provides a transmitting end, including: a memory, a processor, and a computer program stored in the memory and runnable on the processor, and the processor executes the program to implement the diagnostic communication separation time optimization method as described in the above embodiment.

[0018] Therefore, this application has the following beneficial effects:

[0019] The embodiments of the present application can determine a target segmentation time based on the current processing capacity of the receiving end and historical data, and send the target segmentation time to the transmitting end. The transmitting end can then adjust the transmission interval of consecutive frames in real time, thereby achieving efficient and reliable diagnostic communication. This fully utilizes the processing capacity of the receiving end without increasing hardware costs, improving communication efficiency and stability. This solves the problems of low communication efficiency and poor stability that exist in related technologies that rely on setting a fixed minimum segmentation time to achieve data reception and processing.

[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 A flowchart of a method for optimizing diagnostic communication separation time according to an embodiment of the present application is provided;

[0023] Figure 2 A flowchart of another method for optimizing the diagnostic communication separation time provided according to an embodiment of the present application;

[0024] Figure 3 A block diagram of a diagnostic communication separation time optimization device provided according to an embodiment of the present application;

[0025] Figure 4 This is a block diagram of another diagnostic communication separation time optimization device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0027] The following describes the diagnostic communication separation time optimization method, device, receiving end, and transmitting end of the embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a diagnostic communication separation time optimization method. In this method, the target separation time is determined based on the current processing power and historical data of the receiving end, and the target separation time is sent to the transmitting end. The transmitting end can adjust the transmission time interval of consecutive frames in real time, thereby achieving efficient and reliable diagnostic communication. In this way, without increasing the hardware cost, the processing power of the receiving end is fully utilized, and the communication efficiency and communication stability are improved. As a result, the problems of low communication efficiency and poor stability in the related art of receiving and processing data by setting a fixed minimum separation time are solved.

[0028] Specifically, Figure 1 A flowchart of a method for optimizing diagnostic communication separation time provided in an embodiment of the present application is provided.

[0029] like Figure 1 As shown, the diagnostic communication separation time optimization method is applied to the receiving end and includes the following steps:

[0030] In step S101 , historical data sent by the sending end at the current split time during the diagnostic communication process is obtained.

[0031] Understandably, during the system development phase, the sender can configure a wide fixed STmin value to ensure stable communication. For high-performance CPUs, the STmin value should be set to 5ms–10ms to ensure efficient communication. For medium-performance CPUs, the STmin value should be set to 10ms–20ms to balance efficiency and processing power. For highly loaded systems or during the debugging phase, the STmin value should be set to 20ms–50ms to improve fault tolerance and avoid communication anomalies. Therefore, when the processing power of the receiver is unknown, a fixed STmin value can ensure stable communication and provide a foundation for subsequent dynamic optimization.

[0032] In some embodiments, the present application may establish a 1ms task cycle at the transmitting end for executing CanTp_MainFunction, ensuring that continuous frame transmission can be dynamically adjusted with a granularity of 1ms.

[0033] In step S102, a target split time is generated according to the current processing capability of the receiving end and historical data.

[0034] Among them, the target segmentation time is directly proportional to the current processing capacity.

[0035] In one embodiment of the present application, a target segmentation time is generated based on the current processing capability of the receiving end and historical data, including: extracting the processing time of each data frame in the historical data; calculating the mean and standard deviation based on the processing time of each data frame; and determining the target segmentation time based on the current processing capability, mean, and standard deviation.

[0036] It can be understood that the embodiments of the present application can record the time of data parsing, storage and processing after receiving historical data at the receiving end, record the timestamps at the start and end points of frame reception, calculate the total processing time of a single frame, and complete the data storage, parsing and processing logic, and record the end time of processing.

[0037] Furthermore, embodiments of the present application can fit a normal distribution based on the processing time of each data frame, calculate the mean and standard deviation, and then generate a dynamic STmin value (i.e., the target segmentation time). Assuming that the processing time at the receiving end conforms to the normal distribution characteristics, the distribution parameters and statistical methods are used to calculate the 99th percentile value as the predicted worst-case STmin value.

[0038] For example, when receiving each data frame, the receiving end records the time consumed from receiving the frame to completing processing as a processing time sample, and stores the latest N (eg, N=50) processing time samples in a circular buffer.

[0039] Regularly collect statistics on the processing time samples in the circular buffer and calculate their mean μ (mean) and standard deviation σ (standard deviation), namely:

[0040]

[0041] where t i is the processing time of the i-th history record.

[0042] Furthermore, embodiments of the present application can combine current processing capacity parameters (such as CPU utilization, task priority, hardware configuration, etc.) to adopt a probabilistic prediction mechanism to determine the target segmentation time. For example, assuming that the processing time follows a normal distribution, the 99% percentile can be taken as the target segmentation time, and the formula is as follows:

[0043] T target =μ+k·σ

[0044] Where k is the Z value corresponding to the quantile (for example, k = 2.33 for the 99% quantile), T targetis the target split time. If the system is currently loaded with high load or has reduced processing capacity, an adjustment factor α (0<α≤1) can be introduced:

[0045] T target =α·(μ+k·σ)

[0046] Among them, α can be dynamically adjusted according to the real-time collected CPU load, memory usage and other indicators to ensure that the target segmentation time can flexibly reflect the current processing capacity. The calculated target segmentation time T target , through mechanisms such as flow control frames, real-time feedback is given to the sender, guiding the sender to adjust the interval between consecutive frame transmissions, thus achieving adaptive optimization of diagnostic communication.

[0047] In one embodiment of the present application, before generating the target segmentation time based on the current processing capability of the receiving end and historical data, it also includes: counting the total number of records of the processing time of the data frames in the historical data; if the total number of records is greater than the number threshold, generating the target segmentation time based on the current processing capability of the receiving end and historical data.

[0048] The quantity threshold can be set according to actual conditions, such as 50, without any specific limitation.

[0049] It can be understood that the embodiment of the present application can store the recorded processing time in a circular buffer. When the number of records in the buffer reaches 50, the maximum value, average value or other distribution indicators are statistically generated as the basis for dynamically generating the STmin value to ensure that the calculation results are reasonable and stable.

[0050] In one embodiment of the present application, before generating the target split time according to the current processing capability and historical data of the receiving end, it also includes: obtaining the load data and hardware configuration data of the receiving end; and determining the current processing capability of the receiving end according to the load data and hardware configuration data.

[0051] It is understandable that when the receiving end has strong hardware performance, a fixed large STmin value will limit the data transmission speed, resulting in a waste of resources. When the receiving end has a high load or weak hardware performance, a fixed small STmin value may make it difficult for the receiving end to handle the data, resulting in communication interruption or data loss. The embodiments of the present application can determine the current processing capacity of the receiving end based on the hardware configuration data and load of the receiving end, and optimize the data frame transmission interval based on the current processing capacity of the receiving end, thereby improving communication efficiency and enhancing system stability.

[0052] In step S103, the target segmentation time is fed back to the sending end, wherein the sending end optimizes the current segmentation time based on the target segmentation time.

[0053] The embodiment of the present application dynamically adjusts the STmin value of the diagnostic communication and feeds the STmin value back to the sending end so that it can adapt to the actual processing capability of the receiving end. The sending end accurately adjusts the time interval for sending consecutive frames based on the dynamic STmin value provided by the receiving end, thereby improving the efficiency and robustness of the diagnostic communication.

[0054] It should be noted that after multiple rounds of data transmission, processing time statistics are regularly updated to further optimize the STmin value. In actual implementation, the embodiments of this application can use tools such as CANalyzer or CANoe to verify the optimized STmin configuration: check whether the frame transmission interval meets the STmin value fed back by the receiver. This verifies the stability of the optimization solution under different load conditions.

[0055] Secondly, referring to another diagnostic communication separation time optimization method provided in the embodiment of the present application, the method is applied to the sending end, such as Figure 2 As shown, the following steps are included:

[0056] In step S201 , historical data is sent to a receiving end at a current split time during a diagnostic communication process, wherein the receiving end generates a target split time according to the current processing capability of the receiving end and the historical data.

[0057] In step S202, the target split time sent by the receiving end is obtained.

[0058] In step S203, the current segmentation time is optimized based on the target segmentation time.

[0059] The embodiments of the present application overcome the limitations of fixed STmin in related technologies by dynamically adjusting the STmin value, significantly improving the efficiency and stability of diagnostic communications. Specifically, by dynamically generating the STmin value, it adapts to different operating conditions based on the actual data processing capabilities of the receiving end and historical statistical analysis. When the load is high or the hardware performance is insufficient, STmin is automatically increased to avoid overload; when the load is light, STmin is reduced to improve communication efficiency. This mechanism not only improves the utilization of communication bandwidth, but also enhances the stability of the system under extreme loads. Through a data-driven optimization mechanism, the embodiments of the present application can dynamically adjust according to real-time measurement data to ensure the scientificity and accuracy of the STmin value. In addition, the dynamic adjustment mechanism is compatible with the existing ISO 15765-2 standard and has good scalability. It is applicable to a variety of hardware performance and communication protocols, such as CAN FD and Ethernet protocols. Overall, it not only solves the shortcomings of fixed STmin, but also significantly improves the flexibility and adaptability of diagnostic communications through automatic optimization and self-adaptation capabilities, and has broad application prospects and practical value.

[0060] According to the diagnostic communication interval optimization method proposed in the embodiments of this application, a target interval is determined based on the current processing power of the receiving end and historical data. This target interval is then sent to the transmitting end, enabling the transmitting end to adjust the interval between consecutive frames in real time, thereby achieving efficient and reliable diagnostic communication. This method fully utilizes the processing power of the receiving end, improves communication efficiency, and enhances system stability without increasing hardware costs.

[0061] Next, a diagnostic communication separation time optimization device proposed according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0062] Figure 3 3 is a block diagram of a diagnostic communication separation time optimization device according to an embodiment of the present application, which is applied to a receiving end.

[0063] like Figure 3 As shown, the diagnostic communication separation time optimization device 10 includes: a first acquisition module 101 , a generation module 102 and a feedback module 103 .

[0064] Among them, the first acquisition module 101 is used to obtain the historical data sent by the sending end at the current segmentation time during the diagnostic communication process; the generation module 102 is used to generate the target segmentation time based on the current processing capability and historical data of the receiving end; the feedback module 103 is used to feed back the target segmentation time to the sending end, wherein the sending end optimizes the current segmentation time based on the target segmentation time.

[0065] In one embodiment of the present application, the generation module 102 is further configured to extract the processing time of each data frame in the historical data; calculate the mean and standard deviation based on the processing time of each data frame; and determine the target segmentation time based on the current processing capacity, the mean and the standard deviation.

[0066] In one embodiment of the present application, the target segmentation time is directly proportional to the current processing capacity.

[0067] In one embodiment of the present application, the diagnostic communication separation time optimization device 10 also includes: a statistical module, which is used to count the total number of records of processing time of data frames in historical data before generating a target separation time based on the current processing capability of the receiving end and historical data; if the total number of records is greater than a quantity threshold, the target separation time is generated based on the current processing capability of the receiving end and historical data.

[0068] In one embodiment of the present application, the diagnostic communication separation time optimization device 10 also includes: a determination module, which is used to obtain the load data and hardware configuration data of the receiving end before generating the target separation time based on the current processing capacity and historical data of the receiving end; and determine the current processing capacity of the receiving end based on the load data and hardware configuration data.

[0069] Another embodiment of the present application further provides a diagnostic communication separation time optimization device, which is applied to the sending end, such as Figure 4 As shown, it includes: a sending module 201, a second obtaining module 202 and an optimizing module 203.

[0070] Among them, the sending module 201 is used to send historical data to the receiving end at the current segmentation time during the diagnostic communication process, wherein the receiving end generates a target segmentation time based on the current processing capability of the receiving end and the historical data; the second acquisition module 202 is used to obtain the target segmentation time sent by the receiving end; the optimization module 203 is used to optimize the current segmentation time based on the target segmentation time.

[0071] It should be noted that the above explanations of the embodiment of the diagnostic communication separation time optimization method are also applicable to the diagnostic communication separation time optimization device of this embodiment, and will not be repeated here.

[0072] According to the diagnostic communication interval optimization device proposed in the embodiments of this application, a target interval is determined based on the current processing power of the receiving end and historical data. This target interval is then sent to the transmitting end, enabling the transmitting end to adjust the interval between consecutive frames in real time, thereby achieving efficient and reliable diagnostic communication. This fully utilizes the processing power of the receiving end, improves communication efficiency, and enhances system stability without increasing hardware costs.

[0073] In addition, an embodiment of the present application also provides a receiving end, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the diagnostic communication separation time optimization method as described in the above embodiment.

[0074] An embodiment of the present application also provides a transmitting end, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the diagnostic communication separation time optimization method as described in the above embodiment.

[0075] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0076] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0077] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0078] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, the steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement the method: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0079] A person skilled in the art may understand that all or part of the steps carried out in the method for implementing the above-mentioned embodiment may be completed by instructing the relevant hardware through a program, and the above-mentioned program may be stored in a computer-readable storage medium, which, when executed, includes one of the steps of the method embodiment or a combination thereof.

[0080] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for optimizing the separation time of diagnostic communication, characterized in that: The method is applied to a receiving end, wherein the method comprises the following steps: Obtain historical data sent by the sender at the current split time during the diagnostic communication process; generating a target segmentation time according to the current processing capability of the receiving end and the historical data; The target segmentation time is fed back to the transmitting end, wherein the transmitting end optimizes the current segmentation time based on the target segmentation time.

2. The diagnostic communication separation time optimization method according to claim 1, characterized in that: Generating the target segmentation time according to the current processing capability of the receiving end and the historical data includes: Extracting the processing time of each data frame in the historical data; Calculate the mean and standard deviation based on the processing time of each data frame; The target segmentation time is determined according to the current processing capability, the mean value, and the standard deviation.

3. The diagnostic communication separation time optimization method according to claim 2, characterized in that: The target segmentation time is directly proportional to the current processing capacity.

4. The diagnostic communication separation time optimization method according to claim 2, characterized in that: Before generating the target split time according to the current processing capability of the receiving end and the historical data, the method further includes: Counting the total number of records of processing time of data frames in the historical data; If the total number of records is greater than the number threshold, a target segmentation time is generated according to the current processing capability of the receiving end and the historical data.

5. The diagnostic communication separation time optimization method according to any one of claims 1 to 4, characterized in that: Before generating the target split time according to the current processing capability of the receiving end and the historical data, the method further includes: Obtaining load data and hardware configuration data of the receiving end; The current processing capability of the receiving end is determined according to the load data and the hardware configuration data.

6. A method for optimizing the separation time of diagnostic communication, characterized in that: The method is applied to a transmitting end, wherein the method comprises the following steps: sending historical data to a receiving end at a current split time during a diagnostic communication process, wherein the receiving end generates a target split time based on a current processing capability of the receiving end and the historical data; Obtaining the target split time sent by the receiving end; The current segmentation time is optimized based on the target segmentation time.

7. A diagnostic communication separation time optimization device, characterized in that: The device is applied to a receiving end, wherein the device includes: The first acquisition module is used to acquire historical data sent by the sending end at the current split time during the diagnostic communication process; A generating module, configured to generate a target segmentation time according to the current processing capability of the receiving end and the historical data; A feedback module is configured to feed back the target segmentation time to the sending end, wherein the sending end optimizes the current segmentation time based on the target segmentation time.

8. A diagnostic communication separation time optimization device, characterized in that: The device is applied to a transmitting end, wherein the device includes: a sending module, configured to send historical data to a receiving end at a current split time during a diagnostic communication process, wherein the receiving end generates a target split time based on a current processing capability of the receiving end and the historical data; A second acquisition module is used to acquire the target segmentation time sent by the receiving end; An optimization module is configured to optimize the current segmentation time based on the target segmentation time.

9. A receiving end, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the diagnostic communication separation time optimization method according to any one of claims 1 to 5.

10. A transmitting end, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the diagnostic communication separation time optimization method according to claim 6.

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