Data acquisition device and data acquisition system

Abstract

The invention discloses a data acquisition device and a data acquisition system, the data acquisition device comprises a first chip, a second chip, a first operation system, a second operation system, a data acquisition module and a data processing module, the first chip runs on the first chip, the first chip is connected with an electronic control unit (ECU) of a vehicle through a bus of the vehicle, and the first operation system is used for scheduling the first chip to acquire ECU data of the vehicle; a second operating system runs on the second chip, the second chip is connected with the first chip, and the second operating system is used for scheduling the second chip to obtain the ECU data from the first chip so as to monitor the working performance of the vehicle. According to the scheme, a dual-chip dual-system architecture is arranged in the data acquisition equipment, the first operating system (such as RTOS) can process ECU data acquisition and transmission with high real-time requirements, and the second operating system (such as Linux) is used for processing ECU data. The layered design helps the data acquisition equipment to meet the requirements of high-real-time data transmission and high-complexity data processing, and the stability is improved.

Description

Technical Field

[0001] The present application relates to the technical field of data acquisition, and more specifically, to a data acquisition device and a data acquisition system. Background Art

[0002] As vehicles become increasingly digital, intelligent, and networked, they are equipped with a large number of electronic control units (ECUs). During the entire life cycle of vehicle development and after-sales, how to collect ECU data and use ECU data to monitor the vehicle's working performance has become a research hotspot in the vehicle industry.

[0003] There are many types of vehicle data acquisition devices on the market (CANoe, PCAN-USB Pro, Memorator Pro, etc.), but they all have shortcomings. For example, CANoe is complex to operate and needs to be bound to corresponding software, which makes it lack flexibility and scalability. For another example, PCAN-USB Pro only supports the separate acquisition of data from a specific bus, which makes it lack flexibility and scalability. For another example, Memorator Pro cannot meet the needs of highly complex data processing. Summary of the invention

[0004] The embodiment of the present application provides a data acquisition device and a data acquisition system. The data acquisition device and the data acquisition system involved in the embodiment of the present application are introduced below.

[0005] In a first aspect, a data acquisition device is provided, comprising: a first chip, on which a first operating system runs, the first chip is connected to an electronic control unit ECU of a vehicle through a bus of the vehicle, and the first operating system is used to schedule the first chip to collect ECU data of the vehicle; a second chip, on which a second operating system runs, the second chip is connected to the first chip, and the second operating system is used to schedule the second chip to obtain the ECU data from the first chip to monitor the working performance of the vehicle.

[0006] As a possible implementation, the data acquisition device further includes: an integrated circuit for carrying the first chip and the second chip, wherein a storage unit is provided on the integrated circuit, and the first chip and the second chip share a storage space of the storage unit.

[0007] As a possible implementation, the second chip is connected to a target cloud platform, and the second chip is used to send the ECU data to the target cloud platform so as to monitor the working performance of the vehicle using the target cloud platform.

[0008] As a possible implementation manner, the second chip is also used to: if the communication quality between the second chip and the target cloud platform is less than a preset threshold, store the ECU data to be sent to the target cloud platform.

[0009] As a possible implementation method, the second chip is also used to send the device information of the data acquisition device to the target cloud platform, and receive the device certificate of the data acquisition device sent from the target cloud platform; the data acquisition device also includes: an integrated hardware security module for storing the device certificate.

[0010] As a possible implementation manner, the second chip is connected to a user device, and the second chip is used to send the ECU data to the user device, so as to monitor the working performance of the vehicle using the user device.

[0011] As a possible implementation, the integrated circuit is a field programmable gate array (FPGA) integrated circuit.

[0012] As a possible implementation, the first operating system is a real-time operating system RTOS, and the second operating system is a Linux operating system.

[0013] In a second aspect, a data acquisition system is provided, including a data acquisition device and a target cloud platform, the data acquisition device is connected to the target cloud platform, and the data acquisition device includes: a first chip, a first operating system running on the first chip, the first chip is connected to the electronic control unit ECU of the vehicle through the vehicle's bus, and the first operating system is used to schedule the first chip to collect the ECU data of the vehicle; a second chip, a second operating system running on the second chip, the second chip is connected to the first chip, and the second operating system is used to schedule the second chip to obtain the ECU data from the first chip, and schedule the second chip to send the ECU data to the target cloud platform, so as to use the target cloud platform to monitor the working performance of the vehicle.

[0014] As a possible implementation, the data acquisition device further includes: an integrated circuit for carrying the first chip and the second chip, wherein a storage unit is provided on the integrated circuit, and the first chip and the second chip share a storage space of the storage unit.

[0015] As a possible implementation method, the target cloud platform is also used to perform target processing operations on the ECU data to obtain target ECU data, and monitor the working performance of the vehicle based on the target ECU data; the target processing operations include one or more of the following: feature extraction processing on the ECU data; decoding operation processing on the ECU data; data cleaning processing on the ECU data.

[0016] As a possible implementation manner, the target cloud platform is also used to: store the target ECU data in a data lake or a data warehouse according to the monitoring scenario of the vehicle.

[0017] As a possible implementation method, the target cloud platform is used to generate a visual analysis chart of the ECU based on the storage structure of the target ECU data and using target screening conditions.

[0018] As a possible implementation manner, the second chip is also used to: if the communication quality between the second chip and the target cloud platform is less than a preset threshold, store the ECU data to be sent to the target cloud platform.

[0019] As a possible implementation method, the second chip is also used to send the device information of the data acquisition device to the target cloud platform, and receive the device certificate of the data acquisition device sent from the target cloud platform; the data acquisition device also includes: an integrated hardware security module for storing the device certificate.

[0020] As a possible implementation method, the target cloud platform is also used to: receive the ECU data sent from a third-party data acquisition device, and use the target cloud platform to monitor the working performance of the vehicle.

[0021] As a possible implementation, the integrated circuit is a field programmable gate array (FPGA) integrated circuit.

[0022] As a possible implementation, the first operating system is a real-time operating system RTOS, and the second operating system is a Linux operating system.

[0023] The present application provides a data acquisition device, comprising: a first chip, a first operating system running on the first chip, the first chip is connected to the electronic control unit ECU of the vehicle through the bus of the vehicle, and the first operating system is used to schedule the first chip to collect the ECU data of the vehicle; a second chip, a second operating system running on the second chip, the second chip is connected to the first chip, and the second operating system is used to schedule the second chip to obtain ECU data from the first chip to monitor the working performance of the vehicle. This solution sets up a dual-chip dual-system architecture in the data acquisition device, the first operating system (such as RTOS) can handle ECU data acquisition and transmission with high real-time requirements, and the second operating system (such as Linux) is used to process ECU data. This layered design helps the data acquisition device meet the requirements of high real-time data transmission and high-complexity data processing, and the data acquisition device has high flexibility and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a structural diagram of a data acquisition device provided in one embodiment of the present application.

[0025] Figure 2 It is a structural diagram of a data acquisition device provided in another embodiment of the present application.

[0026] Figure 3 It is a structural diagram of a data acquisition system provided in one embodiment of the present application.

[0027] Figure 4 It is a structural diagram of a data acquisition system provided in another embodiment of the present application.

[0028] Figure 5 It is a schematic diagram of the business architecture of the data acquisition system provided in one embodiment of the present application.

[0029] Figure 6 It is a schematic diagram of the data flow of the data acquisition system provided in one embodiment of the present application.

[0030] Figure 7 It is a flowchart of the entire life cycle of a data acquisition system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present application should fall within the scope of protection of the present application.

[0032] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0033] In the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention; the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance; in addition, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection; it can be directly connected or indirectly connected through an intermediate medium, it can be the internal connection of two elements; it can be an electrical connection or a communication connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0034] As vehicles become more digital, intelligent, and networked, they are equipped with a large number of ECUs, which communicate data through various buses (such as CAN, LIN, FlexRay, and Ethernet). During the entire life cycle of vehicle development and after-sales, more and more problems have arisen with ECUs, and vehicle manufacturers and suppliers are paying more and more attention to the collection of vehicle operation data. Therefore, reliably and efficiently collecting and processing bus data between multiple ECUs has become an important topic in the field of vehicle electronics.

[0035] There are three main types of existing vehicle bus data acquisition devices: traditional data acquisition devices (such as CANoe), independent data acquisition instruments (such as PCAN-USB Pro), and data acquisition systems that support multiple interfaces (such as Memorator Pro), etc.

[0036] Traditional data acquisition devices, represented by CANoe, collect data with independent hardware and software systems by directly connecting to the vehicle bus. CANoe can be connected to a personal computer (PC) via USB and use a graphical user interface to display and analyze data. The operation of CANoe is relatively complex, and its hardware and software systems need to be bound together, which is costly and lacks flexibility and scalability.

[0037] Independent data acquisition instruments represented by PCAN-USB Pro are mainly used to collect data from a specific bus, which makes them lack flexibility and scalability.

[0038] Multi-interface data acquisition systems represented by Memorator Pro include multiple input interfaces, and their software architecture is usually divided into underlying drivers and upper-level applications. Compared with the former two, this type of device has improved scalability, but lacks real-time data processing, parsing, query, analysis and visualization capabilities, and cannot meet the needs of highly complex data processing.

[0039] From the above description, we can see that although there are many data acquisition devices on the market, they still have certain shortcomings in real-time, scalability, flexibility and cost.

[0040] In order to solve the above problems, the present application provides a data acquisition device, including: a first chip, a first operating system running on the first chip, the first chip is connected to the electronic control unit ECU of the vehicle through the bus of the vehicle, and the first operating system is used to schedule the first chip to collect the ECU data of the vehicle; a second chip, a second operating system running on the second chip, the second chip is connected to the first chip, and the second operating system is used to schedule the second chip to obtain ECU data from the first chip to monitor the working performance of the vehicle. This solution sets up a dual-chip dual-system architecture in the data acquisition device, the first operating system (such as RTOS) can handle ECU data acquisition and transmission with high real-time requirements, and the second operating system (such as Linux) is used to manage ECU data. This layered design helps the data acquisition device meet the requirements of high real-time data transmission and high-complexity data processing, and the data acquisition device has high flexibility and scalability.

[0041] Combined with the following Figure 1 The data acquisition device in the embodiment of the present application is described in detail. Figure 1 As shown, the data acquisition device 100 may include a first chip 110 and a second chip 120 .

[0042] A first operating system runs on the first chip 110 . The first chip 110 is connected to an electronic control unit ECU of the vehicle through a bus of the vehicle. The first operating system is used to schedule the first chip 110 to collect ECU data of the vehicle.

[0043] A second operating system runs on the second chip 120 , which is connected to the first chip 110 . The second operating system is used to schedule the second chip 120 to obtain ECU data from the first chip 110 to monitor the working performance of the vehicle.

[0044] The first operating system is a real-time operating system (RTOS), which can improve the efficiency of ECU data collection and transmission. The second operating system is a Linux operating system, which can improve the processing capability of complex ECU data.

[0045] It should be understood that the first chip and the second chip also support other operating systems. For example, the second chip also supports operating systems including Linux 5.10, Android 11, Ubuntu, Debian 11, OpenHarmony 4.1, etc.

[0046] In some implementations, see Figure 2 The first chip includes multiple onboard communication interfaces, including: Ethernet (such as dual Gigabit Ethernet), FlexRay, USB (such as USB 3.0), SDHC, CAN, CANFD, LIN, UART / SCI and SPI communication interfaces.

[0047] In some implementations, see Figure 2 The second chip includes multiple onboard communication interfaces, including: Ethernet (such as dual Gigabit Ethernet), FlexRay, USB (such as USB 3.0), SDHC, CAN, CANFD, LIN, UART / SCI and SPI communication interfaces.

[0048] The present application does not impose any specific limitation on the type of the first chip 110 . For example, the first chip 110 may be NXPM5748G. In another example, the first chip 110 may also be a self-developed chip.

[0049] The present application does not impose any specific restrictions on the type of the second chip 120. For example, the second chip 120 may be a Cortex-A series chip (such as Cortex-A55); for another example, the first chip 110 may also be a chip of RISC-V architecture or x86 architecture.

[0050] It should be noted that the vehicles mentioned in this application may include but are not limited to: electric vehicles, fuel vehicles or hybrid vehicles. The vehicles in this application are equipped with a large number of ECUs, and multiple ECUs communicate data through a bus. Figure 2 The bus in the vehicle may include but is not limited to: CAN, LIN, FlexRay and Ethernet buses.

[0051] In the present application, ECU data may refer to data generated by ECU, and ECU data is transmitted through the vehicle bus. The acquisition device 100 acquires ECU data through the vehicle bus, and then the ECU data may be used to monitor the working performance of the vehicle system.

[0052] It should be noted that monitoring the working performance of a vehicle may refer to monitoring or diagnosing the working performance parameters (also referred to as operating performance parameters) or operating status of a vehicle system. For example, monitoring the working performance of a vehicle may include, but is not limited to: monitoring the status of a powertrain system (such as monitoring the operating status of a transmission, a drive shaft, and other transmission components), monitoring the status of an engine (such as monitoring performance parameters such as engine speed, temperature, and pressure), and monitoring the changing status of tire pressure.

[0053] In some implementations, see Figure 2 The data acquisition device 100 further includes an integrated circuit 130, which can be used to carry the first chip 110 and the second chip 120. A storage unit (not shown in the figure) is provided on the integrated circuit 130, and the first chip 110 and the second chip 120 share the storage space of the storage unit. The storage unit can be, for example, a cache, a dynamic random access memory, or an embedded flash memory, etc., and this application does not make any specific restrictions on this.

[0054] The flexibility and scalability of the data acquisition device 100 can be improved by setting the integrated circuit 130. The present application does not specifically limit the type of the integrated circuit 130. For example, the integrated circuit 130 can be a field-programmable gate array (FPGA) integrated circuit 130; for another example, the integrated circuit 130 can also be an application-specific integrated circuit 130 (ASIC). It should be noted that, due to the editable nature of the FPGA, setting the integrated circuit 130 as an FPGA can further improve the flexibility and scalability of the data acquisition device 100.

[0055] It should be noted that in the present application, by designing a shared memory architecture, the first operating system and the second operating system can exchange data at high speed, reducing the delay in data transmission and further improving the data transmission efficiency (i.e., improving the real-time performance of data transmission).

[0056] In some implementations, after the second chip 120 obtains the ECU data from the first chip 110, the second chip 120 may be used to compress the ECU data and cache or store the ECU data to be transmitted. The second chip 120 is also used to manage the USB interface, Ethernet interface, 100M network port, cellular network communication module (such as 4G or 5G communication module) and Wi-Fi communication module to ensure reliable external device connection.

[0057] It should be understood that the second chip can transmit the compressed ECU data to an external device (such as a target cloud platform or PC) for processing and analysis. A storage module is also provided on the second chip to cache or store the ECU data to be transmitted. The storage module can be, for example, a random access memory (RAM).

[0058] In some implementations, see Figure 2 The second chip 120 can be connected to the target cloud platform 200, and the second chip 120 is used to send ECU data to the target cloud platform 200, so as to monitor the working performance of the vehicle using the target cloud platform 200. Using cloud-based processing to analyze ECU data helps to meet the requirements of complex data processing.

[0059] In some implementations, the target cloud platform 200 may be a cloud platform maintained by a manufacturer of the data collection device 100 .

[0060] After receiving the ECU data sent by the second chip 120, the target cloud platform 200 is also used to perform target processing operations on the ECU data to obtain target ECU data and monitor the working performance of the vehicle based on the target ECU data. The target processing operations include one or more of the following: feature extraction processing on the ECU data; decoding operation processing on the ECU data; data cleaning processing on the ECU data.

[0061] In some implementations, a data cleaning process is triggered after the ECU data is uploaded to the target cloud platform 200. The cleaning process includes steps such as denoising, format conversion, and data repair, thereby ensuring the data quality of the ECU data.

[0062] The target cloud platform 200 is also used to store the target ECU data in a data lake or a data warehouse according to the monitoring scenario of the vehicle, which helps to improve the accuracy of visual analysis charts or other data analysis.

[0063] This application does not impose specific restrictions on vehicle monitoring scenarios. For example, if large-scale data analysis and machine learning are to be performed on the ECU data of all vehicles to predict vehicle failures, optimize driving behavior, and improve fuel efficiency, in this detection scenario, the corresponding ECU data can be stored in a data lake. Because the storage structure of the data lake is more conducive to large-scale data analysis and storage. For another example, if a more complex vehicle battery status needs to be monitored, the corresponding ECU data can be stored in a data warehouse. Because the data warehouse supports structured data, can support indexing, partitioning, parallel processing, etc., the data warehouse optimizes query performance and supports efficient execution of query operations, that is, the data warehouse supports complex data analysis operations.

[0064] In some implementations, the target cloud platform 200 can also be used to generate a visual analysis chart of the ECU using target screening conditions based on the storage structure of the target ECU data. It should be understood that the target cloud platform 200 may include a visualization interface, and by setting different screening conditions on the visualization interface, the corresponding ECU data can be retrieved from the data lake or data warehouse, so as to form a more accurate visualization analysis chart. The user terminal (such as a mobile phone or computer) can remotely view the visualization interface or visualization analysis chart. The user terminal can, for example, remotely view the visualization interface or visualization analysis chart through a web link. In this way, the user experience can be improved.

[0065] In some implementations, see Figure 2 The data acquisition device 100 can also be directly connected to a user device (such as a computer or iPad), and the second chip 120 is used to send ECU data to the user device so as to monitor the working performance of the vehicle using the user device, thereby increasing the application flexibility of the data acquisition device 100. It should be understood that when the data acquisition device 100 is directly connected to the user device, the user needs to independently develop program code on the user device to process and analyze ECU data, so as to achieve the purpose of monitoring the working performance of the vehicle.

[0066] In some implementations, the second chip 120 is further used to: if the communication quality between the second chip 120 and the target cloud platform 200 is less than a preset threshold, store the ECU data to be sent to the target cloud platform 200. When the communication quality between the second chip 120 and the target cloud platform 200 is greater than or equal to the preset threshold, resend the stored ECU data to be sent to the target cloud platform 200 to the target cloud platform 200. In this way, insufficient data protection (such as data loss) in the case of network disconnection can be effectively prevented, and the data synchronization mechanism is improved.

[0067] In some implementations, the communication quality may refer to the signal communication strength between the second chip 120 and the target cloud platform 200. The preset threshold may be set according to requirements, and this application does not impose any specific restrictions on this.

[0068] The second chip 120 is also used to send the device information of the data acquisition device 100 (such as the device ID, device name, etc. of the data acquisition device 100) to the target cloud platform 200, and receive the device certificate of the data acquisition device 100 sent from the target cloud platform 200. The device certificate can be a device security certificate generated based on the device information by the target cloud platform 200. The device certificate can be used to determine whether the data acquisition device 100 is a legitimate device.

[0069] In some implementations, the data collection device 100 further includes an integrated hardware security module (HSM). The integrated hardware security module can be used to store device certificates, thereby improving data encryption and security at the hardware level.

[0070] The present application does not impose any specific restrictions on the location of the integrated hardware security module. For example, the integrated hardware security module may be integrated in the first chip 110 ; or, in another example, the integrated hardware security module may be integrated on the integrated circuit 130 board.

[0071] The above mainly introduces the data acquisition device 100, and the data acquisition system in this application is introduced below with examples. It should be understood that the data acquisition device in the data acquisition system corresponds to the data acquisition device 100 in the above text, so the parts not described in detail can refer to the description of the embodiment of the data acquisition device 100 in the above text.

[0072] This application also provides a data acquisition system, see Figure 3 The data acquisition system 1000 includes a data acquisition device 100 and a target cloud platform 200 . The data acquisition device 100 is connected to the target cloud platform 200 . The data acquisition device 100 includes a first chip 110 and a second chip 120 .

[0073] A first operating system runs on the first chip 110, which is connected to the vehicle's electronic control unit ECU through the vehicle's bus. The first operating system is used to schedule the first chip 110 to collect the vehicle's ECU data; a second operating system runs on the second chip 120, which is connected to the first chip 110. The second operating system is used to schedule the second chip 120 to obtain ECU data from the first chip 110, and schedule the second chip 120 to send ECU data to the target cloud platform 200, so as to use the target cloud platform 200 to monitor the vehicle's working performance.

[0074] In some implementations, refer again to Figure 2 The data acquisition device 100 further includes an integrated circuit 130. The integrated circuit 130 can be used to carry the first chip 110 and the second chip 120. A storage unit is provided on the integrated circuit 130. The first chip 110 and the second chip 120 share the storage space of the storage unit.

[0075] The target cloud platform 200 is also used to perform target processing operations on the ECU data to obtain target ECU data and monitor the working performance of the vehicle based on the target ECU data; the target processing operations include one or more of the following: feature extraction processing on the ECU data; decoding operation processing on the ECU data; data cleaning processing on the ECU data.

[0076] In some implementations, a data cleaning process is triggered after the ECU data is uploaded to the target cloud platform 200. The cleaning process includes steps such as denoising, format conversion, and data repair, thereby ensuring the data quality of the ECU data.

[0077] The target cloud platform 200 is also used to store the target ECU data in a data lake or a data warehouse according to the monitoring scenario of the vehicle.

[0078] This application does not impose specific restrictions on vehicle monitoring scenarios. For example, if large-scale data analysis and machine learning are to be performed on the ECU data of all vehicles to predict vehicle failures, optimize driving behavior, and improve fuel efficiency, in this detection scenario, the corresponding ECU data can be stored in a data lake. Because the storage structure of the data lake is more conducive to large-scale data analysis and storage. For another example, if a more complex vehicle battery status needs to be monitored, the corresponding ECU data can be stored in a data warehouse. Because the data warehouse supports structured data, can support indexing, partitioning, parallel processing, etc., the data warehouse optimizes query performance and supports efficient execution of query operations, that is, the data warehouse supports complex data analysis operations.

[0079] In some implementations, the target cloud platform 200 can also be used to generate a visual analysis chart of the ECU using target screening conditions according to the storage structure of the target ECU data. It should be understood that the target cloud platform 200 may include a visualization interface, and by setting different screening conditions on the visualization interface, the corresponding ECU data can be retrieved from the data lake or data warehouse, so as to form a visual analysis chart of the ECU. The user terminal (such as a mobile phone or computer) can remotely view the visualization interface or the visualization analysis chart. The user terminal can, for example, remotely view the visualization interface or the visualization analysis chart through a web link. In this way, the user experience can be improved.

[0080] In some implementations, the second chip 120 may be connected to the target cloud platform 200. The second chip 120 is also used to store ECU data to be sent to the target cloud platform 200 if the communication quality between the second chip 120 and the target cloud platform 200 is less than a preset threshold.

[0081] The present application does not impose any specific restrictions on the connection method between the second chip 120 and the target cloud platform 200. For example, the second chip 120 and the target cloud platform 200 may be connected via a cellular network or via the Internet of Things.

[0082] In some implementations, the second chip 120 is further used to send device information of the data acquisition device 100 to the target cloud platform 200, and receive a device certificate of the data acquisition device 100 sent from the target cloud platform 200;

[0083] The data collection device 100 also includes an integrated hardware security module, which is used to store device certificates.

[0084] In some implementations, the data acquisition device 100 may transmit device information of the data acquisition device 100 to the target cloud platform 200 during factory initialization.

[0085] In some implementations, the target cloud platform 200 is also used to: receive ECU data sent from a third-party data acquisition device (such as CANoe), and use the target cloud platform 200 to monitor the working performance of the vehicle. That is to say, the target cloud platform 200 in the embodiment of the present application can also support receiving ECU data collected and uploaded by a third-party data acquisition device. Then, the target cloud platform 200 is also used to perform target processing operations on the ECU data collected by the third party, obtain processed ECU data, and monitor the working performance of the vehicle based on the processed ECU data, thereby increasing the flexibility of the application of the data acquisition system 1000. Among them, the target processing operation includes one or more of the following: feature extraction processing on ECU data; decoding operation processing on ECU data; data cleaning processing on ECU data.

[0086] The following describes the embodiments of the present application in more detail with reference to specific examples. Figures 4 to 7 It is only to help those skilled in the art understand the embodiments of the present application, rather than to limit the embodiments of the present application to the specific values ​​or specific scenarios illustrated. Those skilled in the art can obviously make various equivalent modifications or changes based on the examples given, and such modifications or changes also fall within the scope of the embodiments of the present application.

[0087] See again Figure 2 and Figure 3, the data acquisition system 1000 includes a data acquisition device 100 and a target cloud platform 200. The data acquisition device 100 is connected to the vehicle system through the vehicle bus to obtain vehicle data in real time, and then interacts with the target cloud platform 200 through a wireless network. The user can remotely access the target cloud platform 200 through a user terminal (such as a mobile phone) to remotely monitor the working performance of the vehicle. Of course, the data acquisition device 100 can also interact with the PC through USB, but this physical connection method requires the user to develop corresponding program codes separately to analyze ECU data to achieve the purpose of monitoring the working performance of the vehicle. The data acquisition system 1000 in the embodiment of the present application can ensure the real-time, security and flexibility of data transmission, forming a closed-loop system of the local, target cloud platform 200 and the user end. The data acquisition device 100 can be composed of a dual-chip dual system carried by FPGA, and the dual systems are RTOS and Linux systems respectively. RTOS is responsible for real-time tasks, while Linux processes non-real-time tasks. This layered design helps the data acquisition device 100 meet the requirements of high real-time data transmission and high-complexity data processing, and the flexibility and scalability of the data acquisition device are high.

[0088] In this application, the RTOS system is responsible for tasks with high real-time requirements, such as communicating with the vehicle system through vehicle buses such as CAN / CAN FD, FlexRay, LIN, ETH, and ensuring data security through the HSM module. It is an embedded real-time operating system. The system has a rich on-board communication interface, which includes one or more of the following: Ethernet, FlexRay, USB, SDHC, CAN, CAN FD, LIN, UART / SCI and SPI interfaces, which are suitable for a variety of complex automotive electronics and industrial automation applications.

[0089] The Linux system undertakes multiple non-real-time processing tasks, such as peripheral device management, data storage, and processing of network communication functions such as 4G and Wi-Fi. The Linux system is responsible for managing USB interfaces, Ethernet interfaces, and 100M network ports to ensure reliable external device connections. The Linux system can use the Cortex-A55 architecture chip, and the Neural Processing Unit (NPU) can be integrated on the Linux system's architecture chip to achieve efficient AI task processing.

[0090] The data acquisition system 1000 architecture design in the embodiment of the present application covers the complete process from vehicle data collection and transmission to reception, processing, storage and analysis of the target cloud platform 200, ensuring the real-time, accuracy and security of the data. In this application, data lake and / or data warehouse technology are also used according to different application scenarios to support efficient storage and in-depth analysis of large-scale data. The data acquisition system 1000 of the present application provides a flexible, scalable and efficient solution to meet various business needs of real-time processing and batch analysis, and ultimately realize intelligent management and decision support. The following is combined with Figure 4 The data acquisition system 1000 is described in more detail.

[0091] See also Figure 4 , the data acquisition system 1000 includes a data acquisition device 100 and a target cloud platform 200. The data acquisition device 100 can collect and transmit raw ECU data to the target cloud platform 200 through different communication protocols (such as CAN, FlexRay, Lin, Ethernet). In some implementations, the data acquisition system 1000 may also include a third-party data acquisition device.

[0092] The target cloud platform 200 may include an application layer, a storage layer, and a computing layer.

[0093] The application layer can include an Application Programming Interface (API) gateway. The API gateway provides a unified API entry point to the outside world, which can be used to manage and route client requests. The application layer can also perform access control to ensure the security of the system and data and prevent unauthorized access.

[0094] In some implementations, the application layer may also be used to implement one or more of the following application services:

[0095] Signal database (SDB) management: manages the vehicle's signal data and is used to parse the collected ECU data of the vehicle bus to ensure the accuracy and consistency of the data.

[0096] Permission management: Manage access rights at the user and system levels to ensure that only authorized users can access specific resources and data.

[0097] Device management: monitor and manage various data acquisition devices 100 connected to the system to ensure their normal operation and security.

[0098] Certificate Management: Manage digital certificates for systems and devices to ensure secure communications and identity authentication.

[0099] Task management: supports the scheduling and management of various tasks to ensure orderly execution of tasks and resource optimization.

[0100] Data management: Provide a variety of efficient and flexible services to support data storage, processing and query, and support in-depth data analysis, real-time monitoring and intelligent decision-making.

[0101] The application layer provides efficient, secure and intelligent services through a unified API gateway and strict authentication and authorization mechanisms, helping users achieve data-driven business optimization and intelligent operations.

[0102] In some implementations, the data storage layer may be configured to perform one or more of the following operations:

[0103] Raw ECU data storage: Raw ECU data is stored in the object storage service, awaiting further processing.

[0104] Data lake storage: To meet different business needs, the system supports storage in multiple data formats, including Parquet, CSV, BLF, ZIP, and PCAPNG formats, and supports large-scale data management and query.

[0105] Data warehouse storage. Data warehouses can include: Athena, Clickhouse, Lindorm, Doris, etc.

[0106] Athena: AWS's interactive query service for analyzing data in a data lake.

[0107] Clickhouse: A column-oriented database management system for online analytical processing (OLAP).

[0108] Lindorm: Alibaba Cloud's time series database for large-scale data storage and query.

[0109] Doris: A massively parallel processing (MPP) database system provided by Apache for data analysis and query.

[0110] In some implementations, elastic computing and data cleansing can be performed at the computing layer.

[0111] Elastic computing includes feature computing and decoding computing. Feature computing: extracting feature values ​​from raw data for analysis and model training. For example, average speed, fuel consumption and other indicators can be calculated from the vehicle's status data. Decoding computing: decoding raw binary data into vehicle signal data for subsequent query and analysis operations. The decoding module supports the parsing of multiple vehicle data protocols and can process large amounts of data in real time.

[0112] Data cleaning: When the original data is uploaded to the object storage service, the data cleaning process is triggered. The cleaning process includes steps such as denoising, format conversion, and data repair to ensure data quality.

[0113] It should be understood that the data acquisition system 1000 architecture in this application constructs a complete business process system through six process stages: creating customers, creating equipment, preparation, equipment online, equipment processing and data services. Each stage covers all key steps from customer information entry, equipment activation, communication configuration, data collection and uploading, to data processing, report generation and export of analysis results. This architecture ensures the accuracy, real-time and security of data, provides customers with comprehensive equipment management and data analysis services, supports intelligent business decisions and operations, and realizes efficient and reliable business management of the target cloud platform 200. The business management of the target cloud platform 200 is described in detail below in conjunction with the accompanying drawings.

[0114] Figure 5 For the business architecture diagram of the target cloud platform 200, see Figure 5 ,The business management of the target cloud platform 200 includes: creating customers, creating equipment, preparing work, using equipment, data processing and data services.

[0115] Creating a customer includes information entry and authority allocation. Information entry: Entering customer information, including basic information and detailed information of the customer. Ensure that each customer has unique identification information to facilitate subsequent management and service. Authority allocation: Assign corresponding authority to customers to ensure system security and data access control.

[0116] Creating a device includes entering device information. Entering device information: Enter detailed information about the device, including device type, model, serial number, etc.

[0117] Preparation work includes activating the device, uploading SDB, and configuring the channel. Activating the device: Activate the device and verify the device certificate and other information to ensure that the device is valid and can work properly and connect to the system. Uploading SDB: Upload the SDB file to manage vehicle-side signal definitions and standardized information. Channel configuration: Used to define and manage different types of communication buses (such as CAN, LIN, FlexRay, Ethernet, etc.) and related hardware interfaces. Channel configuration ensures that VNAS can correctly communicate with the actual hardware interface and send and receive bus messages.

[0118] The use of equipment includes equipment online, data collection, data reporting, status reporting and equipment offline. Among them, data collection, data reporting and status reporting are processes that need to be executed cyclically. Equipment online: The target cloud platform 200 detects whether the device is online through the heartbeat mechanism to ensure that the device is successfully connected to the target cloud platform 200 system. Data collection: The target cloud platform 200 issues a collection task, and the device starts to collect data. Data reporting: The device uploads the collected data to the target cloud platform 200 via wifi, 4g, etc. Status upload: During the collection process, the device collection status, device CPU, disk usage, etc. are uploaded to the target cloud platform 200 system for real-time monitoring and management. Equipment offline: The device that has completed the collection task can go offline. After the target cloud platform 200 detects that the device is offline, it sets the device status to offline.

[0119] Data processing includes generating a binary log file (BLF) and message parsing. Generating BLF: The target cloud platform 200 generates a binary log file (BLF) from the collected data, which is used to store and analyze the operation data of the equipment; Message parsing: According to the SDB file, the target cloud platform 200 parses the collected original vehicle bus message data into signal data.

[0120] Data services include importing / downloading data files, querying original messages, querying signals, and generating online analysis / analysis reports. Importing / downloading data files: supports the import and downloading of data files in various formats, facilitating data management and use. Querying original messages: based on the imported data files, convert them into original data messages collected by the vehicle bus based on SDB, DBC and other files. Querying signals: after the original messages are parsed into signal data, online queries can be performed, which helps users quickly obtain the required information for further data analysis or fault diagnosis. Online analysis / analysis report generation: real-time online analysis of data and generation of analysis reports to support business decisions.

[0121] In the embodiment of the present application, the data acquisition system 1000 can collect data through the device, perform format conversion and elastic calculation through the data processing module, and finally store the data in the data lake and data warehouse. The entire data flow ensures the integrity and efficiency of data from collection to storage, supports complex data analysis tasks and business needs, and provides users with reliable data management and analysis services. The data flow of the data acquisition system 1000 is introduced in detail below with reference to the accompanying drawings.

[0122] Figure 6 Schematic diagram of the data flow of the data acquisition system 1000. Figure 6 , the data flow covers the entire life cycle from data collection, storage, processing to analysis. The specific process is as follows:

[0123] Data collection: The data collection device 100 or a third-party collection device collects the corresponding vehicle-side bus data according to the collection instructions issued by the target cloud platform 200.

[0124] Data transmission: The data collection device 100 can upload the collected raw data to the object storage service (such as S3) through WiFi or 5G network, and the third-party collection device can directly upload the collected raw data to the storage module (data lake and / or data warehouse) of the target cloud platform. It supports data files in multiple formats, and the transmission module selects the optimal transmission channel to ensure the real-time performance of the data.

[0125] Data processing: After the raw data is uploaded to the object storage service, the data cleaning and elastic computing process is triggered. The cleaning process includes steps such as denoising, format conversion, and data repair to ensure data quality. The elastic computing module performs feature calculation and decoding processing on the stored data. After the raw data is converted into structured data, the data is stored in the lake and warehouse to support subsequent analysis.

[0126] Data storage and compression: The decoded data is stored in files of different formats (such as parquet, ZIP, TXT, etc.) and compressed as needed to reduce storage overhead.

[0127] It should be understood that if a third-party acquisition device is used to collect ECU data, it is necessary to use a user device (such as a computer) for storage, and independently develop program code for processing (such as compression), and then transmit the processed data in different formats (such as asc, blf, zip, etc.) to the storage module of the target cloud platform.

[0128] Data analysis and query: After the data enters the analytical database system (such as Athena, Clickhouse, etc.), users can conduct in-depth mining and real-time analysis of the data through SQL queries, data visualization tools or customized analysis tasks.

[0129] Generate reports and visualizations: Based on user needs, the system automatically generates analysis reports or data visualizations to provide users with insightful information.

[0130] As an example, the ECU data message collected by the data acquisition device may be:

[0131] {

[0132] "chn":1,

[0133] "frameId":300,

[0134] "len":8,

[0135] "payload":"00000200300005",

[0136] "tcpHeader":{

[0137] "commandId":3,

[0138] "countNum":198460,

[0139] "headerMark":"Z",

[0140] "receiveCanNum":198459,

[0141] "version":1

[0142] },

[0143] "timestamp":1724833225615

[0144] }

[0145] The above ECU data message may be composed of a message header and a message body. The message header is shown in Table 1 below.

[0146] Table 1

[0147] Field Name Field length (bytes) describe headerMark 1(byte) Identification position, Z indicates the start of uploading version 1(byte) Version bit, 1 countNum 8(byte) The actual amount of data uploaded receiveCanNum 8(byte) The actual amount of vehicle-side data received commandId 2(byte) Command type, such as connection command, CAN report command

[0148] The structure of the message body is shown in Table 2. It should be understood that the message body structure will be different depending on the command, and the CAN bus submission is used as an example.

[0149] Table 2

[0150]

[0151]

[0152] In some implementations, the data acquisition device 100 compresses the collected original vehicle bus data and uploads it to the target cloud platform 200 via wifi or 5G.

[0153] In some implementations, the target cloud platform 200 performs data cleaning and calculation on the original ECU data. After the device uploads the original data to the storage layer, the target cloud platform 200 is triggered to clean and calculate the data. The target cloud platform 200 decodes the original data according to the uploaded SDB file. According to the car series, DBC version, bus type, commandId, and hexadecimal payload, the program converts this hexadecimal payload into a 64-bit binary string and parses the detailed information of each signal according to the configuration file in the database.

[0154] The target cloud platform 200 stores the decoded data in a lake or warehouse, such as storing the decoded data in clickhouse for online query and analysis.

[0155] In some implementations, the uploaded data source and data analysis model are selected to generate a visual analysis chart. The visual analysis chart may include, for example, the number of times the battery triggers recharging, the number of times the battery dynamic endurance drops abnormally, the number of times the air conditioning pipeline pressure is insufficient, the number of times the air conditioning refrigerant pressure is abnormally low, the number of times the vehicle transportation is abnormal, etc.

[0156] The present application also provides a flow chart of the entire life cycle of a data acquisition system 1000. Figure 7 , the specific process includes steps 1 to 23. It should be understood that Figure 7 The data acquisition device in is the data acquisition device 100 mentioned above, and the cloud end is the target cloud platform 200 mentioned above.

[0157] In step 1, the data acquisition device is factory initialized. During the initialization process, a key is generated and stored in the HSM.

[0158] In step 2, the user purchases the data acquisition device from the manufacturer of the data acquisition device.

[0159] In step 3, the device manufacturer generates and issues a device license to the user in the cloud.

[0160] In step 4, the user registers and logs in to the cloud platform client.

[0161] In step 5, the cloud receives the user's registration and login information and performs a permission check.

[0162] In step 6, after verification is successful, the user's device information and device license are entered.

[0163] In step 7, the cloud verifies the license of the device, and if the verification passes, the license is bound to the device.

[0164] In step 8, the cloud creates a device record.

[0165] In step 9, the data collection device generates a certificate signing request (CSR) file according to the key, and sends the CSR file to the cloud.

[0166] In step 10, a device certificate is generated for the data collection device according to the CSR file.

[0167] In step 11, a device certificate is issued to the data acquisition device.

[0168] In step 12, the data collection device stores the device certificate in the HSM.

[0169] In step 13, the data acquisition device uploads information such as device certificate and device ID and connects to the cloud.

[0170] In step 14, the cloud performs device certificate verification. If the verification passes, the device is online and data collection can be performed.

[0171] In step 15, the user can upload SDB files, channel configuration and other information to prepare for data collection and analysis.

[0172] In step 16, the user configures the collection task.

[0173] In step 17, after receiving the collection task, the cloud sends a collection instruction to the data collection device.

[0174] In step 18, after receiving the collection instruction, the data collection device responds to the instruction (for example, it may feedback ACK information).

[0175] In step 19, the data acquisition device acquires ECU data via the vehicle bus.

[0176] In step 20, the data acquisition device transmits the collected ECU data to the cloud, and can also report the collection task status, equipment monitoring indicators, etc.

[0177] In step 21, the cloud verifies the collection status and device status.

[0178] In step 22, data storage, data analysis, calculation, etc. are performed in the cloud.

[0179] In step 23, users can perform data query, export, visual analysis, etc. on the cloud platform.

[0180] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A data acquisition device, characterized in that: include: a first chip, wherein a first operating system runs on the first chip, the first chip is connected to an electronic control unit ECU of the vehicle through a bus of the vehicle, and the first operating system is used to schedule the first chip to collect ECU data of the vehicle; A second chip, wherein a second operating system runs on the second chip, the second chip is connected to the first chip, and the second operating system is used to schedule the second chip to obtain the ECU data from the first chip to monitor the working performance of the vehicle.

2. The data acquisition device according to claim 1, characterized in that: The data acquisition device also includes: An integrated circuit is used to carry the first chip and the second chip. A storage unit is provided on the integrated circuit, and the first chip and the second chip share the storage space of the storage unit.

3. The data acquisition device according to claim 1, characterized in that: The second chip is connected to a target cloud platform, and the second chip is used to send the ECU data to the target cloud platform so as to monitor the working performance of the vehicle using the target cloud platform.

4. The data acquisition device according to claim 3, characterized in that: The second chip is also used for: If the communication quality between the second chip and the target cloud platform is less than a preset threshold, the ECU data to be sent to the target cloud platform is stored.

5. A data acquisition system, characterized in that: It includes a data acquisition device and a target cloud platform, the data acquisition device is connected to the target cloud platform, and the data acquisition device includes: a first chip, wherein a first operating system runs on the first chip, the first chip is connected to an electronic control unit ECU of the vehicle through a bus of the vehicle, and the first operating system is used to schedule the first chip to collect ECU data of the vehicle; A second chip, wherein a second operating system runs on the second chip, the second chip is connected to the first chip, and the second operating system is used to schedule the second chip to obtain the ECU data from the first chip, and schedule the second chip to send the ECU data to the target cloud platform, so as to monitor the working performance of the vehicle using the target cloud platform.

6. The data acquisition system according to claim 5, characterized in that: The data acquisition device also includes: An integrated circuit is used to carry the first chip and the second chip. A storage unit is provided on the integrated circuit, and the first chip and the second chip share the storage space of the storage unit.

7. The data acquisition system according to claim 5, characterized in that: The target cloud platform is also used to perform target processing operations on the ECU data to obtain target ECU data, and monitor the working performance of the vehicle based on the target ECU data; The target processing operation includes one or more of the following: Performing feature extraction processing on the ECU data; Performing decoding operation on the ECU data; The ECU data is cleaned.

8. The data acquisition system according to claim 7, characterized in that: The target cloud platform is also used for: According to the monitoring scenario of the vehicle, the target ECU data is stored in a data lake or a data warehouse.

9. The data acquisition system according to claim 7, characterized in that: The target cloud platform is used for: According to the storage structure of the target ECU data, a visual analysis chart of the ECU is generated using target screening conditions.

10. The data acquisition system according to claim 5, characterized in that: The second chip is also used for: If the communication quality between the second chip and the target cloud platform is less than a preset threshold, the ECU data to be sent to the target cloud platform is stored.

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