Automatic simulation test method based on cloud platform, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an automatic simulation test method based on a cloud platform, electronic equipment and a storage medium. The method comprises the steps that a simulation test task is acquired, target test equipment is determined from multiple pieces of test equipment according to the simulation test task, and resources for executing the simulation test task are deployed on the test equipment; establishing communication connection with middleware of the target test equipment through a transfer service layer of the cloud platform; and controlling the target test equipment to execute the simulation test task through the communication connection to obtain a test result. The technical problem of how to improve the efficiency and reliability of the simulation test is solved.

Description

Technical Field

[0001] This application relates to the field of automated testing technology, and in particular to an automated simulation testing method, electronic device and storage medium based on a cloud platform. Background Technology

[0002] In the field of intelligent driving, especially in the research and development of autonomous vehicles, hardware-in-the-loop (HIL) testing and processor-in-the-loop (PIL) testing are crucial steps to ensure the functional safety and performance stability of vehicle electronic control units and domain controllers. However, with the increasing maturity and complexity of autonomous driving technology, traditional HIL and PIL testing methods face numerous challenges.

[0003] In existing testing methodologies, whether for hardware-in-the-loop or platform-in-the-loop testing, resource allocation and scheduling largely rely on manual operation. This manual operation not only consumes significant manpower and time, extending test preparation cycles, but also limits resource utilization efficiency. Due to the limitations of human decision-making, test resources cannot be allocated in a timely and optimal manner, resulting in resource idleness and waste. This inefficient test resource management significantly impacts simulation testing efficiency, especially during peak testing periods. Furthermore, traditional testing methods often use virtualization to directly replace real hardware without considering simulation testing based on actual hardware devices, thus affecting the realism and reliability of the tests.

[0004] Therefore, improving the efficiency and reliability of simulation testing is one of the important technical issues in related fields. Currently, no effective solution has been proposed to address these issues. Summary of the Invention

[0005] This application provides an automated simulation testing method, electronic device, and storage medium based on a cloud platform, aiming to solve the technical problem of how to improve the efficiency and reliability of simulation testing.

[0006] According to one aspect of the embodiments of this application, an automated simulation testing method based on a cloud platform is provided, comprising: acquiring a simulation test task; determining a target test device from multiple test devices according to the simulation test task, wherein the test device is equipped with resources for executing the simulation test task; establishing a communication connection with the middleware of the target test device through the relay service layer of the cloud platform; and controlling the target test device to execute the simulation test task via the communication connection to obtain test results.

[0007] The automated simulation testing method based on a cloud platform provided in this application achieves the following technical effects: First, by acquiring and intelligently analyzing simulation test tasks through the cloud platform, the most suitable test equipment for executing the task, i.e., the target test equipment, is selected. This task-requirement-based test equipment selection mechanism significantly improves the targeted use of resources and avoids the problems of resource waste and long waiting times in traditional testing. Second, the relay service layer of the cloud platform establishes a communication connection with the middleware on the target test equipment, which is a key step in realizing remote control and data transmission. Finally, through the established communication connection, the cloud platform can control the target test equipment to execute simulation test tasks in real time. That is, through the established communication connection, the simulation test tasks can be remotely controlled to execute on real hardware devices on the cloud platform, which simplifies the testing process, improves testing efficiency, and further enhances the realism and reliability of the test. Therefore, this application embodiment can achieve the technical effect of improving the efficiency and reliability of simulation testing, solving the technical problem of how to improve the efficiency and reliability of simulation testing.

[0008] Optionally, the simulation test task includes: operating condition requirement data, which characterizes the operating conditions required during the execution of the simulation test task; the target test device includes a hardware-in-the-loop test device; the middleware includes a proxy service layer; establishing a communication connection with the middleware of the target test device through the relay service layer of the cloud platform includes: in response to the target test device being a hardware-in-the-loop test device, establishing a communication connection with the proxy service layer of the hardware-in-the-loop test device through the relay service layer of the cloud platform; controlling the target test device to execute the simulation test task and obtain test results through the communication connection includes: transmitting the operating condition requirement data from the cloud platform to the hardware-in-the-loop test device through the communication connection; controlling the simulation software deployed on the hardware-in-the-loop test device to perform operating condition simulation based on the operating condition requirement data, obtaining operating condition simulation data; and controlling the hardware-in-the-loop test device to execute the simulation test task and obtain test results based on the operating condition simulation data.

[0009] The optional embodiments described above achieve the following technical effects: A communication connection is established between the relay service layer of the cloud platform and the proxy service layer of the target test equipment. This communication architecture enables data transmission and control command issuance between the cloud platform and the hardware-in-the-loop test equipment. After transmitting the operating condition requirement data to the hardware-in-the-loop test equipment via the communication connection, the simulation software deployed on the hardware-in-the-loop equipment is controlled to perform operating condition simulation, generating operating condition simulation data. The generation of this data provides a foundation for subsequent testing tasks, ensuring the realism of the test environment. Based on the operating condition simulation data, the hardware-in-the-loop test equipment is controlled to execute simulation test tasks, ultimately obtaining the test results. Because it is based on the communication connection, the hardware-in-the-loop test equipment can be directly controlled to perform test tasks, replacing the direct virtualization of hardware into software in the cloud for test execution, thus ensuring the objectivity and accuracy of the test results.

[0010] Optionally, the simulation test task includes: identifying the object under test; controlling the hardware-in-the-loop test equipment to execute the simulation test task based on the operating condition simulation data to obtain test results; including: controlling the hardware-in-the-loop test equipment to process the operating condition simulation data to obtain a first target simulation signal; controlling the hardware-in-the-loop test equipment to test the test object associated with the object under test based on the first target simulation signal to obtain test results, wherein the test object and the target test equipment are communicatively connected.

[0011] The above-described optional embodiments of this application achieve the following technical effects: Through instructions from the cloud platform, the hardware-in-the-loop testing equipment can convert operational condition simulation data into a first target simulation signal, which is directly applied to the object under test. The generation of the first target simulation signal ensures the matching between the test conditions and the test object, enhancing the relevance of the test and further improving test efficiency. Then, the hardware-in-the-loop testing equipment is controlled to test the test object associated with the object under test identifier according to the first target simulation signal. Since the test object is communicatively connected to the target testing equipment, the cloud platform can test the real test object, replacing the method of directly virtualizing the test object in the cloud, thereby improving the reliability of the test results.

[0012] Optionally, the simulation test task includes: operating condition requirement data and test type. The operating condition requirement data is used to characterize the operating conditions required during the execution of the simulation test task. The target test device includes a processor-in-the-loop test device. The target test device is controlled to execute the simulation test task via a communication connection, and the test results are obtained as follows: in response to the target test device being a processor-in-the-loop test device and the test type being closed-loop simulation test, the simulation software deployed on the cloud platform is controlled to perform operating condition simulation based on the operating condition requirement data to obtain operating condition simulation data; the operating condition simulation data is transmitted via a communication connection to control the processor-in-the-loop test device to execute the simulation test task and obtain the test results.

[0013] The above-described optional embodiments of this application achieve the following technical effects: When the target test device is a processor-in-the-loop test device and the test type is closed-loop simulation, the cloud platform controls the simulation software deployed on it to perform operating condition simulation based on the operating condition requirement data, generating operating condition simulation data. This step transforms the abstract operating condition requirements into specific data that the simulation software can understand and execute, laying the foundation for subsequent closed-loop simulation testing. The generation of operating condition simulation data ensures the authenticity of the test. Through the stable communication connection established between the cloud platform and the processor-in-the-loop test device, the operating condition simulation data is transmitted to the processor-in-the-loop test device in real time and accurately. This data transmission process ensures the smooth progress of the closed-loop simulation test. After receiving the operating condition simulation data, the processor-in-the-loop test device can immediately start executing the simulation test task and obtain the test results. The automated execution of this closed-loop process significantly improves test efficiency and reduces test waiting time.

[0014] Optionally, the simulation test task further includes: an identifier for the software module under test (SDB), middleware including an intermediate conversion layer, transmitting operating condition simulation data via a communication connection to control the processor-in-the-loop test device to execute the simulation test task and obtain test results, including: transmitting operating condition simulation data from the cloud platform to the processor-in-the-loop test device via a communication connection, wherein the communication connection is a connection established between the relay service layer of the cloud platform and the intermediate conversion layer of the target test device; controlling the processor-in-the-loop test device to process the operating condition simulation data to obtain a second target simulation signal; controlling the processor-in-the-loop test device to test the test software module associated with the SDB identifier according to the second target simulation signal to obtain a decision signal for the test software module, wherein the test software module is deployed on the hardware resources included in the processor-in-the-loop test device; updating the operating condition simulation data according to the decision signal to obtain updated operating condition simulation data, wherein the decision signal is transmitted from the processor-in-the-loop test device to the cloud platform via the communication connection; controlling the processor-in-the-loop test device to test the test software module according to the updated operating condition simulation data to obtain test results, wherein the updated operating condition simulation data is transmitted from the cloud platform to the processor-in-the-loop test device via the communication connection.

[0015] The above-described optional embodiments of this application achieve the following technical effects: Through a communication connection, operating condition simulation data is transmitted from the cloud platform to the processor-in-the-loop test device. This step ensures that the execution of the test task is based on accurate operating condition data, improving the reliability and accuracy of the test. The processor-in-the-loop test device processes the operating condition simulation data to obtain a second target simulation signal. This conversion process transforms the abstract operating condition description into a specific signal executable by the processor-in-the-loop test device, thereby driving the execution of the test software module. The generation of the second target simulation signal ensures the effective application of the operating condition simulation data. The processor-in-the-loop test device tests the test software module associated with the identified software module under test according to the second target simulation signal, obtaining a decision signal for the test software module. Since the testing of the test software module is performed on real hardware, replacing the method of directly testing software functions on virtualized hardware in the cloud, the authenticity of the test and the reliability of the test results are guaranteed. Based on the decision signal, the industrial control simulation data is updated to obtain updated operating condition simulation data. This feedback mechanism means that the test process can dynamically adjust the operating conditions according to the actual output of the software module, realizing closed-loop control of the test and ensuring the comprehensiveness and authenticity of the test. The updated operating condition simulation data is then transmitted to the processor-in-the-loop test equipment for a new round of testing. This closed-loop testing method significantly improves the reliability of the test.

[0016] Optionally, the cloud platform is deployed with an object storage module, which is used to store operating condition requirement data. The automated simulation testing method also includes: generating a simulation container based on the identification number of the processor-in-the-loop test device and the operating condition requirement data. The simulation container is used for operating condition simulation. When the simulation container is in the startup state, the processor-in-the-loop test device that needs to interact with data is determined by the identification number.

[0017] The optional embodiments described above achieve the following technical effects: Dynamically creating simulation containers based on specific processor-in-the-loop test equipment and operational requirement data enables intelligent resource configuration and isolation. The generation of the simulation container ensures that each test task has an independent operating environment, avoiding resource conflicts. When the simulation container is in the startup state, the processor-in-the-loop test equipment requiring data interaction is identified through an identification number. This step enables the simulation container to establish communication with the correct target test equipment, ensuring accurate transmission of simulation results. The use of identification numbers not only simplifies the matching process between devices but also improves the accuracy and efficiency of data interaction.

[0018] Optionally, the cloud-based automated simulation testing method also includes: controlling the processor-in-the-loop test equipment to perform simulation testing tasks according to the clock signal provided by the simulation engine in the simulation container.

[0019] The above-mentioned optional embodiments of this application can achieve the following technical effects: According to the clock signal provided by the simulation engine in the simulation container, the processor-in-the-loop test device is controlled to execute simulation test tasks. This ensures that the actions between the cloud platform and the processor-in-the-loop test device are coordinated and consistent. Using the clock signal as a time reference, the simulation test can be carried out in an orderly manner under a pre-set time sequence, avoiding data disorder and test failure caused by time asynchrony, thereby improving the efficiency and reliability of the test.

[0020] Optionally, controlling the hardware-in-the-loop test equipment to process the operating condition simulation data to obtain a first target simulation signal includes: controlling the real-time machine to perform format conversion on the operating condition simulation data to obtain the first target simulation signal, wherein the real-time machine is deployed on the hardware-in-the-loop test equipment, and the real-time machine is used to convert the format of the operating condition simulation data into a communication protocol format adapted to the test object.

[0021] The above-mentioned optional embodiments of this application can achieve the following technical effects: the real-time machine is controlled to perform format conversion on the operating condition simulation data to obtain the first target simulation signal. This process is performed by the real-time machine. As a key component of the hardware-in-the-loop test equipment, the format conversion function of the real-time machine ensures that the operating condition simulation data can be accurately converted into a communication protocol format adapted to the test object. This operation simplifies the data transmission process and thus accelerates the test process.

[0022] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the executable program, wherein the executable program executes the cloud-based automated simulation testing method described in any of the above embodiments.

[0023] The electronic device provided in this application embodiment achieves the following technical effects: the executable program corresponding to the cloud platform-based automated simulation testing method described above is stored in the memory, and the executable program stored in the memory is executed by the processor, thereby improving the efficiency and reliability of simulation testing and solving the technical problem of how to improve the efficiency and reliability of simulation testing.

[0024] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, wherein the computer program is configured to execute the cloud-based automated simulation testing method described above when running on a computer or processor.

[0025] The computer-readable storage medium provided in this application embodiment achieves the following technical effects: it stores the computer program corresponding to the cloud platform-based automated simulation testing method in any of the above-mentioned methods in the computer-readable storage medium, and uses a processor to execute the computer program stored in the computer-readable storage medium, thereby improving the efficiency and reliability of simulation testing and solving the technical problem of how to improve the efficiency and reliability of simulation testing. Attached Figure Description

[0026] Figure 1 This is a flowchart of an automated simulation testing method based on a cloud platform provided in an embodiment of this application;

[0027] Figure 2 This is a system architecture diagram of an automated simulation testing system based on a cloud platform provided in one embodiment of this application;

[0028] Figure 3 This is a scheduling and orchestration diagram of a task by a cloud control platform provided in an embodiment of this application;

[0029] Figure 4 This is a structural block diagram of the hardware provided in one embodiment of this application, including the hardware on the ring test bench, the cloud, and the operating terminal.

[0030] Figure 5 This is an architecture diagram of a cloud platform in-loop closed-loop simulation provided in one embodiment of this application. Detailed Implementation

[0031] To make the technical problems, technical solutions, and beneficial effects solved by this application clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] This application provides a cloud-based automated vehicle testing method. Please refer to [link / reference]. Figure 1 This includes the following steps:

[0034] An automated simulation testing method based on a cloud platform is available for reference. Figure 1 This includes the following steps:

[0035] S10, Obtain the simulation test task, and determine the target test device from multiple test devices based on the simulation test task, wherein the test device is equipped with resources to execute the simulation test task;

[0036] S20 establishes a communication connection with the middleware of the target test equipment through the relay service layer of the cloud platform;

[0037] S30, via communication connection, controls the target test equipment to perform simulation test tasks and obtain test results.

[0038] The cloud platform parses the simulation test task request it receives, and based on the parsing results, determines the target test device from multiple test devices to execute the current simulation test task.

[0039] In one optional embodiment, the cloud platform obtains the current status of multiple test devices (such as occupancy, available resources, performance indicators, etc.), and determines the target test device that best matches the task requirements based on the current status of the multiple test devices.

[0040] Multiple test devices refer to a collection of test devices that can be scheduled by the cloud platform.

[0041] Optionally, the test equipment is equipped with resources for performing simulation test tasks. These resources refer to the hardware and software resources required to perform the simulation test tasks, which together determine whether the test equipment can effectively perform specific test tasks.

[0042] Optionally, hardware resources include computing resources, such as central processing units, graphics processing units, and digital signal processors, used to run simulation models and algorithms, process input data and generate output signals, and perform complex mathematical and logical operations; storage resources, such as random access memory, read-only memory, hard disk drives, solid-state drives, and memory cards, used to store simulation data, test software, configuration files, intermediate results, and test reports; network resources, such as network interface cards, routers, and switches, used for data transmission and communication to ensure that the test equipment can communicate with cloud platforms or other network components (such as middleware and data sources); dedicated hardware, such as ADAS (Advanced Driver Assistance Systems) hardware, domain controllers, and ECUs (Electronic Control Units), used for specific test environments to ensure that the test object can operate normally in the simulation environment; and physical resources, such as motion platforms, vehicle models, and environmental simulation devices, used to physically recreate test scenarios, such as vehicle dynamic behavior, road conditions, and wind resistance simulation.

[0043] Optionally, software resources include simulation software, used to create and simulate test environments, including vehicle dynamics models, scenario construction, sensor simulation, etc., which is the core tool for performing simulation tests; control software, such as Agent services, used to receive test tasks and instructions from the cloud platform, manage the hardware resources of the test equipment, execute test tasks, monitor the test status, and upload test results to the cloud platform; and middleware and communication protocol software, such as the DDS (Data Distribution Service) conversion layer, used to handle data format conversion and realize efficient data exchange between the test equipment, the cloud platform, and the simulation software.

[0044] Efficient communication between the cloud platform and the target test equipment is crucial for enabling remote control and data transmission. In this stage, the cloud platform's relay service layer acts as a communication bridge, establishing a communication connection with the middleware on the target test equipment to achieve bidirectional transmission of operational requirement data, test commands, and test results. The relay service layer uses standardized communication protocols (such as HTTP, TCP / IP, DDS, etc.) and ensures secure data transmission through a secure encrypted channel.

[0045] The relay service layer is responsible for managing and coordinating communication between the cloud platform and test equipment, ensuring the efficiency and security of data transmission, and providing necessary control interfaces for automated testing tasks. The middleware, deployed on the test equipment, is responsible for decoding test instructions from the cloud platform into commands that the hardware can directly execute, and encoding the raw data generated by the hardware into a format that the cloud platform can parse.

[0046] Optionally, before establishing a communication connection with the middleware of the target test device, the relay service layer needs to verify the identity of the middleware to ensure communication security and prevent unauthorized access. Furthermore, the relay service layer will dynamically adjust communication parameters based on network conditions, such as retransmission mechanisms, data compression, and error correction, to ensure communication stability and data integrity even under unstable network conditions.

[0047] Once a stable communication connection is established, the cloud platform can directly send simulation test task instructions to the target test equipment via the relay service layer. These instructions include operating condition settings, test scripts, test parameters, and other control commands. Upon receiving the instructions, the target test equipment will begin executing the simulation test task, which involves simulating vehicle dynamics, processor behavior, or the decision-making process of software modules under specific operating conditions. Test results (including but not limited to vehicle status data, processor response time, and software module output) are then collected, appropriately processed and encoded, and transmitted back to the cloud platform via the communication connection for subsequent analysis and report generation.

[0048] The automated simulation testing method based on a cloud platform provided in this application achieves the following technical effects: First, by acquiring and intelligently analyzing simulation test tasks through the cloud platform, the most suitable test equipment for executing the task, i.e., the target test equipment, is selected. This task-requirement-based test equipment selection mechanism significantly improves the targeted use of resources and avoids the problems of resource waste and long waiting times in traditional testing. Second, the relay service layer of the cloud platform establishes a communication connection with the middleware on the target test equipment, which is a key step in realizing remote control and data transmission. Finally, through the established communication connection, the cloud platform can control the target test equipment to execute simulation test tasks in real time. That is, through the established communication connection, the simulation test tasks can be remotely controlled to execute on real hardware devices on the cloud platform, which simplifies the testing process, improves testing efficiency, and further enhances the realism and reliability of the test. Therefore, this application embodiment can achieve the technical effect of improving the efficiency and reliability of simulation testing, solving the technical problem of how to improve the efficiency and reliability of simulation testing.

[0049] Optionally, the simulation test task includes: operating condition requirement data, which characterizes the operating conditions required during the execution of the simulation test task; the target test device includes a hardware-in-the-loop test device; the middleware includes a proxy service layer; establishing a communication connection with the middleware of the target test device through the relay service layer of the cloud platform includes: in response to the target test device being a hardware-in-the-loop test device, establishing a communication connection with the proxy service layer of the hardware-in-the-loop test device through the relay service layer of the cloud platform; controlling the target test device to execute the simulation test task and obtain test results through the communication connection includes: transmitting the operating condition requirement data from the cloud platform to the hardware-in-the-loop test device through the communication connection; controlling the simulation software deployed on the hardware-in-the-loop test device to perform operating condition simulation based on the operating condition requirement data, obtaining operating condition simulation data; and controlling the hardware-in-the-loop test device to execute the simulation test task and obtain test results based on the operating condition simulation data.

[0050] Operating condition requirements data define the environment and conditions simulated during test execution. These requirements include, but are not limited to, elements such as road type, weather conditions, and various obstacles, ensuring that the test comprehensively covers all possible operating scenarios that the autonomous driving system may encounter.

[0051] The cloud platform establishes a connection with the agent service layer on the hardware-in-the-loop test equipment through the relay service layer. This connection is the basis for data transmission and control commands.

[0052] Hardware-in-the-Loop (HIL) test equipment is a simulation platform used to test and verify the performance of system hardware. In particular, for autonomous vehicles, HIL test equipment can simulate the physical behavior of the vehicle and its systems.

[0053] The proxy service layer is a software component deployed on the hardware-in-the-loop testing equipment. It is responsible for receiving instructions from the cloud platform, executing local operations, and uploading the results back to the cloud platform.

[0054] Operating condition simulation data is virtual environment data generated by simulation software based on operating condition requirements data. It simulates the driving environment under specific operating conditions.

[0055] After transmitting the operating condition requirements data to the HIL testing equipment, the agent service layer is responsible for passing this data to the simulation software. The simulation software constructs a virtual environment based on the data and simulates the vehicle's response behavior within that environment, generating operating condition simulation data. Subsequently, the testing equipment executes predetermined simulation test tasks based on the operating condition simulation data, obtaining the simulation test results.

[0056] The optional embodiments described above achieve the following technical effects: A communication connection is established between the relay service layer of the cloud platform and the proxy service layer of the target test equipment. This communication architecture enables data transmission and control command issuance between the cloud platform and the hardware-in-the-loop test equipment. After transmitting the operating condition requirement data to the hardware-in-the-loop test equipment via the communication connection, the simulation software deployed on the hardware-in-the-loop equipment is controlled to perform operating condition simulation, generating operating condition simulation data. The generation of this data provides a foundation for subsequent testing tasks, ensuring the realism of the test environment. Based on the operating condition simulation data, the hardware-in-the-loop test equipment is controlled to execute simulation test tasks, ultimately obtaining the test results. Because it is based on the communication connection, the hardware-in-the-loop test equipment can be directly controlled to perform test tasks, replacing the direct virtualization of hardware into software in the cloud for test execution, thus ensuring the objectivity and accuracy of the test results.

[0057] Optionally, the simulation test task includes: identifying the object under test; controlling the hardware-in-the-loop test equipment to execute the simulation test task based on the operating condition simulation data to obtain test results; including: controlling the hardware-in-the-loop test equipment to process the operating condition simulation data to obtain a first target simulation signal; controlling the hardware-in-the-loop test equipment to test the test object associated with the object under test based on the first target simulation signal to obtain test results, wherein the test object and the target test equipment are communicatively connected.

[0058] When the target test device is a hardware-in-the-loop test device, the Object Under Test (OUT) identifier refers to a specific hardware module. It is the basis for performing simulation tests and is used to clearly identify the test object, such as a specific domain controller. That is, in the test process, the OUT identifier is unique and is used to uniquely identify the hardware to be tested in the system, ensuring the accurate targeting of the test task.

[0059] The first target analog signal is the operating condition simulation data processed by the HIL test equipment and converted into a signal that matches the object under test, such as a CAN bus signal, LIN signal, or a specific sensor input format, which can be directly recognized and responded to by the object under hardware-in-the-loop testing.

[0060] Establish an effective communication connection between the test object (such as a domain controller) and the HIL test equipment to facilitate signal input and output, ensure that test commands can be received by the test object, and that test results can be collected by the HIL test equipment.

[0061] During test execution, the HIL test equipment sends a first target analog signal to the test object. Upon receiving the signal, the test object executes a response action according to pre-programmed logic. The test equipment monitors the test object's response through sensors or dedicated hardware interfaces, ultimately generating test results. These results are uploaded to a cloud platform for further analysis and report generation.

[0062] The above-described optional embodiments of this application achieve the following technical effects: Through instructions from the cloud platform, the hardware-in-the-loop testing equipment can convert operational condition simulation data into a first target simulation signal, which is directly applied to the object under test. The generation of the first target simulation signal ensures the matching between the test conditions and the test object, enhancing the relevance of the test and further improving test efficiency. Then, the hardware-in-the-loop testing equipment is controlled to test the test object associated with the object under test identifier according to the first target simulation signal. Since the test object is communicatively connected to the target testing equipment, the cloud platform can test the real test object, replacing the method of directly virtualizing the test object in the cloud, thereby improving the reliability of the test results.

[0063] Optionally, the simulation test task includes: operating condition requirement data and test type. The operating condition requirement data is used to characterize the operating conditions required during the execution of the simulation test task. The target test device includes a processor-in-the-loop test device. The target test device is controlled to execute the simulation test task via a communication connection, and the test results are obtained as follows: in response to the target test device being a processor-in-the-loop test device and the test type being closed-loop simulation test, the simulation software deployed on the cloud platform is controlled to perform operating condition simulation based on the operating condition requirement data to obtain operating condition simulation data; the operating condition simulation data is transmitted via a communication connection to control the processor-in-the-loop test device to execute the simulation test task and obtain the test results.

[0064] Closed-loop simulation testing simulates the interaction between the test object and the environment through continuous iteration. In this process, the output of the test object (such as decision signals) affects the subsequent operating condition simulation data, which in turn affects the input of the test object in the next cycle, forming a closed-loop interaction process.

[0065] The test type also includes open-loop recharge testing. Unlike closed-loop simulation testing, open-loop recharge testing is conducted under preset conditions. The inputs in the test are fixed, and the output of the test object is obtained based on these inputs. Then, the output is evaluated to see if it meets expectations, but the output does not affect the subsequent operating condition simulation data.

[0066] Processor-in-the-Loop (PIL) testing equipment: used to test and verify the performance of software algorithms or modules running on a processor.

[0067] The simulation software on the cloud platform will construct a series of virtual driving scenarios based on the input working condition requirements data. These scenarios include, but are not limited to, city streets, highways, and complex intersections. At the same time, it also needs to simulate weather conditions, road surface conditions, and the behavior of traffic participants to generate working condition simulation data.

[0068] Optionally, the cloud platform establishes a communication connection with the PIL device's middleware through a relay service layer, and then sends the operating condition simulation data to the PIL device. After receiving the data, the PIL device begins to execute the simulation test task and obtains the test results. In the closed-loop simulation test mode, the decision signals of the test object are fed back to the simulation software on the cloud platform in real time, forming a dynamic interactive process.

[0069] The above-described optional embodiments of this application achieve the following technical effects: When the target test device is a processor-in-the-loop test device and the test type is closed-loop simulation, the cloud platform controls the simulation software deployed on it to perform operating condition simulation based on the operating condition requirement data, generating operating condition simulation data. This step transforms the abstract operating condition requirements into specific data that the simulation software can understand and execute, laying the foundation for subsequent closed-loop simulation testing. The generation of operating condition simulation data ensures the authenticity of the test. Through the stable communication connection established between the cloud platform and the processor-in-the-loop test device, the operating condition simulation data is transmitted to the processor-in-the-loop test device in real time and accurately. This data transmission process ensures the smooth progress of the closed-loop simulation test. After receiving the operating condition simulation data, the processor-in-the-loop test device can immediately start executing the simulation test task and obtain the test results. The automated execution of this closed-loop process significantly improves test efficiency and reduces test waiting time.

[0070] Optionally, the simulation test task further includes: an identifier for the software module under test (SDB), middleware including an intermediate conversion layer, transmitting operating condition simulation data via a communication connection to control the processor-in-the-loop test device to execute the simulation test task and obtain test results, including: transmitting operating condition simulation data from the cloud platform to the processor-in-the-loop test device via a communication connection, wherein the communication connection is a connection established between the relay service layer of the cloud platform and the intermediate conversion layer of the target test device; controlling the processor-in-the-loop test device to process the operating condition simulation data to obtain a second target simulation signal; controlling the processor-in-the-loop test device to test the test software module associated with the SDB identifier according to the second target simulation signal to obtain a decision signal for the test software module, wherein the test software module is deployed on the hardware resources included in the processor-in-the-loop test device; updating the operating condition simulation data according to the decision signal to obtain updated operating condition simulation data, wherein the decision signal is transmitted from the processor-in-the-loop test device to the cloud platform via the communication connection; controlling the processor-in-the-loop test device to test the test software module according to the updated operating condition simulation data to obtain test results, wherein the updated operating condition simulation data is transmitted from the cloud platform to the processor-in-the-loop test device via the communication connection.

[0071] The software module under test (MDT) identifier is used to identify the software module or algorithm to be tested. In autonomous driving systems, this can be the software version number of a specific domain controller or the ID number of a specific software function module.

[0072] The intermediate conversion layer is deployed on the processor-in-the-loop test equipment. Its main functions include data format conversion, signal processing, and communication protocol adaptation, ensuring that data from the cloud platform can be correctly interpreted and used by the PIL equipment.

[0073] The simulation software on the cloud platform generates corresponding operating condition simulation data, which is sent to the PIL device through a communication connection. After receiving the operating condition simulation data, the PIL device converts the format of the operating condition simulation data to obtain the second target simulation signal, ensuring that the software module under test can correctly receive and use these signals.

[0074] The processor-in-the-loop (PIL) test equipment, based on the second target simulation signal, tests the test software module associated with the software module under test (SDB) identifier, obtaining the decision signal of the test software module. This process verifies the functionality and performance of the software module under specific operating conditions. The generated decision signal is then transmitted back from the PIL equipment to the cloud platform via a communication connection. The simulation software on the cloud platform updates the operating condition simulation data in the virtual environment based on these signals and controls the PIL equipment to test the test software module based on the updated operating condition simulation data, obtaining the test results and forming a closed-loop simulation process.

[0075] The above-described optional embodiments of this application achieve the following technical effects: Through a communication connection, operating condition simulation data is transmitted from the cloud platform to the processor-in-the-loop test device. This step ensures that the execution of the test task is based on accurate operating condition data, improving the reliability and accuracy of the test. The processor-in-the-loop test device processes the operating condition simulation data to obtain a second target simulation signal. This conversion process transforms the abstract operating condition description into a specific signal executable by the processor-in-the-loop test device, thereby driving the execution of the test software module. The generation of the second target simulation signal ensures the effective application of the operating condition simulation data. The processor-in-the-loop test device tests the test software module associated with the identified software module under test according to the second target simulation signal, obtaining a decision signal for the test software module. Since the testing of the test software module is performed on real hardware, replacing the method of directly testing software functions on virtualized hardware in the cloud, the authenticity of the test and the reliability of the test results are guaranteed. Based on the decision signal, the industrial control simulation data is updated to obtain updated operating condition simulation data. This feedback mechanism means that the test process can dynamically adjust the operating conditions according to the actual output of the software module, realizing closed-loop control of the test and ensuring the comprehensiveness and authenticity of the test. The updated operating condition simulation data is then transmitted to the processor-in-the-loop test equipment for a new round of testing. This closed-loop testing method significantly improves the reliability of the test.

[0076] Optionally, the cloud platform is deployed with an object storage module, which is used to store operating condition requirement data. The automated simulation testing method also includes: generating a simulation container based on the identification number of the processor-in-the-loop test device and the operating condition requirement data. The simulation container is used for operating condition simulation. When the simulation container is in the startup state, the processor-in-the-loop test device that needs to interact with data is determined by the identification number.

[0077] Object storage modules are used to store unstructured data, such as files, images, videos, and simulation scene data packages. Compared to traditional block storage or file systems, object storage offers greater scalability and data access flexibility.

[0078] The processor-in-the-loop test device identification number is a unique identifier for each processor-in-the-loop test device, used to locate and schedule specific test resources in the cloud platform.

[0079] A simulation container refers to a runtime environment created on a cloud platform using container technology, used to execute specific simulation testing tasks. A simulation container encapsulates simulation software, operating condition data, and other resources required to perform the test.

[0080] When generating a simulation container, the cloud platform automatically configures the environment variables within the container, including but not limited to the simulation software version, the path to the operating data, and communication protocol parameters, to ensure that the simulation container can successfully execute test tasks.

[0081] In one optional embodiment, the cloud platform establishes a communication connection between the simulation container and the corresponding PIL device using an identification number. When the simulation container starts, it loads and parses the operating condition requirement data from the cloud platform's object storage module, and then begins simulating the operating conditions. Simultaneously, the simulation container sends the generated operating condition simulation data to the designated PIL device via the communication connection. Upon receiving the signal, the PIL device begins executing the simulation test task. The decision signals or test results from the software module are then transmitted back to the simulation container via the same communication connection, completing one data interaction cycle.

[0082] The optional embodiments described above achieve the following technical effects: Dynamically creating simulation containers based on specific processor-in-the-loop test equipment and operational requirement data enables intelligent resource configuration and isolation. The generation of the simulation container ensures that each test task has an independent operating environment, avoiding resource conflicts. When the simulation container is in the startup state, the processor-in-the-loop test equipment requiring data interaction is identified through an identification number. This step enables the simulation container to establish communication with the correct target test equipment, ensuring accurate transmission of simulation results. The use of identification numbers not only simplifies the matching process between devices but also improves the accuracy and efficiency of data interaction.

[0083] Optionally, the cloud-based automated simulation testing method also includes: controlling the processor-in-the-loop test equipment to perform simulation testing tasks according to the clock signal provided by the simulation engine in the simulation container.

[0084] A simulation engine refers to the software running inside a simulation container, used to simulate various driving scenarios.

[0085] In simulation testing, the clock signal provided by the simulation engine plays the role of a time reference. It is used to synchronize the data flow and event sequence between the simulation engine and the PIL device to ensure the time consistency of the entire testing process.

[0086] The above-mentioned optional embodiments of this application can achieve the following technical effects: According to the clock signal provided by the simulation engine in the simulation container, the processor-in-the-loop test device is controlled to execute simulation test tasks. This ensures that the actions between the cloud platform and the processor-in-the-loop test device are coordinated and consistent. Using the clock signal as a time reference, the simulation test can be carried out in an orderly manner under a pre-set time sequence, avoiding data disorder and test failure caused by time asynchrony, thereby improving the efficiency and reliability of the test.

[0087] Optionally, controlling the hardware-in-the-loop test equipment to process the operating condition simulation data to obtain a first target simulation signal includes: controlling the real-time machine to perform format conversion on the operating condition simulation data to obtain the first target simulation signal, wherein the real-time machine is deployed on the hardware-in-the-loop test equipment, and the real-time machine is used to convert the format of the operating condition simulation data into a communication protocol format adapted to the test object.

[0088] Because the original format of the operating condition simulation data is incompatible with the communication protocol between the test object and the test object, the real-time machine needs to convert the operating condition simulation data into a format that the test object can recognize and use. For example, cloud platforms use JSON or XML format to store data, while ECUs or domain controllers communicate via CAN bus or Ethernet protocol, and the data format is binary or a specific text format. The task of the real-time machine is to convert the operating condition simulation data into the format required by these communication protocols.

[0089] Optionally, in addition to format conversion, the real-time machine is also responsible for encapsulating the converted data according to the communication protocol standard of the test object, ensuring that the data can be correctly transmitted between the hardware-in-the-loop test equipment and the test object. This includes setting the correct data packet header, check sequence, and necessary control signals to match the requirements of CAN, Ethernet, or any other specific communication protocol.

[0090] Furthermore, the real-time machine (RTM) is equipped with a wide range of interfaces, ensuring compatibility with various hardware and software systems, including but not limited to sensor simulators, actuator simulators, domain controllers, and other simulation software. This high compatibility ensures that the RTM can serve as a universal interface, connecting cloud platforms, HIL test benches, and the object under test (DUT) to achieve seamless data transfer.

[0091] Meanwhile, the real-time machine (RTM) has built-in support for multiple communication protocols, enabling it to process and convert various data formats to adapt to different test objects and communication standards. This multi-protocol support capability allows the RTM to act as an effective communication coordinator in complex test environments, ensuring the correct transmission of data.

[0092] The above-mentioned optional embodiments of this application can achieve the following technical effects: the real-time machine is controlled to perform format conversion on the operating condition simulation data to obtain the first target simulation signal. This process is performed by the real-time machine. As a key component of the hardware-in-the-loop test equipment, the format conversion function of the real-time machine ensures that the operating condition simulation data can be accurately converted into a communication protocol format adapted to the test object. This operation simplifies the data transmission process and thus accelerates the test process.

[0093] In one alternative embodiment, the cloud platform is not only responsible for receiving and managing simulation test tasks, but also bears the important responsibility of resource allocation and status monitoring. Once the object to be tested (e.g., a hardware unit or software module) is determined, the cloud platform immediately queries the status of all online test devices capable of executing test tasks to understand which test devices are available and which are being used by other test tasks.

[0094] Online testing equipment refers to testing equipment that has established a communication connection with the cloud platform. These testing devices maintain real-time communication with the cloud platform through a stable network connection, enabling the cloud platform to monitor their operating status and availability in real time.

[0095] In another alternative embodiment, the cloud platform determines the target test device based on the status of multiple test devices fed back by the scheduling system, and then establishes a communication connection with the target test device.

[0096] According to another aspect of the embodiments of this application, an automated simulation testing system based on a cloud platform is also provided, including: test management software, a vehicle dynamics simulation model, a real-time machine, scene simulation software, a video injection module, a driver's cockpit simulator, visualization system software, and a controller under test, etc. The controlled object includes a hardware-in-the-loop simulation bench and a domain controller backfeed test bench cluster.

[0097] The system scheduling process is as follows Figure 2 As shown, it includes:

[0098] (1) Hardware-in-the-loop (HIL) cluster access to the cloud: First, an HIL simulation task is initiated on the cloud front-end interface. The simulation task is recorded in the form of a task list, which includes the simulation test cases to be tested, the associated simulation scenarios, and the simulation map. After receiving the task, the Scheduler module queries the HIL rack resources currently connected to the system and performs task distribution and scheduling. The cloud control platform schedules and orchestrates the tasks as follows: Figure 3As shown, the cloud control platform writes test cases and creates test scripts, activates the HIL bench function, establishes test nodes, and creates scheduling tasks. The cloud platform triggers the execution of the scheduling tasks and selects bench resources. The bench executes the test tasks and uploads the test results and bench resource status to the cloud, generating bench monitoring reports and submitting test reports, thereby realizing the selection of bench resources and the querying of simulation results and bench status. The HIL host computer deploys the Agent module, which is responsible for managing the host computer's information and communication with the simulation software. In HIL testing, the simulation software is deployed on the host computer of the HIL bench, on the same computer as the Agent service. After receiving the simulation task, the Agent downloads the scene and map files from object storage to the local folder file system. The simulation software starts the simulation and communicates with the test equipment, writing the test result data to the file. The Agent obtains the simulation end information through status query, retrieves the simulation results from the result data file, and reports them to the cloud. The simservice records the results of this simulation in the database. The Agent synchronizes the local host computer information (remote desktop connection method, etc.) and the current status of the simulation software to the cloud.

[0099] HIL terminal connection reference with cloud and operator terminal Figure 4 The operating end includes ECU software, test engineering, test management software, and scenario simulation software, while the bench end includes a real-time machine, video injection equipment, and domain controller. The HIL-in-the-loop bench, including the cockpit simulator, consists of two main parts: first, the cockpit controller, which integrates key components such as the steering simulator, brake pedal, accelerator pedal, gear selector, and instrument panel; second, the six-degree-of-freedom hydraulic motion platform, which can be configured to suit different test requirements. The cockpit position needs to be adjusted according to the instructions on the visualization terminal to ensure the driver experiences an immersive visual experience. The controller inside the cockpit can receive real-time transmitted vehicle dynamics parameters, thereby simulating the vehicle's dynamic characteristics. Simultaneously, the cockpit can record various driver commands and transmit them to the controller under test to achieve a realistic driver experience in the human-in-the-loop simulation test.

[0100] Alternatively, the vehicle dynamics module can be replaced by various vehicle dynamics simulation software, whose parameters can be adjusted and calibrated according to the actual vehicle model to ensure high-precision vehicle dynamics simulation. The compiled vehicle dynamics module is processed by a real-time machine and can calculate various motion parameters based on the input vehicle commands.

[0101] Scene simulation software can utilize various simulation tools as substitutes, and the calculated vehicle kinematic parameters are then imported into the software. This software integrates multiple sensor simulation models suitable for autonomous driving and allows for customized secondary development based on actual sensor parameters to ensure accuracy during the simulation process. Within the scene simulation software, a virtual vehicle operating environment can be constructed, including road network elements, various obstacles, and weather conditions. The software combines the calculated vehicle dynamics parameters with the synchronous processing of sensor simulation data and scene simulation data, ultimately presenting the entire process in a visual rendering format.

[0102] The calculation results from each sensor are converted by a real-time machine and transmitted to the controller under test via protocols such as CAN and Ethernet.

[0103] The visualization results are transmitted to the controller under test via the video injection module through HDMI (an uncompressed high-definition digital audio / video interface) in real time and then transmitted to the controller under test through the required interface protocol. At the same time, the visualization rendering screen is adjusted according to the selected visualization terminal to ensure an intuitive observation experience.

[0104] (2) Domain Controller-in-the-Loop (DIL) Cluster Access to the Cloud: First, initiate a PIL simulation task on the cloud front-end interface. The simulation task is recorded in the form of a task list. PIL testing includes two types: closed-loop simulation and open-loop backfeedback. After receiving the task, the Scheduler module queries the PIL rack resources currently attached to the system according to the task type and performs task distribution and scheduling. When performing open-loop backfeedback, the Scheduler module issues a backfeedback data task, and the PIL end pulls backfeedback data from object storage to start the backfeedback evaluation task. When performing closed-loop simulation, the simulator in the cloud sim-pod needs to be invoked through the Scheduler module in the cloud. Data closed-loop interaction is performed through the simulator. This closed-loop link requires the software under test in PIL to support the simulation virtual clock scheduling. The closed-loop simulation link is as follows: Figure 5 As shown, the simulator generates simulation data based on scene files and map files. The simulation data is sent to the PIL device through Trans (i.e., the relay service layer). The middleware converts the simulation data, and the converted data is input into the software system (such as the navigation module). The output of the software system is further fed back to the simulator through Trans to update the simulator's simulation results, forming a complete closed-loop simulation.

[0105] During closed-loop simulation, the TCP communication program deployed on PIL needs to support data interaction with the simulator and receiving PIL control information (via Trans, i.e., the relay service layer). PIL devices connect to the relay server, which manages these PIL devices, handles data distribution and message exchange, provides PIL device status queries, and can send commands to PIL devices (requiring PIL itself to support control). When starting a closed-loop simulation task, the Scheduler queries available PIL devices, creates a simulation pod by combining the PIL device ID with the task parameters, and during the simulation, the sim-pod communicates with specific PIL devices through the relay service. The simulation platform interface controls the PIL devices via simService -> Relay Server -> PIL Device.

[0106] Optionally, the PIL device uses the timing provided by the simulation engine in sim-pod, with a clock signal of 100Hz (10ms; however, since the network is dynamic, the clock signal will not be exactly 10ms).

[0107] Optionally, when the PIL device and the simulation software are linked to different relay service nodes, the relay message will be relayed once between the nodes within the relay service. To avoid this relay, the simulation software can first query the node linked to the target device when linking to the relay service. In the event of relay service maintenance or other failures, it is inevitable that internal relay messages will be required.

[0108] Optionally, the relay service provides a fixed IP address or domain name on the cloud, and PIL devices access the cloud via the IP address or domain name.

[0109] Optionally, message forwarding for the relay service is based on a TCP long connection, while the query and control service is based on the HTTP protocol.

[0110] Optionally, the cloud-based automated simulation testing system includes a test bench and an operator terminal connected remotely to the cloud. The cloud includes functions such as HIL task and PIL task management, scenario management, algorithm management, and report viewing, used to distribute tasks to different test benches. The test bench includes a HIL test bench cluster and a PIL cluster. The HIL test bench cluster includes multiple HIL test benches for connecting to the ECU (Electronic Control Unit) under test; the PIL cluster contains domain controller cabinets for multiple platforms. The operator terminal includes a software management subsystem, a test management subsystem, an experiment management subsystem, a HIL test bench scheduling subsystem, and a scenario simulation subsystem.

[0111] The software management subsystem receives ECU software and automated test projects; the HIL / PIL bench scheduling subsystem creates test nodes, builds the test environment for execution on the HIL / PIL bench, and creates scheduling tasks. These tasks extract the signal values ​​required for ECU software testing from the test management subsystem, store them in the HIL / PIL bench's test environment, and trigger the software management subsystem to execute ECU test projects and automated test projects on the HIL bench. The test management subsystem creates test projects, establishes corresponding test tasks, and associates these tasks with scheduling tasks in the HIL / PIL bench scheduling subsystem. Each test task is also associated with a specific test case. When the test management subsystem initiates a relevant test task, the HIL bench scheduling subsystem checks the scheduling tasks associated with the test task to determine if the corresponding HIL / PIL bench is occupied. If the bench is occupied, the test task is placed in a queue to wait until the bench is free. If the bench is free, the system automatically distributes the ECU software and corresponding automated test projects to the bench's workspace and writes the automated test projects into the ECU under test through the test management subsystem. After successfully writing the ECU software, the automated test program will run automatically and the test results will be exported.

[0112] It is understood that the cloud-based automated simulation testing system in this application embodiment can virtualize and schedule the ECU under test into test tasks, dynamically update and share the ECU cluster according to different projects. Through agent services and the Trans layer, hardware device domain controllers and HIL test benches are virtualized in the cloud and scheduled within cloud-based Kubernetes container components. This avoids the need for direct vECU virtualization within cloud pods. Controlling the entire system via the cloud platform allows for control of the entire automated testing process, enabling remote scheduling, monitoring, and reporting of the test benches.

[0113] Furthermore, the test benches in the testing system include Domain Controller Backfeeding (PIL) testing and Hardware-in-the-Loop (HIL) simulation testing, and can dynamically expand the number of benches as dynamic resources for cloud testing. Software updates are dynamically scheduled to test tasks based on the needs of different projects and platforms. Moreover, the testing system supports access to multiple domain controller systems and can automatically update the domain controllers under test and test cases in the cluster via online upgrade services. Simultaneously, the testing system supports PIL cloud-based closed-loop simulation, which, compared to the conventional method of requiring a dedicated computer for closed-loop backfeeding of a single domain controller locally, improves the convenience of cloud service scheduling.

[0114] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the executable program, wherein the executable program executes the cloud-based automated simulation testing method described in any of the above embodiments.

[0115] The electronic device provided in this application embodiment achieves the following technical effects: the executable program corresponding to the cloud platform-based automated simulation testing method described above is stored in the memory, and the executable program stored in the memory is executed by the processor, thereby improving the efficiency and reliability of simulation testing and solving the technical problem of how to improve the efficiency and reliability of simulation testing.

[0116] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, wherein the computer program is configured to execute the cloud-based automated simulation testing method described above when running on a computer or processor.

[0117] The computer-readable storage medium provided in this application embodiment achieves the following technical effects: it stores the computer program corresponding to the cloud platform-based automated simulation testing method in any of the above-mentioned methods in the computer-readable storage medium, and uses a processor to execute the computer program stored in the computer-readable storage medium, thereby improving the efficiency and reliability of simulation testing and solving the technical problem of how to improve the efficiency and reliability of simulation testing.

[0118] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0119] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0120] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0121] In this application, "multiple" refers to two or more.

[0122] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0123] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0124] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0125] Unless otherwise specified, all steps in this application may be performed sequentially or randomly. For example, if the method includes steps A and B, it means that the method may include steps A and B performed sequentially, or it may include steps B and A performed sequentially. For example, if the method may also include step C, it means that step C may be added to the method in any order. For example, the method may include steps A, B, and C, or it may include steps A, C, and B, or it may include steps C, A, and B, etc.

[0126] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An automated simulation testing method based on a cloud platform, characterized in that, include: Obtain a simulation test task, and determine a target test device from multiple test devices based on the simulation test task, wherein the test device is equipped with resources to execute the simulation test task; A communication connection is established with the middleware of the target testing device through the relay service layer of the cloud platform; The target test device is controlled to perform the simulation test task via the communication connection to obtain test results.

2. The automated simulation testing method according to claim 1, characterized in that, The simulation test task includes: operating condition requirement data, which characterizes the operating conditions required during the execution of the simulation test task; the target test equipment includes a hardware-in-the-loop test equipment; the middleware includes a proxy service layer; and establishing a communication connection with the middleware of the target test equipment through the relay service layer of the cloud platform includes: In response to the fact that the target test device is a hardware-in-the-loop test device, a communication connection is established with the proxy service layer of the hardware-in-the-loop test device through the relay service layer of the cloud platform; The target test device is controlled to perform the simulation test task via the communication connection, and the test results obtained include: The operating condition requirement data is transmitted from the cloud platform to the hardware-in-the-loop test equipment via the communication connection. Based on the operating condition requirement data, the simulation software deployed on the hardware-in-the-loop test equipment is controlled to perform operating condition simulation to obtain the operating condition simulation data. Based on the simulated operating data, the hardware-in-the-loop test equipment is controlled to execute the simulation test task, and the test results are obtained.

3. The automated simulation testing method according to claim 2, characterized in that, The simulation test task includes: identifying the object under test; controlling the hardware-in-the-loop test equipment to execute the simulation test task based on the simulated operating conditions data; and obtaining the test results, including: The hardware-in-the-loop test equipment is controlled to process the operating condition simulation data to obtain a first target simulation signal; The hardware-in-the-loop test equipment is controlled to test the test object associated with the test object identifier according to the first target analog signal, and the test result is obtained, wherein the test object is communicatively connected to the target test equipment.

4. The automated simulation testing method according to claim 1, characterized in that, The simulation test task includes: operating condition requirement data and test type. The operating condition requirement data is used to characterize the operating conditions required during the execution of the simulation test task. The target test device includes a processor-in-the-loop test device. The simulation test task is executed by controlling the target test device via the communication connection, and the test results obtained include: In response to the target test device being the processor-in-the-loop test device and the test type being closed-loop simulation test, the simulation software deployed on the cloud platform is controlled to perform operating condition simulation based on the operating condition requirement data to obtain the operating condition simulation data. The operating condition simulation data is transmitted via the communication connection to control the processor-in-the-loop test equipment to execute the simulation test task and obtain the test results.

5. The automated simulation testing method according to claim 4, characterized in that, The simulation test task further includes: an identifier for the software module under test; the middleware includes an intermediate conversion layer; the operating condition simulation data is transmitted via the communication connection to control the processor-in-the-loop test equipment to execute the simulation test task and obtain the test results, including: The operating condition simulation data is transmitted from the cloud platform to the processor-in-the-loop test device via the communication connection, wherein the communication connection is a connection established between the relay service layer of the cloud platform and the intermediate conversion layer of the target test device; The processor-in-the-loop test equipment is controlled to process the operating condition simulation data to obtain a second target simulation signal; The processor-in-the-loop test equipment is controlled to test the test software module associated with the identifier of the software module under test according to the second target simulation signal, and the decision signal of the test software module is obtained, wherein the test software module is deployed on the hardware resources included in the processor-in-the-loop test equipment; Based on the decision signal, the operating condition simulation data is updated to obtain updated operating condition simulation data, wherein the decision signal is transmitted from the processor-in-the-loop test device to the cloud platform via the communication connection; The processor-in-the-loop test equipment is controlled to test the test software module based on the updated operating condition simulation data, and the test results are obtained. The updated operating condition simulation data is transmitted from the cloud platform to the processor-in-the-loop test equipment via the communication connection.

6. The automated simulation testing method according to claim 4, characterized in that, The cloud platform is equipped with an object storage module, which is used to store the working condition requirement data. The method further includes: A simulation container is generated based on the identification number of the processor-in-the-loop test device and the operating condition requirement data. The simulation container is used for operating condition simulation. When the simulation container is in the startup state, the processor-in-the-loop test device that needs to interact with data is determined by the identification number.

7. The automated simulation testing method according to claim 6, characterized in that, The method further includes: The processor-in-the-loop test device is controlled to execute the simulation test task based on the clock signal provided by the simulation engine in the simulation container.

8. The automated simulation testing method according to claim 3, characterized in that, Controlling the hardware-in-the-loop test equipment to process the operating condition simulation data to obtain the first target simulation signal includes: The real-time machine is controlled to convert the format of the operating condition simulation data to obtain the first target simulation signal. The real-time machine is deployed on the hardware-in-the-loop test equipment and is used to convert the format of the operating condition simulation data into a communication protocol format adapted to the test object.

9. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the executable program, wherein the executable program executes the cloud-based automated simulation testing method according to any one of claims 1 to 8 when it runs.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the cloud-based automated simulation testing method as described in any one of claims 1 to 8 when run on a computer or processor.

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