Function test method and system for electronic control actuating mechanism in vehicle

Abstract

The invention discloses a function test method and system for an electric control executing mechanism in a vehicle. The method comprises the following steps: in response to a test instruction triggered for a to-be-tested electric control execution mechanism of a vehicle, generating a test case corresponding to the to-be-tested electric control execution mechanism; based on a target test scene indicated by the test case, determining a target simulation model from the simulation model set, and determining a control signal of a motor of the to-be-tested electric control execution mechanism; performing analogue simulation on the target test scene by using the target simulation model, and triggering a generator to drive a to-be-tested electric control execution mechanism in the simulated target test scene by using the control signal so as to simulate and execute a to-be-tested target function in the target test scene and obtain a simulation result; and determining a test result of the target function based on the simulation result. The technical problem that the function test effect of the electric control executing mechanism in the vehicle is poor is solved.

Description

Technical Field

[0001] This application relates to the field of vehicle testing technology, and more specifically, to a method and system for testing the function of electronic control actuators in a vehicle. Background Technology

[0002] Currently, functional testing of electronic control actuators in vehicles (such as the rear spoiler) employs real-vehicle testing. However, real-vehicle testing relies on manual operation, inevitably introducing subjective errors. Coupled with a lack of automation, this results in lengthy testing cycles and low efficiency. More importantly, real-world driving environments encompass numerous complex conditions, ranging from high-speed driving to extreme weather conditions. These conditions are difficult to reproduce under laboratory conditions, leading to insufficient test coverage, particularly challenging the verification of edge cases and boundary conditions.

[0003] While real-vehicle testing reflects the behavior of electronic control actuators in natural environments to some extent, the significant consumption of human resources, time, and costs, as well as limitations of the testing scenarios, often prevents test results from providing a comprehensive and in-depth functional analysis. Consequently, the testing performance of electronic control actuators in vehicles falls short of expectations, exhibiting issues such as functional omissions and inadequate responses to abnormal operating conditions, severely impacting product reliability and market competitiveness. Therefore, the technical problem of poor functional testing results for electronic control actuators in vehicles persists.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a method and system for functional testing of electronic control actuators in vehicles, so as to at least solve the technical problem of poor functional testing results of electronic control actuators in vehicles.

[0006] According to one aspect of the embodiments of this application, a method for functional testing of an electronically controlled actuator in a vehicle is provided. The method includes: generating test cases corresponding to the electronically controlled actuator under test in response to a test command triggered for the electronically controlled actuator under test; determining a target simulation model from a set of simulation models and determining a control signal for the motor of the electronically controlled actuator under test based on a target test scenario indicated by the test cases, wherein different simulation models in the set of simulation models correspond to different test scenarios for the electronically controlled actuator under test, and different test scenarios are used to provide an environment for testing different functions of the electronically controlled actuator under test; simulating the target test scenario using the target simulation model, and triggering the motor to drive the electronically controlled actuator under test in the simulated target test scenario using the control signal to simulate the execution of the target function in the target test scenario, and obtaining simulation results; and determining test results for the target function based on the simulation results, wherein the test results are used to represent the accuracy of the electronically controlled actuator under test in simulating the execution of the target function in the simulated target test scenario.

[0007] Optionally, determining the control signal of the motor of the electronically controlled actuator under test includes: converting the test case into an electrical signal of the vehicle, wherein the electrical signal is used to represent the operating state of the vehicle during the test of the target function; and determining the control signal based on the electrical signal.

[0008] Optionally, the electrical signals include a first electrical signal and a second electrical signal. The first electrical signal represents the operating state of the network in the vehicle, and the second electrical signal represents the operating state of the motor. Based on the electrical signals, the control signal is determined, including: using a network simulation module to simulate the operating state of the network based on the first electrical signal to obtain a network simulation result; and using a motor signal simulation module to simulate the operating state of the motor based on the second electrical signal to obtain a motor simulation result; and using the domain controller corresponding to the electronic control actuator under test to determine the control signal based on the network simulation result and the motor simulation result.

[0009] Optionally, the second electrical signal includes a first sub-electrical signal and a second sub-electrical signal. The first sub-electrical signal represents the position state of the motor, and the second sub-electrical signal represents the operating state of the motor. The motor signal simulation module includes a first simulation module and a second simulation module. The first simulation module corresponds to the first sub-electrical signal, and the second simulation module corresponds to the second sub-electrical signal. The test case is converted into the vehicle's electrical signal, including: using the first simulation module to convert the position information of the electronic control actuator under test in the test case into the first sub-electrical signal; using the second simulation module to convert the motor's state information in the test case into the second sub-electrical signal; or, using the motor signal simulation module, based on the second electrical signal, to simulate the motor's operating state and obtain the motor simulation result, including: using the first simulation module, based on the first sub-electrical signal, to simulate the position state and obtain the motor simulation result corresponding to the first sub-electrical signal; using the second simulation result, based on the second sub-electrical signal, to simulate the operating state and obtain the motor simulation result corresponding to the second sub-electrical signal.

[0010] Optionally, the target test scenario is simulated using a target simulation model, and a control signal is used to trigger the motor to drive the electronic control actuator under test in the simulated target test scenario to simulate the execution of the target function to be tested in the target test scenario, and the simulation results are obtained. This includes: converting the control signal into a physical signal and initializing the target simulation model to obtain an initialized target simulation model; using the initialized target simulation model, based on the physical signal, the dynamic behavior of the motor in the target test scenario is simulated to obtain simulation results, wherein the dynamic behavior is used to represent the behavior that the motor needs to perform when driving the electronic control actuator under test to simulate the execution of the target function.

[0011] Optionally, based on the simulation results, the test results for the target function are determined, including: based on the simulation results, determining the control results of the electronically controlled actuator under test, wherein the control results are used to indicate whether the electronically controlled actuator under test has simulated and completed the target function; in response to the control results indicating that the electronically controlled actuator under test has not simulated and completed the target function, or that the function simulated and completed by the electronically controlled actuator under test is different from the target function, determining the test result as having an accuracy level lower than an accuracy level threshold; in response to the control results indicating that the electronically controlled actuator under test has simulated and completed the target function, determining the test result as having an accuracy level greater than or equal to an accuracy level threshold.

[0012] According to another aspect of the embodiments of this application, a functional testing system for an electronically controlled actuator in a vehicle is also provided, comprising: a testing software system for generating test cases corresponding to the electronically controlled actuator under test in response to a test command triggered for the electronically controlled actuator under test; a hardware system for determining the control signal of the motor of the electronically controlled actuator under test; a simulation model system for determining a target simulation model from a set of simulation models included in the simulation model system based on the target test scenario indicated by the test cases, wherein different simulation models in the simulation model set correspond to different test scenarios for the electronically controlled actuator under test, and different test scenarios are used to provide an environment for testing different functions of the electronically controlled actuator under test; using the target simulation model to simulate the test scenario, and using the control signal to trigger the motor to drive the electronically controlled actuator under test in the simulated test scenario to simulate the execution of the target function to be tested in the target test scenario, thereby obtaining simulation results; and a domain controller for determining the test result of the target function based on the simulation result, wherein the test result is used to represent the accuracy of the electronically controlled actuator under test in simulating the execution of the target function in the test scenario.

[0013] Optionally, the simulation system also includes an interface model, which is used to convert test cases into electrical signals of the vehicle, wherein the electrical signals are used to represent the operating state of the vehicle during the testing of the target function.

[0014] Optionally, the electrical signals include a first electrical signal and a second electrical signal. The first electrical signal represents the operating status of the network in the vehicle, and the second electrical signal represents the operating status of the motor. The hardware system includes: a network simulation module for simulating the first electrical signal to obtain a network simulation result; and a motor signal simulation module for simulating the second electrical signal to obtain a motor simulation result. A domain controller generates a control signal based on the received network simulation result and motor simulation result, and sends the control signal to the hardware system. The hardware system sends the received control signal to the simulation system.

[0015] Optionally, the electronic control actuator under test includes the vehicle's rear wing, and the simulation model set corresponding to the rear wing includes at least one of the following: a rear wing deployment model, used to simulate the test scenario corresponding to the process of switching from a retracted state to a preset deployment state; a rear wing folding model, used to simulate the test scenario corresponding to the process of switching from a preset deployment state to a retracted state; a rear wing stall model, used to simulate the test scenario corresponding to the process of encountering an obstacle during state switching, causing the rear wing to be in an abnormally stationary state; a rear wing anti-pinch model, used to simulate the test scenario corresponding to the process of the rear wing encountering an obstacle during state switching and switching to a stopped state or a reversed state; and a rear wing ice-breaking model, used to simulate the test scenario corresponding to the process of the rear wing switching from a frozen state to a running state.

[0016] According to another aspect of the embodiments of this application, a functional testing device for an electronically controlled actuator in a vehicle is also provided, comprising: a generation unit, configured to generate test cases corresponding to the electronically controlled actuator under test in response to a test command triggered for the electronically controlled actuator under test in a vehicle; a first determining unit, configured to determine a target simulation model from a set of simulation models based on a target test scenario indicated by the test cases, and to determine the control signal of the motor of the electronically controlled actuator under test, wherein different simulation models in the set of simulation models correspond to different test scenarios for the electronically controlled actuator under test, and different test scenarios are used to provide an environment for testing different functions of the electronically controlled actuator under test; a simulation unit, configured to simulate the target test scenario using the target simulation model, and to trigger the motor to drive the electronically controlled actuator under test in the simulated target test scenario using the control signal, so as to simulate the execution of the target function to be tested in the target test scenario, and obtain simulation results; and a second determining unit, configured to determine the test result of the target function based on the simulation result, wherein the test result is used to represent the accuracy of the electronically controlled actuator under test in simulating the execution of the target function in the simulated target test scenario.

[0017] 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 program, wherein the program executes the methods in various embodiments of this application when it runs.

[0018] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0019] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0020] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the methods in various embodiments of this application.

[0021] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0022] According to another aspect of the embodiments of this application, a vehicle is also provided, including a memory and a processor, the memory storing an executable program and the processor for running the program, wherein the program executes the methods of various embodiments of this application when it runs.

[0023] In this embodiment, in response to a test command triggered by the electronically controlled actuator under test (ECU) of a vehicle, test cases corresponding to the ECU are generated. Based on the target test scenario indicated by the test cases, a target simulation model is determined from the simulation model set, as well as the control signal of the motor of the ECU under test. Using the target simulation model, the target test scenario is simulated, and using the control signal, the motor is triggered to drive the ECU under test in the simulated target test scenario to simulate the execution of the target function to be tested in the target test scenario, obtaining simulation results. Based on the simulation results, the test results of the target function are determined. In other words, this application constructs a simulation model set and an automated testing process, generates test cases according to the characteristics of the ECU under test, and can accurately simulate various complex test scenarios by selecting a simulation model that matches the target test scenario, overcoming the limitation of being unable to reproduce real driving conditions in a laboratory environment. On this basis, the motor control signal is triggered by automated means to drive the ECU to execute the target function in a virtual environment, the simulation results are collected, and the accuracy of the function is evaluated based on the simulation results. The above method not only avoids errors caused by subjective operation, but also significantly improves testing efficiency and coverage, thereby effectively improving the reliability of test results and the overall performance of electronic control actuators. This achieves the technical effect of improving the functional testing effect of electronic control actuators in vehicles and solves the technical problem of poor functional testing effect of electronic control actuators in vehicles. Attached Figure Description

[0024] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0025] Figure 1 This is a flowchart illustrating a functional testing method for an electronically controlled actuator in a vehicle, according to an embodiment of this application.

[0026] Figure 2 This is a schematic diagram of a hardware-in-the-loop test system for an electric rear wing of an automobile based on single-Hall simulation, according to an embodiment of this application.

[0027] Figure 3 This is a schematic diagram of a functional testing system for an electronically controlled actuator in a vehicle, according to an embodiment of this application.

[0028] Figure 4This is a structural block diagram of a functional testing device for an electronically controlled actuator in a vehicle, according to an embodiment of this application.

[0029] Figure 5 This is a structural block diagram of an autonomous vehicle according to an embodiment of this application. Detailed Implementation

[0030] 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.

[0031] 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.

[0032] According to an embodiment of this application, a functional testing method for an electronically controlled actuator in a vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0033] This application provides a method for functional testing of electronically controlled actuators in vehicles. This method can be used to perform functional testing on the electronically controlled actuators of vehicles in preset application scenarios. These preset application scenarios can include the following scenarios in the vehicle field: autonomous driving scenarios for commuting, artificial intelligence (AI) assisted driving scenarios for family cars, automatic parking assistance (APA) scenarios (such as memory parking for self-owned parking spaces in garages, intelligent parking for designated parking spaces in parking lots, etc.), and navigation-guided pilot (NGP) scenarios in urban or highway areas. Furthermore, the preset application scenarios may also include, but are not limited to: autonomous driving scenarios in the logistics and transportation field for intelligent driving trucks or unmanned trucks requiring augmented reality navigation functions, autonomous driving scenarios in the agricultural machinery field for autonomous agricultural vehicles requiring augmented reality navigation functions, autonomous driving scenarios for drones requiring augmented reality navigation functions, and autonomous driving scenarios for intelligent robots (such as cleaning robots, service robots, delivery robots, etc.) requiring augmented reality navigation functions.

[0034] When the aforementioned preset application scenario is a scenario in a field other than the vehicle field, those skilled in the art should understand that the vehicle in the above-mentioned functional testing method for the electronic control actuator of a vehicle can be replaced with other objects (such as agricultural machinery, drones, robots, etc.), and correspondingly, the functional testing of the electronic control actuator in the above-mentioned vehicle can be replaced with functional testing of the electronic control actuator in other objects. Based on this, this application embodiment takes the vehicle field as an example to illustrate the specific implementation method of the above-mentioned functional testing method for the electronic control actuator of a vehicle.

[0035] Figure 1 This is a flowchart illustrating a functional testing method for an electronically controlled actuator in a vehicle, according to an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0036] Step S102: In response to the test command triggered by the electronic control actuator under test for the vehicle, generate test cases corresponding to the electronic control actuator under test.

[0037] In the technical solution provided in step S102 of this application, the electronically controlled actuator under test can refer to a mechanical or electrical component in a vehicle controlled by an Electronic Control Unit (ECU) or a Regional Domain Controller Unit (RDCU). The function of the aforementioned electronically controlled actuator under test can be activated or adjusted via an electrical signal. In the embodiments of this application, the electronically controlled actuator under test can be a vehicle's rear wing or other similar component whose position or state is controlled by a motor. The aforementioned displacement can be the movement of the rear wing (or other electronically controlled actuator) from one position to another, for example, the movement of the rear wing from a retracted state to an deployed state.

[0038] Optionally, test instructions can be a series of parameters and conditions set by test engineers or automated test systems before testing. These test instructions can define specific test requirements and expected behaviors for the function of the electronic control actuator under test. For example, test instructions can be input by testers through a graphical user interface (GUI), including but not limited to the selection of test scenarios, the target position the actuator should reach, the setting of environmental conditions (e.g., temperature, humidity), and the specific steps of functional testing.

[0039] Optionally, test cases can be a preset set of input conditions and expected results, which can be used to verify whether the electronic control actuator under test can correctly and stably perform the corresponding functions under specified conditions. In the embodiments of this application, the above-mentioned test cases can be designed specifically for the electronic control actuator under test based on the content of test instructions. Each test case can include a detailed description of the test scenario, details of the input signals (e.g., voltage, frequency, etc. of the motor control signal), and expected results set according to the specifications and functional requirements of the electronic control actuator. By executing different test cases, the performance of the actuator under various test scenarios (operating conditions) can be comprehensively checked, including normal operating scenarios and possible abnormal situations.

[0040] In this embodiment, if a test command is detected for the electronic control actuator under test of the vehicle, test cases corresponding to the electronic control actuator under test can be generated.

[0041] Optionally, test instructions can be received from testers or automated test systems. These test instructions can be provided through a GUI (Graphical User Interface) and may include specific requirements and parameters for the test, such as the test scenario, type of actuator, environmental conditions, and expected functional performance.

[0042] Optionally, the received test instructions can be parsed to understand their inherent meaning and specific requirements, including determining the type of the electronic control actuator under test (e.g., rear wing, window motor, etc.) and the target scenario and conditions for the test. Based on the parsed test instructions, requirements analysis can be performed to clarify the purpose, scope, and key test points for the electronic control actuator under test, and obtain the necessary analysis results. For example, testing the deployment and retraction performance of the rear wing at high speeds, or detecting the anti-icing capability of the rear wing under low-temperature conditions.

[0043] Optionally, based on the above requirements analysis results, a basic test framework can be constructed, which may include selecting a suitable hardware platform (e.g., NI hardware bench system), software environment (e.g., Matrix Labs (MATLAB) / System-level Modeling and Simulation Toolkit (Simulink)), and determining the signal simulation strategy (e.g., Pulse Width Modulation (PWM) signal simulation).

[0044] Optionally, based on the above testing framework, specific test cases can be designed. Each test case can describe in detail the type and parameters of the input signal, as well as the expected output and behavior. During the design process, both normal and abnormal operating conditions can be considered to ensure the comprehensiveness and depth of the testing. The designed test cases are then transformed into executable test scripts or sequences using a testing software system (e.g., a self-developed multi-board testing tool). This process may involve writing test case parameters into tables or other data management tools for subsequent editing and management.

[0045] Optionally, based on the target test scenario indicated in the test cases, a suitable simulation model (e.g., a Hall effect model of the tail fin motor) can be selected and configured as necessary to match the characteristics of the electronic control actuator under test and the test scenario. Signal output boards in the hardware system, such as Controller Area Network (CAN) transceivers, analog signal input / output boards, and PWM signal output boards, can be configured to ensure accurate simulation of the signal environment of the electronic control actuator under test. Once all the above hardware, software, and model configurations are ready, and the test environment (including the virtual environment) has been correctly set up, test cases can be executed.

[0046] Step S104: Based on the target test scenario indicated by the test case, determine the target simulation model from the simulation model set, and determine the control signal of the motor of the electric control actuator under test.

[0047] In the technical solution provided in step S104 of this application, different simulation models in the simulation model set correspond to different test scenarios for the electronic control actuator under test. Different test scenarios can be used to provide environments for testing different functions of the electronic control actuator under test.

[0048] Optionally, the target test scenario can refer to a series of specific operating conditions or fault conditions preset when testing the electronic control actuator under test, aiming to comprehensively cover various operating environments and abnormal situations that the electronic control actuator under test may encounter. For example, for a vehicle's rear wing, test scenarios may include normal deployment, normal folding, continuous stalling, low-temperature ice breaking, and deployment and retraction at high speed, etc., each test scenario representing the working state of the rear wing under different operating conditions. The simulation model set can be a set of pre-built digital models, each simulation model in the simulation model set corresponding to different functional modules or physical components, used to simulate the real behavior of the electronic control actuator under test in a software environment. For example, for the functional test scenario of the rear wing, the simulation model set may include simulation models such as the rear wing deployment model, the rear wing folding model, and the rear wing stalling model, etc., without specific limitations. The above simulation models work together to reproduce the dynamic response and working characteristics of the rear wing under various test scenarios.

[0049] Optionally, the target simulation model can refer to the simulation model selected from the set of simulation models that is most relevant to the target test scenario. For example, when testing the tail fin deployment function, the target simulation model can be a tail fin deployment model, which can describe in detail the response process of the tail fin motor under the deployment command, including the motor's torque output, speed change, and pulse signals fed back by the Hall sensor.

[0050] Optionally, the control signal can refer to the instruction signal sent by the electronically controlled actuator under test to the actuator (e.g., a motor), which can be used to drive the actuator's actions. For example, if the electronically controlled actuator under test is a tail fin, the control signal can include the speed command, direction command, preset position command, etc. of the motor in the tail fin. Through the above control signals, the controller (e.g., an RDCU domain controller) can command the motor to realize actions such as unfolding and folding the tail fin.

[0051] Optionally, the function can refer to a specific task or operation that the electronic control actuator under test can perform. For example, if the electronic control actuator under test is a tail fin, the function of the tail fin may include, but is not limited to: automatic deployment and folding of the tail fin, stall protection, anti-pinch safety mechanism, ice-breaking operation in low-temperature environments, etc., without specific limitations. The above functions can be used to ensure that the tail fin can operate normally, safely, and efficiently under various working conditions.

[0052] In this embodiment, after generating test cases corresponding to the electronic control actuator under test in response to test instructions, the corresponding target simulation model can be determined from the simulation model set based on the target test scenario indicated by the test cases, and the control signal of the motor of the electronic control actuator under test can be determined.

[0053] Optionally, the objective of this embodiment is to select a specific simulation model from the set of simulation models that matches the test scenario based on given test cases, and to determine the control signal used to drive the motor of the electronically controlled actuator under test. This method ensures the accuracy and effectiveness of the testing of the electronically controlled actuator under test, enabling comprehensive performance verification for different functions and operating conditions.

[0054] Optionally, analyze the target test scenario indicated in the test cases to understand its details, including but not limited to the required operating state, input conditions, environmental factors, and expected output. Retrieve the simulation model corresponding to the target test scenario from the simulation model set. In the above steps, the descriptive information of the test scenario (e.g., operating mode, environmental parameters) can be used as keywords to find the simulation model that best meets the requirements of this test from the simulation model set as the target simulation model. Load the found target simulation model into the Hardware-in-the-Loop (HIL) test system, ensuring the compatibility of the target simulation model with the HIL test system and that the necessary input and output interfaces are correctly connected.

[0055] Optionally, the parameters of the target simulation model can be set according to the requirements of the test cases. These parameters may include, but are not limited to, motor parameters, environmental conditions, and load characteristics, to ensure that the model can accurately reflect the operating conditions under the test scenario.

[0056] Optionally, based on the target test scenario and the loaded target simulation model, the control signal parameters that the motor should receive can be determined. These control signal parameters may include the signal type (e.g., PWM, analog, digital), signal amplitude, frequency, and signal sequence (the signal order designed according to the test procedure). Using the hardware resources of the HIL test system (such as a signal generator and I / O boards), the corresponding control signals are generated according to the determined control signal parameters, and these control signals are sent to the motor of the electrical control actuator under test.

[0057] In this embodiment, starting with test cases, through model selection, parameter configuration, signal determination and transmission, to monitoring test results and performing iterative analysis, the ultimate goal is to verify the functionality and performance of the electronically controlled actuator under various preset scenarios. This method ensures the comprehensiveness, accuracy, and repeatability of the test, ensuring that the test can be conducted in a virtual environment simulating real-world working conditions, covering all functions and potential boundary conditions of the electronically controlled actuator, thereby significantly improving the development quality and verification efficiency of the actuator under test.

[0058] Step S106: Using the target simulation model, the target test scenario is simulated, and using control signals, the motor is triggered to drive the electrical control actuator under test in the simulated target test scenario to simulate the execution of the target function under test in the target test scenario and obtain the simulation results.

[0059] In the technical solution provided in step S106 of this application, the simulation results may include a series of output data and status information, which can be used to reflect the actual response and performance of the electronic control actuator under test in the target test scenario. Optionally, the simulation results may cover at least the following aspects: motor response characteristics, position feedback and control accuracy, working conditions and environmental factors, safety and stability, and error and anomaly detection.

[0060] Optionally, the aforementioned motor response characteristics may include the motor's start-up time, acceleration time, time required to reach the target position, changes in motor current and voltage, and motor temperature. These motor response characteristics can be used to evaluate the effectiveness of motor control and its performance under specific operating conditions. Regarding position feedback and control accuracy, during the execution of the target function by the electronically controlled actuator under test, feedback signals from the actuator's Hall sensors can be collected to calculate its actual position. The deviation between the position feedback data and the target position in the simulation results can be used to measure the actuator's control accuracy and response speed. Regarding working conditions and environmental factors, the target simulation model can simulate various working conditions and environmental factors, such as temperature, wind resistance, and load changes. Simulation results under specific environments can reflect the adaptability and robustness of the electronically controlled actuator, as well as its functional performance under abnormal conditions (such as stalled rotor or low temperature). Regarding stability and safety, the simulation results may include the stability performance of the electronically controlled actuator in the target test scenario and the triggering of safety mechanisms. For example, when the tail fin encounters stall protection, it's necessary to determine whether the tail fin can respond promptly and take appropriate protective measures to avoid motor damage or ensure passenger safety. Regarding error and anomaly detection, if the electronic control actuator under test exhibits unexpected behavior during the simulation, such as abnormal signal output or motor failure to start, this behavior can also be recorded in the simulation results for subsequent error analysis and system optimization.

[0061] In this embodiment, after determining the target simulation model from the simulation model set and the control signal of the motor of the electronic control actuator under test, the target simulation model can be used to simulate the target test scenario. Then, using the control signal, the motor is triggered to drive the electronic control actuator under test in the simulated target test scenario to simulate the execution of the target function to be tested in the target test scenario and obtain the simulation result.

[0062] Optionally, ensure the target simulation model has been loaded into the HIL test system. Set the initial conditions for the simulation model, which may include, but are not limited to, environmental parameters (such as temperature and humidity), the state of the electronically controlled actuator (such as initial position and power level), and any prior system configurations. Input the determined control signals into the simulation model. These control signals will trigger the motor drive module in the target simulation model to simulate the actual response of the electronically controlled actuator in the target test scenario. Execute the target simulation model, causing it to run under the set control signals and begin simulating the target test scenario. At this point, the target simulation model can dynamically simulate the motor's starting, acceleration, deceleration, and stopping operations, as well as the corresponding behavior of the entire electronically controlled actuator, based on the input control signals and environmental conditions.

[0063] Optionally, during the simulation process, the output and state changes of the target simulation model can be continuously monitored, and data related to the simulation can be recorded, including motor torque output, speed changes, position signals, current and voltage values, and any abnormal behavior or error states. Depending on the test case requirements, some abnormal operating conditions (such as stall, power failure, high temperature, etc.) can be artificially triggered to observe whether the electronic control actuator can respond correctly under these conditions and maintain the stability and safety of the system. When the target test scenario is completed or the preset termination conditions are reached, the simulation is stopped, and the final simulation results are extracted and saved from the simulation system.

[0064] In this embodiment, by loading a target simulation model, inputting control signals, and monitoring the simulation results, real-world operating conditions can be reproduced in a virtual environment, thereby enabling safe, efficient, and comprehensive testing of the electronically controlled actuator. This process not only verifies the implementation of basic functions but also allows for the evaluation of the system's stability and safety under extreme or abnormal conditions.

[0065] Step S108: Based on the simulation results, determine the test results of the target function.

[0066] In the technical solution provided in step S108 of this application, the test results can be used to represent the accuracy of the electrical control actuator under test in simulating the target function under the simulated target test scenario.

[0067] Optionally, the evaluation of test results can be based on at least one of the following key points: functional implementation verification, performance index evaluation, abnormal operating condition response capability, safety mechanism verification, and comprehensive evaluation and feedback. Among these, the aforementioned functional implementation verification can be used to check whether the electronically controlled actuator has fully achieved the target function as expected. For example, if the target function of the tail fin is its deployment and retraction, the test results can be used to indicate whether the tail fin can accurately respond to control signals and successfully reach the designated position. The aforementioned performance index evaluation can be used to analyze the performance of the electronically controlled actuator under test during the execution of the target function, and may include, but is not limited to, indicators such as control accuracy, response time, power consumption, and stability. For example, it can assess whether the tail fin deployment speed is completed within a specified time, and whether the error range during the control process is within an acceptable threshold. The aforementioned abnormal operating condition response capability can be used to evaluate the behavior and response of the electronically controlled actuator under simulated abnormal operating conditions. For example, when the tail fin stalls, the test results can indicate whether the motor can be stopped and restarted immediately, and whether the tail fin can maintain stability under extreme temperature conditions.

[0068] Optionally, the aforementioned safety mechanism verification can be used to confirm whether the safety mechanisms of the electronically controlled actuator are effectively triggered and operational, especially in simulated safety-related test scenarios. For example, if the tail fin is found to pose a risk to the system or human health, the test result can indicate whether automatic safety measures can be taken. The aforementioned comprehensive evaluation and feedback can be based on the assessments of the various aspects mentioned above to comprehensively evaluate the test results of the electronically controlled actuator under test and determine whether design modifications or algorithm optimizations are necessary. Simultaneously, the test results can also include detailed feedback information, indicating which aspects performed well and which aspects need improvement.

[0069] In this embodiment, after generating the simulation results, the test results of the target function can be determined based on the simulation results.

[0070] Optionally, collect relevant data and log files generated from HIL simulation tests, which may include motor response data, Hall sensor signal feedback, state change records, etc. Organize the above data and arrange them in chronological order for subsequent analysis. Compare the signal data in the simulation results (especially motor drive signals and Hall feedback signals) with the expected signal performance under the preset test scenario. Analyze the signal differences and check the accuracy of motor control and feedback loops. Based on the simulation results, evaluate the accuracy of the EMU under test in performing the target function under the target test scenario. Check whether the EMU can correctly deploy or retract the tail fin according to the predetermined control logic to achieve the desired position and attitude.

[0071] Optionally, compare the performance data in the simulation results (e.g., response speed, control accuracy, power consumption, stability, etc.) with the test specifications or standard requirements. Verify whether the various performance indicators of the electronic control actuator are within the expected range. Check for any abnormal behaviors or fault states in the simulation results, such as stalled rotor, overheating, signal interruption, etc. Evaluate whether the electronic control actuator's response strategies and recovery capabilities under abnormal conditions meet the design requirements.

[0072] Optionally, analyze whether the safety mechanisms of the electronically controlled actuator are correctly triggered and operate effectively under simulated hazardous or emergency conditions. Confirm whether the electronically controlled actuator under test can respond in a timely manner and take measures to prevent potential harm. Based on the above analysis, the test result is judged as pass, warning, or failure. For each test scenario, mark its result status and note any reasons for deviations from expectations.

[0073] Optionally, a detailed test result report should be prepared, including but not limited to a description of each test, the control signals used, simulation results, judgment results, and improvement suggestions. The test report should clearly demonstrate the accuracy and performance of the electronically controlled actuator in the target test scenario. Relevant engineers and technical experts should review the test results to confirm the accuracy of the assessment. It should be confirmed that all test results have been fully recorded and analyzed, with no important information omitted.

[0074] Optionally, based on the test results, develop a next steps plan, including hardware or software adjustments to the electronic control actuators if necessary. Plan scenarios and schedules for repeated or extended testing to ensure that all issues are properly addressed.

[0075] In steps S102 to S108 of this application, in response to a test command triggered by the electronic control actuator under test (ECU) of the vehicle, test cases corresponding to the ECU under test are generated; based on the target test scenario indicated by the test cases, a target simulation model is determined from the simulation model set, and the control signal of the motor of the ECU under test is determined; using the target simulation model, the target test scenario is simulated, and using the control signal, the motor is triggered to drive the ECU under test in the simulated target test scenario to simulate the execution of the target function to be tested in the target test scenario, and the simulation result is obtained; based on the simulation result, the test result of the target function is determined. In other words, this application constructs a simulation model set and an automated testing process, generates test cases according to the characteristics of the ECU under test; by selecting a simulation model that matches the target test scenario, it can accurately simulate various complex test scenarios, overcoming the limitation of difficulty in reproducing real driving conditions in a laboratory environment. On this basis, automated means are used to trigger the motor control signal to drive the ECU to execute the target function in a virtual environment, collect simulation results, and evaluate the accuracy of the function based on the simulation results. The above method not only avoids errors caused by subjective operation, but also significantly improves testing efficiency and coverage, thereby effectively improving the reliability of test results and the overall performance of electronic control actuators. This achieves the technical effect of improving the functional testing effect of electronic control actuators in vehicles and solves the technical problem of poor functional testing effect of electronic control actuators in vehicles.

[0076] The following section further explains how to determine the control signal of the motor of the electronically controlled actuator under test in this embodiment.

[0077] As an optional implementation, step S104, determining the control signal of the motor of the electronic control actuator under test, includes: converting the test case into an electrical signal of the vehicle, wherein the electrical signal is used to represent the operating state of the vehicle during the test of the target function; and determining the control signal based on the electrical signal.

[0078] In this embodiment, electrical signals can refer to various physical signals transmitted in the vehicle's electronic system. These electrical signals carry information about the vehicle's operating status, driver intentions, environmental conditions, etc. After being parsed by the ECU or RDCU, they drive the various actuators of the vehicle to respond and act.

[0079] Electrical signals can include CAN signals, PWM signals, analog signals, and digital signals. The CAN signal, based on the CAN communication protocol, is used to exchange data between different ECUs in a vehicle. In this embodiment, the CAN signal can transmit motor control commands, position feedback, fault codes, or other information related to rear wing control. The PWM signal can be used for motor speed control. By changing the duty cycle (the ratio of the high-level duration to the total cycle), the motor speed and torque can be adjusted. Analog signals can represent continuously changing physical quantities, such as voltage, current, and temperature. In testing scenarios, analog signals can simulate the output of Hall sensors, reflecting the position information of the electronic control actuator under test. Digital signals can represent discrete state signals, such as switch signals and indicator light signals. During testing, digital signals can simulate the locked / unlocked state and fault alarms of the electronic control actuator under test.

[0080] Optionally, electrical signals can serve as carriers of control commands. These signals can be sent from the HIL simulation platform to the electronically controlled actuator under test (ECU) to guide the motor's operation and simulate the execution of the target function. Electrical signals can also reflect the vehicle's current operating status and environmental conditions. They can include feedback information from the vehicle's actuators, such as position sensor readings, motor current, and temperature. This information can be used to evaluate the performance and functionality of the control loop.

[0081] Optionally, in the process of determining the control signal of the motor of the electronically controlled actuator under test, the test cases can be converted into the vehicle's electrical signals, thereby determining the control signal based on the electrical signals.

[0082] Optionally, analyze and understand the predetermined test cases, clarify the details and requirements of the target function, and the vehicle operating states that need to be simulated in the test (such as tail wing deployment, retraction, speed, position, etc.). Determine the specific control commands and simulation conditions that need to be converted into electrical signals in the test cases.

[0083] Optionally, depending on the requirements of the test cases, the instructions describing the vehicle's operating status and target functions are converted into corresponding electrical signal formats, such as CAN messages, PWM signals, and analog signals. Using the rule engine of the test software, the text descriptions or parameter configurations in the test cases are converted into electrical signal instructions recognizable by the ECU / RDCU. It is ensured that the converted electrical signal format is compatible with the vehicle communication protocol (such as CAN ID, signal length, transmission rate, etc.) and conforms to the interface specifications of the electronic control actuator under test. If the test cases require simulating Hall position sensor signals, it must be ensured that the frequency and duty cycle of the generated signal (PWM signal) conform to the interaction standards between the sensor and the RDCU.

[0084] Optionally, signals directly related to motor control, such as PWM drive signals and analog control signals, can be identified and extracted from the converted electrical signals. Based on the control commands in the electrical signals (such as tail fin deployment angle and speed requirements), the control signal parameters required for motor drive, such as PWM duty cycle, drive current magnitude, and voltage level, are calculated or determined. Before sending the control signals, necessary preprocessing, such as signal amplification, filtering, and isolation, is performed according to the characteristics and limitations of the HIL hardware system to ensure that the signals can be accurately reproduced and transmitted in the laboratory environment. The synchronization and timing of the signals are adjusted to ensure accurate interaction with the simulation model and the real ECU.

[0085] Optionally, HIL hardware systems (such as CAN transceivers and PWM signal output boards from NI test benches) can be used to send control signals to the actuator under test. Electrical signals fed back from the actuator, such as feedback signals from position sensors and motor status reports, are monitored and received for subsequent functional verification and data analysis.

[0086] The following section further explains how the control signal is determined based on the electrical signal in this embodiment.

[0087] As an optional implementation, the electrical signals include a first electrical signal and a second electrical signal. The first electrical signal represents the operating state of the network in the vehicle, and the second electrical signal represents the operating state of the motor. Based on the electrical signals, the control signal is determined, including: using a network simulation module to simulate the operating state of the network based on the first electrical signal to obtain a network simulation result; and using a motor signal simulation module to simulate the operating state of the motor based on the second electrical signal to obtain a motor simulation result; and using the domain controller corresponding to the electronic control actuator under test to determine the control signal based on the network simulation result and the motor simulation result.

[0088] In this embodiment, the first electrical signal can refer to the data signal transmitted in the vehicle's CAN network, used to indicate the operating status of the network in the vehicle, including but not limited to control commands, status reports, fault information, etc. In HIL testing, the first electrical signal can be crucial for simulating the entire vehicle network environment, helping test engineers reproduce complex network interaction scenarios under laboratory conditions, thus improving the realism and effectiveness of the test. The first electrical signal may include CAN network information.

[0089] Optionally, the second electrical signal may include analog signals and PWM signals. The second electrical signal can be used to represent the motor's operating state, such as its speed, position, and torque. The analog signal can be used to represent continuously changing physical quantities, such as voltage or current, and can be used to simulate the output of sensors, such as Hall effect position sensors and temperature sensors. The PWM signal can be used for motor speed control, adjusting the signal's duty cycle to control the motor's power and speed. The second electrical signal can be used to simulate the motor's actual operating conditions in HIL testing, verifying the correctness and performance of the motor drive algorithm, and ensuring the motor's stability and response speed under various operating conditions.

[0090] Optionally, the network simulation module can be a CAN transceiver. The network simulation module can be the hardware used in the HIL test platform to simulate a vehicle CAN network. This network simulation module can send and receive CAN signals, simulate data exchange in the vehicle network, including simulating ECU responses and receiving control commands from the RDCU domain controller, creating a near-realistic network interaction simulation.

[0091] Optionally, the motor signal simulation module may include digital analog signal input / output (I / O) boards and a dedicated PWM signal output board. The motor signal simulation module can be used to generate and receive electrical signals simulating the operating status of the motor. Specifically, the aforementioned I / O boards can generate and acquire analog signals, such as simulating motor current or voltage, to simulate the motor's power supply and load conditions during testing. The dedicated PWM signal output (PWMO) board generates high-precision PWM signals to simulate motor control signals and verify the motor drive logic.

[0092] Optionally, the domain controller can be an RDCU, which is an intelligent control unit in the vehicle used to centrally manage specific functional areas (such as body control, powertrain, etc.). In HIL testing, the RDCU domain controller is used to receive CAN data from the network simulation module and motor operating status information from the motor signal simulation module. Based on the above motor operating status information, it generates and sends motor control signals to simulate the control logic of the electronic control actuator and verify the accuracy and efficiency of the control logic implementation.

[0093] Optionally, motor simulation results can be simulated data generated by the motor signal simulation module during motor operation, including simulated motor speed, position, torque, and other information. Motor simulation results provide a way to evaluate the performance of the motor control algorithm under different operating conditions and serve as a basis for determining the effectiveness of control signals. Network simulation results can be data generated by the network simulation module when simulating a vehicle network environment, including signal transmission, reception, delay, and error states within the network. Network simulation results can be used to verify the interaction logic between the RDCU and other ECUs in the vehicle network, ensuring that the RDCU can still correctly process information and generate appropriate control signals under network anomalies or complex interaction conditions.

[0094] Optionally, in the process of determining the control signal based on the electrical signal, a network simulation module can be used to simulate the network's operating state based on the first electrical signal to obtain the network simulation result. Alternatively, a motor signal simulation module can be used to simulate the motor's operating state based on the second electrical signal to obtain the motor simulation result. The domain controller can then determine the control signal based on the aforementioned network simulation result and motor simulation result.

[0095] Optionally, gain a thorough understanding of the target function of each test case, and the requirements of these target functions on the vehicle network and motor operating status. Extract the specifications of the first and second electrical signals from the test cases, including signal type, parameter values, triggering conditions, etc.

[0096] Optionally, during the network simulation module configuration process, CAN transceiver parameters can be set, such as CAN identifier, baud rate, and data frame structure. Based on test cases, specific CAN messages are sent through the network simulation module to simulate data exchange and operational status on the network. Signal transmission during the network simulation process is recorded, including signal delay, collisions, and signal loss, generating network simulation results.

[0097] Optionally, during the configuration of the motor signal simulation module, the output parameters of the digital analog signal input / output board and the dedicated PWM signal output board can be set. Based on the test requirements, the motor signal simulation module outputs analog signals or PWM signals to simulate the motor's operating states such as current, voltage, speed, and position. The feedback signals of the motor under simulation conditions are monitored and recorded, including readings from the position sensor and data from the temperature sensor, to form the motor simulation results.

[0098] Optionally, the RDCU domain controller under test is started, and the software modules and control logic corresponding to the test cases are loaded. The obtained network simulation results are input into the RDCU domain controller to simulate a real network environment. Similarly, the motor simulation results are also input into the RDCU domain controller to ensure that the controller can perceive the simulated motor operating status. Based on the network simulation results and the motor simulation results, the RDCU domain controller executes a preset control algorithm and logic to calculate the motor control signal.

[0099] Optionally, after the control signal is calculated, preliminary verification can be performed in a simulation environment. If the verification result is not ideal, the process can be returned to regenerate the simulation signal and adjust the parameters of the simulation signal to iteratively optimize the calculation process of the control signal.

[0100] Optionally, once a valid control signal is identified, the RDCU domain controller sends a signal to the actuator under test via its output port. The response of the actuator's motor to the control signal is observed, including motor start-up, stopping, speed changes, and position adjustments. Feedback signals during the motor response process, such as real-time readings from the position sensor, are acquired using a motor signal simulation module. The expected behavior of the target function is compared with the actual response of the motor to evaluate the accuracy of the control signal and the effectiveness of the function implementation.

[0101] In this embodiment, the aforementioned electrical signal processing and control signal determination process covers the entire process from test case analysis to control signal calculation, signal execution, feedback monitoring, and result analysis. The network simulation module and motor signal simulation module generate first and second electrical signals, providing the RDCU domain controller with a near-real-world testing environment. This allows the controller to calculate precise control signals based on simulation results, thereby verifying the functionality and performance of the electrical control actuator under test. The iterative execution of this method ensures comprehensive and in-depth testing, facilitating rapid problem identification and resolution, and improving the R&D efficiency and quality of electrical control actuators.

[0102] The following describes in detail how the test cases are converted into vehicle electrical signals, and how the motor signal simulation module is used to simulate the motor's operating state based on the second electrical signal to obtain the motor simulation results.

[0103] As an optional implementation, the second electrical signal includes a first sub-electrical signal and a second sub-electrical signal. The first sub-electrical signal represents the position state of the motor, and the second sub-electrical signal represents the operating state of the motor. The motor signal simulation module includes a first simulation module and a second simulation module. The first simulation module corresponds to the first sub-electrical signal, and the second simulation module corresponds to the second sub-electrical signal. The test case is converted into the vehicle's electrical signal, including: using the first simulation module to convert the position information of the electronically controlled actuator under test in the test case into the first sub-electrical signal; using the second simulation module to convert the motor's state information in the test case into the second sub-electrical signal; or, using the motor signal simulation module, based on the second electrical signal, to simulate the motor's operating state and obtain the motor simulation result, including: using the first simulation module, based on the first sub-electrical signal, to simulate the position state and obtain the motor simulation result corresponding to the first sub-electrical signal; using the second simulation result, based on the second sub-electrical signal, to simulate the operating state and obtain the motor simulation result corresponding to the second sub-electrical signal.

[0104] In this embodiment, the first sub-electrical signal can be a Hall sensor signal from the external tail fin or an analog signal. The Hall sensor signal can be a digital signal generated by a Hall sensor mounted on the external tail fin, used to detect the precise position of the tail fin. The Hall sensor uses the principle of magnetic induction to convert changes in the magnetic field into an electrical signal, thus providing feedback on the tail fin's position. In HIL testing, the first sub-electrical signal can be simulated to test the RDCU's ability to identify and control the tail fin's position. The analog signal can be a continuously changing electrical signal, such as voltage or current, used to represent continuous changes in physical quantities, such as motor temperature or tail fin load. The analog signal is used in testing to simulate environmental conditions of the motor or tail fin, such as temperature changes and wind resistance, to evaluate the performance of the control algorithm under different conditions.

[0105] Optionally, the second sub-electrical signal can be a PWM signal generated by a Hall sensor inside the tail fin motor. The PWM signal can be used for precise control of the motor speed and position. Inside the motor, the Hall sensor detects the position of the motor rotor, and the duty cycle of the generated PWM signal reflects the motor's speed and position. In HIL testing, the second sub-electrical signal is used to simulate the dynamic state inside the motor, verifying the accuracy and robustness of the motor control algorithm.

[0106] Optionally, the first simulation module can be an I / O board. The aforementioned first simulation module can be a hardware device capable of outputting and receiving digital or analog signals to simulate the electrical behavior of sensors in a real vehicle environment. In this embodiment, it may include simulating signals from the external Hall sensor of the tail wing and processing analog signals. The aforementioned first simulation module can be used to create a first sub-electrical signal, simulating the position state of the tail wing, and the continuous changing state of the motor or environment, such as temperature and wind resistance, providing realistic environmental signals for testing.

[0107] Optionally, the second simulation module can be a PWMO board. This second simulation module can be a dedicated hardware device used to generate high-precision PWM signals to simulate the electrical output of the Hall sensors inside the motor. This second simulation module is used to accurately simulate the dynamic response and position feedback of the motor during HIL testing. By adjusting the duty cycle and frequency of the output PWM signal, different motor speeds and position states can be simulated, verifying the impact of the motor control signal on the actual operation of the motor and ensuring the accuracy and reliability of the control algorithm.

[0108] Optionally, the position information can refer to information in the test case that reflects the precise position of the object in space. In the embodiments of this application, the position information can refer to the deployed or folded position of the tail wing on the vehicle. The aforementioned position information can be used to define the target position that the motor needs to reach, and can be used to test whether the tail wing control function is accurate and whether the response is timely.

[0109] Optionally, the state information can be various state parameters covering the motor's operation in the test cases, such as the motor's speed, temperature, current, and voltage, as well as environmental conditions such as the tail fin's load and wind resistance. In HIL testing, the state information can be used to simulate the motor's operating state under different conditions, testing the adaptability and stability of the control algorithm under various conditions. By simulating various state information, the performance and functional implementation of the tail fin control system can be comprehensively evaluated.

[0110] Optionally, in the process of converting test cases into electrical signals, a first simulation module can be used to convert the position information of the electrical control actuator under test in the test case into a first sub-electrical signal. Alternatively, a second simulation module can be used to convert the motor state information in the test case into a second sub-electrical signal. In the process of using a motor signal simulation module to simulate the motor's operating state based on the second electrical signal and obtaining the motor simulation result, the first simulation module can be used to simulate the position state based on the first sub-electrical signal to obtain the motor simulation result corresponding to the first sub-electrical signal. Alternatively, the second simulation module can be used to simulate the operating state based on the second sub-electrical signal to obtain the motor simulation result corresponding to the second sub-electrical signal.

[0111] Optionally, during test case preparation, the test cases can be analyzed in detail to clarify the position information of the electronically controlled actuator under test and the state information of the motor, including but not limited to parameters such as target position, speed, and temperature. During the generation of the first sub-electrical signal, a first simulation module (e.g., a digital-analog signal input / output board / IO board) can be configured to simulate the output of the external Hall sensor or position sensor of the tail fin. The position information in the test cases (e.g., the specific angle or displacement that the tail fin should achieve) is converted into the first sub-electrical signal. This signal can be a pulse signal from the Hall sensor or an analog signal, used to represent the position state that the motor should achieve. Ensure that the format and characteristics of the first sub-electrical signal match those of the actual sensor output signal to provide a high-fidelity simulation environment.

[0112] Optionally, during the generation of the second sub-electrical signal, a second simulation module can be configured to prepare for simulating the PWM signal output of the Hall sensor inside the tail fin motor. The motor state information (such as motor speed, current, voltage, etc.) in the test case is converted into the second sub-electrical signal, which is a PWM signal used to represent the motor's operating state. The duty cycle and frequency of the PWM signal are adjusted to accurately reflect the motor's state under different operating conditions, ensuring the accuracy of the simulation.

[0113] Optionally, during the motor operation state simulation, the first simulation module simulates the motor's position state based on a first sub-electrical signal. For example, it generates a signal conforming to specific position information by simulating the output of a Hall sensor or position sensor, thus forming the position state portion of the motor simulation result. The output of the simulated position signal generated by the first simulation module is recorded and monitored to ensure it meets the set position information requirements. The second simulation module simulates the motor's operating state based on a second sub-electrical signal. For example, it outputs a PWM signal with specific parameters to reflect the motor's speed, torque, energy consumption, and other operating conditions, thus forming the operating state portion of the motor simulation result. The PWM signal generated by the second simulation module is monitored to ensure its duty cycle and frequency accurately reflect the motor's state information, forming a complete motor simulation result.

[0114] Optionally, during the control signal adjustment and testing process, the network simulation results (first electrical signal) and motor simulation results (second electrical signal) are imported into the RDCU domain controller to simulate the vehicle network environment and motor operating environment. Based on the simulation results, the RDCU domain controller executes the control algorithm to determine the control signals for the motor, including but not limited to adjusting PWM signal parameters to control motor speed and position. The determined control signals are sent to the electronic control actuator under test, and the actual motor response is observed and recorded, including changes in motor speed and position adjustments. The actual motor response is compared with the expected results of the test cases to evaluate the effectiveness of the control signals and the performance of the control algorithm.

[0115] Optionally, during the result analysis and iteration process, the motor simulation results and actual response data are analyzed to evaluate the accuracy of the simulation of position and operating states, as well as the efficiency of the control signals. If the simulation results or motor response do not meet expectations, the above steps are returned, the parameters of the simulation module or the information in the test cases are adjusted, and the electrical signal conversion and motor operating state simulation are repeated. This iteration continues until the motor simulation results and actual response meet the test standards, ensuring the accuracy and reliability of the control algorithm of the electronically controlled actuator.

[0116] In this embodiment, the process of converting test cases into vehicle electrical signals involves precise simulation of position and state information to generate a first sub-electrical signal and a second sub-electrical signal. The first and second simulation modules respectively simulate the motor's position and operating states, forming a comprehensive motor simulation result. Based on the aforementioned motor and network simulation results, the RDCU domain controller adjusts the control signals to verify the control performance and functional implementation of the electronically controlled actuator. This process includes a closed loop of test case analysis, signal simulation, state detection, control signal adjustment, and result analysis, ensuring the comprehensiveness and efficiency of HIL testing.

[0117] The following explanation further details how, in this embodiment, a target simulation model is used to simulate a target test scenario, and control signals are used to trigger a motor to drive the electronically controlled actuator under test in the simulated target test scenario to simulate the execution of the target function under test in the target test scenario and obtain the simulation results.

[0118] As an optional implementation, step S106 involves using a target simulation model to simulate the target test scenario, and using control signals to trigger the motor to drive the electronic control actuator under test in the simulated target test scenario to simulate the execution of the target function to be tested in the target test scenario, and obtaining simulation results. This includes: converting the control signals into physical signals, and initializing the target simulation model to obtain an initialized target simulation model; using the initialized target simulation model, based on the physical signals, to simulate the dynamic behavior of the motor in the target test scenario, and obtaining simulation results. The dynamic behavior is used to represent the behavior that the motor needs to perform when driving the electronic control actuator under test to simulate the execution of the target function.

[0119] In this embodiment, physical signals can refer to signals that can directly act on physical objects (such as motors), typically manifested as changes in physical quantities such as voltage, current, and electromagnetic fields. In the HIL testing environment, physical signals are converted from digital or analog signals and can be received and responded to by the motor in the electronically controlled actuator under test. In this application embodiment, physical signals can be in the form of converted control signals, which can be used to actually drive the motor and simulate the movement of the electronically controlled actuator under test in the target test scenario. The aforementioned physical signals serve as a bridge connecting the simulation model and the real-world motor, enabling the computer-generated control signals to be understood and executed by the motor, thereby verifying the performance of the controller and the correctness of the algorithm.

[0120] Optionally, dynamic behavior can refer to a series of state changes and reactions of the motor over time after receiving an input (such as a control signal). In the context of this embodiment, dynamic behavior specifically refers to a series of actions and state evolutions performed by the motor after receiving a physical signal, such as acceleration, deceleration, steering, or stopping. Simulating dynamic behavior is a crucial step in evaluating the effectiveness of motor control strategies and their ability to achieve target functions. By simulating target test scenarios in HIL testing, including environmental conditions and load conditions, the simulation of dynamic behavior can verify whether the motor's response to control signals under different operating conditions meets expectations, helping to identify potential control logic errors or performance bottlenecks, thereby optimizing algorithm design and improving product reliability.

[0121] Optionally, during the generation of simulation results, the control signals can be converted into physical signals, and the target simulation model can be initialized to obtain an initialized target simulation model. Using the initialized target simulation model, based on the physical signals, the dynamic behavior of the motor under the target test scenario can be simulated to obtain simulation results.

[0122] Optionally, during the control signal conversion process, the control signal output from the RDCU domain controller can meet specific electrical characteristics, such as voltage, current, frequency, and duty cycle, to ensure accurate motor drive. Using the motor signal simulation module (including a first simulation module and a second simulation module), the required signal conversion parameters are configured to prepare for converting the control signal into a physical signal.

[0123] Optionally, during the initialization of the target simulation model, a test scenario model related to the target function, such as a tail fin deployment / retraction condition model, can be loaded into MATLAB / Simulink or a similar simulation environment. Based on the target test scenario, reasonable initial parameters are set for the model, such as the initial position, speed, and temperature of the motor, as well as the state information of the vehicle network. This ensures that the initial state of the model is correct and meets the test requirements, preparing it for subsequent dynamic behavior simulations.

[0124] Optionally, during the conversion of control signals into physical signals, the control signals output by the RDCU domain controller (such as PWM, CAN messages, etc.) can be converted into physical signals (such as current, voltage) that the motor can respond to. During the conversion process, the accuracy and reliability of the physical signals are ensured, for example through waveform analysis and signal strength detection.

[0125] Optionally, during the dynamic behavior simulation and result acquisition process, the converted physical signals can be input into the initialized target simulation model as input for motor control. Based on the input physical signals, the target simulation model simulates the dynamic behavior of the motor, such as acceleration / deceleration, position changes, and temperature changes, reflecting the operating state of the electrical control actuator under test in the target test scenario. Various data generated during the model simulation process are collected and recorded, including the motor's trajectory, speed curve, position data, and temperature changes, as components of the simulation results.

[0126] Optionally, during the simulation result analysis, the collected simulation results can be used to analyze whether the dynamic response of the motor under the target test scenario meets expectations, and to evaluate the accuracy and stability of the control algorithm. The simulation results are compared with the target functions in the test cases to determine whether the functional requirements are met and to identify potential problems or optimization points. The simulation test process, results, and analysis are then compiled into a test report to provide a basis for subsequent software iterations and hardware optimizations.

[0127] In this embodiment, the method described above illustrates how to convert the control signals of the RDCU domain controller into physical signals and simulate the dynamic behavior of the motor in the target simulation model to verify the functional implementation of the electronic control actuator under test in a specific test scenario. By initializing the target simulation model, accurately converting control signals, simulating the dynamic response of the motor, and deeply analyzing the simulation results, the HIL test platform can provide a closed-loop test environment to comprehensively evaluate the performance of the control system and ensure its reliability and effectiveness in practical applications. This process embodies the core value of HIL testing, namely, reconstructing the actual vehicle environment under laboratory conditions to achieve in-depth testing and optimization of the electronic control actuator.

[0128] The following section further explains how to determine the test results of a function based on simulation results in this embodiment.

[0129] As an optional implementation, step S108, based on the simulation results, determines the test result of the target function, including: based on the simulation results, determining the control result of the electronically controlled actuator under test, wherein the control result is used to indicate whether the electronically controlled actuator under test simulates and completes the target function; in response to the control result indicating that the electronically controlled actuator under test has not simulated and completed the target function, or that the function simulated and completed by the electronically controlled actuator under test is different from the target function, determining the test result as having an accuracy level lower than an accuracy level threshold; in response to the control result indicating that the electronically controlled actuator under test has simulated and completed the target function, determining the test result as having an accuracy level greater than or equal to an accuracy level threshold.

[0130] In this embodiment, the control result can be an indicator evaluated based on simulation results, reflecting the ability and effectiveness of the electronically controlled actuator under test (ECU) in performing a specific function in the target test scenario. The control result can indicate whether the ECU successfully performed the target function. For example, for a tail fin, the control result can include whether the tail fin completed the deployment or retraction action at a predetermined angle and speed, whether the motor responded correctly to the control signal, and whether there were any unexpected pauses, abnormal vibrations, or other unstable behaviors throughout the process. The control result can also reflect the control accuracy and response time when performing the function. For example, when the tail fin deploys, whether the motor's response speed meets the design requirements, whether the final position of the tail fin is accurate, and whether the deviation from the theoretical value is within an acceptable threshold. The impact of the control strategy on motor energy consumption and the overall efficiency of the system when performing the target function are analyzed. This includes important parameters such as motor power consumption, thermal management, and energy utilization rate under different operating conditions, which are indicators for evaluating long-term performance and economy. The control result can also be used to verify the robustness of the ECU in the face of simulated fault injection, environmental changes, etc. For example, when the simulated Hall sensor signal is abnormal, can the motor safely stop or switch to a backup control strategy to avoid damage or ensure user safety? By repeatedly testing the same test case, the repeatability and consistency of the control results are checked, ensuring that similar results are obtained each time. This can be used to reflect the stability and predictability of the control algorithm.

[0131] Optionally, control results serve as the fundamental basis for evaluating whether the electrical control actuator under test meets functional, performance, and safety requirements. Through control results, the effectiveness of HIL testing can be quantified, determining whether the test passes or requires further optimization. Detailed analysis of control results can identify deficiencies in the control algorithm, such as excessively long response times, substandard control accuracy, or unreasonable energy consumption, thereby guiding software engineers to make targeted improvements. Control results also reflect the hardware's response to control signals, helping to confirm whether the hardware meets software requirements and serving as an important reference for hardware selection and system integration. Comprehensive inspection and analysis of control results help identify potential product defects early, reducing later product recalls and repair costs, and improving overall product quality and market competitiveness.

[0132] Optionally, in the process of determining the test results of the function based on the simulation results, the control results of the electronic control actuator under test can be determined based on the simulation results. The test results can be determined based on the control results.

[0133] Optionally, during the analysis of simulation results, control performance data related to the electronically controlled actuator under test can be extracted from the simulation results obtained from the HIL test platform. This includes the motor's position, speed, torque, energy consumption curves, and the specific operational states of the electronically controlled actuator, such as the tail fin. The above data is then compared with the expected results of the test cases to check whether each parameter meets the expected range and whether the electronically controlled actuator has performed its target function as designed.

[0134] Optionally, in determining the control results, it is possible to evaluate whether the electronically controlled actuator can fully perform the task, such as whether the tail fin successfully deploys from the initial position to the target position or retracts from the open state to the closed state. Analyze the dynamic response of the motor during the function execution process, including start-up time, operating speed, stability, and energy consumption. For example, check whether the motor reaches the target speed within a specified time, whether abnormal vibrations occur during operation, and whether the energy consumption is within a reasonable range throughout the process. Check whether the response of the electronically controlled actuator is safe during testing, especially during fault injection testing, and whether the controller can detect and adapt to faults, such as whether the motor stall protection or tail fin anti-pinch function is effectively triggered. Verify whether the response of the electronically controlled actuator is consistent under the same test cases, whether the test results are repeatable, and ensure the stability and predictability of the control algorithm.

[0135] Optionally, during the process of determining test results, a comprehensive analysis can be conducted based on the control results to confirm the overall function and performance of the electronic control actuator under test in the target test scenario. Based on the comprehensive analysis, the success of the entire test is determined, i.e., whether the electronic control actuator under test fully meets all test requirements, including the accuracy of functional execution, the timeliness of dynamic response, safety and robustness, and the consistency and repeatability of performance. The test results are summarized, including successes, identified problems and their severity, and recommended improvement measures, forming a detailed test report to provide a basis for subsequent R&D decisions or product improvements.

[0136] Optionally, during the result feedback and iteration process, test results, especially failed tests and encountered problems, can be reported to the R&D team. Based on the test results, control algorithm parameters can be adjusted or hardware design optimized to resolve identified issues or improve performance. After modifications, the above steps are repeated to perform HIL testing on the updated electronic control actuator again until all tests pass.

[0137] In this embodiment of the application, within the HIL testing framework, determining functional test results based on simulation results is a systematic process encompassing data analysis, control result evaluation, test result judgment, and result feedback and optimization. Through meticulous data analysis and rigorous testing standards, this process ensures the maturity of the control algorithm and the reliability of the hardware performance of the electronically controlled actuator, laying a solid foundation for improving overall system performance and promoting product innovation. Each test result not only reflects the current design level.

[0138] In this embodiment, during the process of determining the test result based on the control result, if the control result indicates that the electronic control actuator under test has not simulated and completed the target function, or that the function simulated and completed by the electronic control actuator under test is not the target function, the test result can be determined as having an accuracy level lower than the accuracy threshold. If the control result indicates that the electronic control actuator under test has simulated and completed the target function, the test result can be determined as having an accuracy level greater than or equal to the accuracy threshold.

[0139] Optionally, during the evaluation of control results, the control results can be analyzed from the simulation results of the HIL test, focusing on whether the electronically controlled actuator under test performed the target function as expected, and the accuracy and efficiency of the performance. Control results are categorized into two types: one where the electronically controlled actuator successfully and accurately performed the target function, and the other where it failed to successfully or accurately perform the target function. Failure may include complete non-execution, interrupted execution, or execution failure; inaccuracy may manifest as deviations during execution exceeding the allowable range.

[0140] Optionally, in determining the accuracy level, an accuracy threshold is defined based on design requirements and testing standards. This threshold serves as the benchmark for evaluating the accuracy of the electronically controlled actuator's function execution. This accuracy threshold can be a comprehensive standard based on multiple key performance indicators such as position deviation, speed control accuracy, and energy efficiency. The accuracy reflected in the control results is compared with the preset accuracy threshold to determine whether the test results meet the standard.

[0141] Optionally, during the process of determining the test results, if the control results indicate that the electronically controlled actuator failed to simulate the target function, or that the function performed differed significantly from the target (accuracy below the accuracy threshold), the test result is determined to be a failure or requires improvement. This indicates a defect in the control algorithm or hardware design, which may require adjustment of the control logic, optimization of parameter settings, or consideration of hardware component replacement. If the control results indicate that the electronically controlled actuator successfully and accurately completed the target function (accuracy greater than or equal to the accuracy threshold), the test result is determined to be a success or meets the standard. This indicates that the current control strategy and hardware configuration meet the design standards, and subsequent testing can continue or preparations can be made for the next stage of development.

[0142] Optionally, during the results feedback and optimization process, test results can be fed back to the project team, including the control algorithm designer, hardware engineer, and system integrator, to ensure all stakeholders are aware of the test results. For test results with accuracy below the threshold, the team should analyze the specific reasons, which may include defects in the control algorithm, mismatches in hardware parameters, or errors in the test environment, and then develop targeted optimization solutions. After optimization, retesting should be conducted, and the optimized control algorithm or hardware configuration should be re-deployed in the HIL test environment until the accuracy of all test results reaches or exceeds the accuracy threshold.

[0143] In this embodiment, by systematically evaluating the control results and comparing them with an accuracy threshold, the test results of the target function are determined, providing clear guidance for the performance optimization and system integration of the electronically controlled actuator. The accuracy threshold, as a benchmark for performance evaluation, helps the team distinguish whether the system performance meets design requirements, and thus take corresponding adjustment measures to ensure the quality and efficiency of product development.

[0144] The following section further explains how to record the test failure process when the test result is less than the accuracy threshold in this embodiment.

[0145] As an optional implementation, the method further includes: in response to a test result indicating that the accuracy is lower than an accuracy threshold, generating record information corresponding to the test result, wherein the record information is used to indicate the reason for the failure of the target function test in the target test scenario; and displaying the test result and / or record information on a graphical user interface to obtain a display result.

[0146] In this embodiment, the recorded information can be used to record and analyze in detail the reasons for failure to meet predetermined standards, helping engineers locate the problem and take effective corrective measures. The recorded information can include the following types of data: test case details, actual simulation results, deviation analysis, fault detection, and suggestions and actions. Specifically, the test case details describe the specific test scenario and target function, including the expected control signal parameters and the expected action state of the actuator. The actual simulation results present the actual dynamic response of the actuator in the target test scenario, including the motor's position, speed, torque curve, and other real-time data related to function execution. The deviation analysis compares the expected results with the actual simulation results, detailing the deviations of various performance indicators, such as position deviation, speed control error, and excessive energy consumption. The fault detection records any abnormalities that occur during execution, including hardware failures, software errors, communication interruptions, or incorrect settings in the simulation environment. The suggestions and actions, based on deviation analysis and fault detection, propose possible solutions or improvement measures, as well as the next action plan, such as algorithm adjustments, hardware upgrades, or test case modifications.

[0147] Optionally, a graphical user interface (GUI) can be an intuitive human-computer interaction method, widely used in test software, enabling test engineers to easily and quickly monitor and manage test processes and results. In a HIL test system, the GUI can have the following functions: test result visualization, real-time monitoring, record information retrieval, test case management, and interactive control. Specifically, test result visualization can be used to transform complex test data into charts, curves, or dashboards, intuitively displaying the accuracy of the target function and the comparison between actual values ​​and thresholds. Real-time monitoring can provide real-time system status and test progress, such as currently executing test cases, simulation timelines, and motor status indicators, helping engineers quickly grasp the test dynamics. Record information retrieval allows the GUI to clearly display recorded information when tests fail, including specific deviations, fault details, and recommended corrective actions, facilitating rapid problem location and action. Test case management provides an interface for editing, storing, and retrieving test cases, enabling test engineers to easily create, modify, and select test scenarios, as well as record and track test history. It allows users to manually or automatically control the testing process, including the selection of test cases, starting / pausing / stopping tests, and adjusting parameters, thus enhancing the flexibility and efficiency of testing.

[0148] In this embodiment, the combined use of recorded information and a GUI within the HIL testing framework significantly improves the transparency of the testing process and the efficiency of engineers. The detailed and accurate recording of information makes problem localization more scientific and systematic; while the intuitiveness and convenience of the GUI make test management more efficient and user-friendly. The two complement each other, jointly supporting the efficient operation of HIL testing.

[0149] The following uses the rear wing of a vehicle as an example to illustrate the above technical solution of this application embodiment.

[0150] Currently, electric rear wings, as a core functional module of vehicle body control systems, provide crucial downforce at high speeds, effectively improving vehicle stability. Therefore, comprehensive testing of the rear wing's software functionality is essential. However, current functional testing of rear wings primarily relies on real-vehicle testing, which suffers from the following significant problems: Low testing efficiency. Real-vehicle testing is difficult to automate, requiring manual operation, resulting in long testing cycles and high labor costs. Furthermore, testing cannot be conducted in the early stages of development when no real-vehicle vehicles are available, and testing time is limited to weekday daytime, severely impacting development progress. Difficulty in testing under special operating conditions. Many complex operating conditions are difficult to simulate in a real-vehicle environment or are extremely costly to simulate, such as: reproducing continuous stall conditions, precise control testing of anti-pinch angle and force, verification of ice-breaking function in low-temperature environments (requiring a dedicated environmental chamber), and rear wing deployment / retraction testing at high speeds (requiring a rotating test bench). Limited testing resources. The high cost per vehicle for models under development and the limited availability of vehicles for testing severely restrict the comprehensive implementation of testing work.

[0151] To address the aforementioned issues, there is an urgent need to introduce a HIL (Hardware-in-the-Loop) simulation testing solution. This application's embodiment establishes a high-precision closed-loop model of the entire vehicle and constructs a virtual vehicle testing environment in a laboratory setting. This allows for flexible configuration of various test conditions, including extreme conditions that are difficult to achieve in a real vehicle. This method not only significantly improves the depth and breadth of testing but also effectively reduces the development risk of the controller. Therefore, building a professional, full-function test environment for the rear wing bench, and using bench testing as the primary means of verifying the rear wing's functionality, has become an inevitable trend in the industry.

[0152] The methods of the embodiments of this application will be further illustrated below.

[0153] The purpose of this application is to overcome the shortcomings of related technologies and provide a technical solution for a highly integrated, accurate, and comprehensive HIL test platform and method for automotive rear wing control systems.

[0154] Figure 2 This is a schematic diagram of a hardware-in-the-loop testing system for an electric rear wing of an automobile based on single-Hall simulation, according to an embodiment of this application. Figure 2As shown, the test system may include an NI hardware system 21, a Simulink model system 22, a test software system 23, and an RDCU domain controller 24. The NI hardware system 21 may include an I / O board 211, a PWMO board 212, and a CAN transceiver 213. The Simulink model system 22 may include an I / O interface model 221 and a high-precision simulation model 222 for the tail fin motor Hall. The high-precision simulation model 222 for the tail fin motor Hall may include an initial calibration model 2221, a tail fin deployment model 2222, a tail fin folding model 2223, a tail fin stall model 2224, a tail fin anti-pinch model 2225, and a tail fin icebreaking model 2226. The test software system 23 may include a multi-board test toolchain 231. The multi-board test toolchain 231 may include an Excel visualization front-end interface 2311, CAN / analog / digital signal control 2312, Simulink model control 2313, and UDS / XCP / SOA protocol control 2314.

[0155] Optionally, such as Figure 2 As shown, the IO board 211 can be used to simulate and acquire various types of input and output signals, including analog and digital signals, and is an important interface for communication between the hardware system and the controller. In HIL testing, it can generate simulated Hall sensor signals and also capture motor drive signals, establishing a signal bridge between the controller and the model system. It can be used to simulate the acquisition of signals from the external Hall sensor of the tail fin and the output of tail fin motor drive signals.

[0156] The PWMO board 212 can be used to generate high-precision PWM signals to simulate the feedback signals from the Hall sensors inside the tail fin motor, which is crucial for testing the accuracy of the tail fin control algorithm. The PWMO board ensures the real-time performance and accuracy of the signal. It is used to accurately simulate the PWM signals generated by the Hall sensors inside the tail fin motor.

[0157] The CAN transceiver 213 can be used to simulate CAN communication in a vehicle network environment, ensuring that the RDCU controller can exchange data with other components of the platform (such as model systems and test software systems). It can be used to simulate a vehicle CAN network environment, enabling bus signal interaction with the RDCU controller.

[0158] The IO interface model 221 plays a conversion and adaptation role in the signal simulation process, ensuring that the control signals from the RDCU can be understood by the model system, and also converting the feedback signals of the model system into a form that the RDCU can read. It is the key to realizing signal communication between the model system, the hardware system, and the controller. It performs signal conversion between the hardware IO board and the simulation model; it converts the load model's state information and test inputs into electrical signals (such as CAN messages, analog signals, and PWM signals) that the RDCU controller can recognize, and at the same time converts the control signals (such as motor drive signals) issued by the RDCU into physical signals for use by the load model. This model manages the signal list and configures the NI real-time interface according to the controller interface definition, and processes signal types including CAN signals, external Hall analog signals, motor Hall analog PWM signals, and tail fin motor drive signals.

[0159] The Hall high-precision simulation model 222 for the tail fin motor is subdivided into six sub-models, each corresponding to the simulation of the tail fin motor under different operating conditions. Specifically, these include: the initial calibration model 2221, which simulates the behavior of the tail fin motor during initial startup or recalibration, ensuring the motor can accurately find zero position, serving as the starting point for subsequent control operations; the tail fin deployment model 2222, which simulates the dynamic process of the tail fin deployment under normal conditions, including motor acceleration, stable operation, deceleration and stopping, and the accuracy of position feedback; the tail fin folding model 2223, which, in contrast to the deployment model, simulates the process of the tail fin retracting to its initial position, also focusing on the timeliness of motor response and position control accuracy; the tail fin stall model 2224, which simulates the motor's reaction when the tail fin encounters obstacles during deployment or folding, ensuring the controller can detect and respond to stalling phenomena in a timely manner, preventing motor damage; and the tail fin anti-pinch model 2225, which tests the anti-pinch mechanism when the tail fin detects foreign objects such as fingers entering during operation, verifying whether the control logic can correctly trigger the protective action, ensuring user safety. The tail fin ice-breaking model 2226 can be used to simulate the tail fin's activation in low-temperature environments, especially the motor's ice-breaking capability when the surface is covered with frost, and to check the stability and reliability of the tail fin control system in harsh environments.

[0160] The multi-board test toolchain 231 is an integrated test tool comprising four main functional modules: an Excel visual front-end interface 2311, providing an intuitive user interface that allows test engineers to easily create, modify, and manage test cases by editing Excel spreadsheets, greatly simplifying the test plan development process; CAN / digital / analog signal control 2312, used to control signals between the controller and the model system, including CAN communication signals and digital / analog signals, ensuring accurate transmission and reception of test data; Simulink model control 2313, capable of controlling the operating status of the Simulink model, including start / stop and signal input adjustment, to achieve flexible simulation of different test scenarios; and UDS / XCP / SOA protocol control 2314, supporting interface with various communication protocols commonly used in automotive electronic systems, such as Unified Diagnostics Services (UDS), eXtended Calibration Protocol (XCP), and Service-Oriented Architecture (SOA), enabling the test software system to comprehensively cover all service and diagnostic functions of the controller.

[0161] The RDCU domain controller 24 is the control center of the vehicle's rear wing under test. It receives control signals from the test software system 23 transmitted through the hardware system and drives the rear wing motor based on these control signals. Simultaneously, it can also send feedback signals to the test platform to report the motor's real-time status. The performance of the RDCU is the core objective for verifying the entire test system.

[0162] This application embodiment, through the collaborative design and deep integration of the aforementioned hardware system, model system, and test software system, constructs a highly reliable and efficient verification environment capable of performing full lifecycle verification of the rear wing control software integrated in the RDCU. The platform's test case coverage exceeds 90%, comprehensively covering conventional functional conditions, boundary conditions, and fault injection modes, with 100% coverage of basic functions and 80% coverage of abnormal conditions. Practice shows that this platform significantly improves verification efficiency, shortening the development cycle of the rear wing control system by approximately 40%, while increasing the defect detection rate by 60%, providing strong assurance for product reliability. By integrating high-performance hardware, high-precision models, and automated test software, comprehensive, efficient, and accurate HIL testing of the automotive rear wing control system is achieved, solving several challenges in integrated controller testing and significantly improving development efficiency and product quality.

[0163] It should be noted that the hardware system of the aforementioned HIL test platform can also be built using other brands of real-time emulators (such as dSPACE, ETAS, Speedgoat, etc.), as long as it has a high-speed real-time processor, abundant multi-type I / O board resources (including CAN, analog, digital, PWM, etc.), and can be seamlessly integrated with the model development environment (such as Simulink), all of which are equivalent substitutes or variations of this solution. The analog Hall sensor signal is not limited to using a dedicated PWM output board; its voltage characteristics can also be simulated using a high-precision analog output board, or a customized waveform output with higher frequency and lower latency can be achieved through an FPGA board, which is then converted into the required PWM signal by an external circuit. Such solutions that achieve the same signal simulation purpose based on different hardware resources are all within the protection scope of the embodiments of this application.

[0164] Furthermore, the simulation model system can be developed not only based on MATLAB / Simulink, but also using other modeling environments (such as AMESim, Dymola) or directly using programming languages ​​such as C / C++ and Python, and deployed to the real-time target machine through automatic code generation technology. As long as it implements the functional characteristics of the IO interface model and the motor Hall model, it is considered an equivalent implementation of the embodiments of this application. The test software system is not limited to using the self-developed multi-board test tool, but can also be built based on mainstream commercial test software (such as NI TestStand, Vector CANoe, dSPACE AutomationDesk). Its core lies in having the functions of visual test case editing, automated test sequence execution, automatic result judgment and report generation, and the ability to read and write various signals and protocols. The platform architecture and method are not limited to testing the tail wing control system. By replacing the IO model, load model and test cases, the platform can be easily reused to test other similar vehicle body control systems, such as windows, seats, power tailgates, power sliding doors and other systems driven by motors and requiring precise position control. This generalized test platform design concept is an important variation and application extension of this application.

[0165] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0166] According to another aspect of the embodiments of this application, corresponding to the embodiments of the above-described functional testing method for electronically controlled actuators in vehicles, this specification also provides a functional testing system for electronically controlled actuators in vehicles. Figure 3 This is a schematic diagram of a functional testing system for an electronically controlled actuator in a vehicle, according to an embodiment of this application. Figure 3 As shown, the functional testing system 300 for the electronic control actuators in the vehicle may include: a testing software system 302, a hardware system 304, a simulation model system 306, and a domain controller 308.

[0167] Among them, the test software system 302 is used to respond to test instructions triggered by the electronic control actuator under test for the vehicle and generate test cases corresponding to the electronic control actuator under test.

[0168] Hardware system 304 is used to determine the control signal of the motor of the electrical control actuator under test.

[0169] The simulation model system 306 is used to determine the target simulation model from the set of simulation models included in the simulation model system based on the target test scenario indicated by the test cases; to simulate the test scenario using the target simulation model; and to trigger the motor to drive the electrical control actuator under test in the simulated test scenario using control signals to simulate the execution of the target function to be tested in the target test scenario and obtain the simulation results.

[0170] Domain controller 308 is used to determine the test results of the target function based on simulation results.

[0171] The above embodiments will be further explained below.

[0172] As an optional implementation, the simulation system also includes an interface model, which is used to convert test cases into electrical signals of the vehicle, wherein the electrical signals are used to represent the operating state of the vehicle during the testing of the target function.

[0173] As an optional implementation, the electrical signals include a first electrical signal and a second electrical signal. The first electrical signal represents the operating status of the network in the vehicle, and the second electrical signal represents the operating status of the motor. The hardware system includes: a network simulation module for simulating the first electrical signal to obtain a network simulation result; and a motor signal simulation module for simulating the second electrical signal to obtain a motor simulation result. A domain controller generates a control signal based on the received network simulation result and motor simulation result, and sends the control signal to the hardware system. The hardware system sends the received control signal to the simulation system.

[0174] As an optional implementation, the electronic control actuator under test includes the vehicle's rear wing, and the simulation model set corresponding to the rear wing includes at least one of the following: a rear wing deployment model, used to simulate the test scenario corresponding to the process of switching from a retracted state to a preset deployment state; a rear wing folding model, used to simulate the test scenario corresponding to the process of switching from a preset deployment state to a retracted state; a rear wing stall model, used to simulate the test scenario corresponding to the process of encountering an obstacle during the state switching process, causing the rear wing to be in an abnormally stationary state; a rear wing anti-pinch model, used to simulate the test scenario corresponding to the process of the rear wing encountering an obstacle during the state switching process and switching to a stopped state or a reversed state; and a rear wing ice-breaking model, used to simulate the test scenario corresponding to the process of the rear wing switching from a frozen state to an operating state.

[0175] According to another aspect of the embodiments of this application, corresponding to the embodiments of the above-described method for testing the function of electronically controlled actuators in vehicles, this specification also provides a device for testing the function of electronically controlled actuators in vehicles. Figure 4 This is a structural block diagram of a functional testing device for an electronically controlled actuator in a vehicle, as shown in an embodiment of this application. Figure 4 As shown, the functional testing device 400 for the electronic control actuator in the vehicle may include: a generation unit 402, a first determination unit 404, a simulation unit 406, and a second determination unit 408.

[0176] The generation unit 402 is used to generate test cases corresponding to the electronic control actuator under test in response to test commands triggered for the vehicle's electronic control actuator under test. The first determining unit 404 is used to determine the target simulation model from the simulation model set and the control signal of the motor of the electronic control actuator under test based on the target test scenario indicated by the test cases. The simulation unit 406 is used to simulate the target test scenario using the target simulation model and, using the control signal, trigger the motor to drive the electronic control actuator under test in the simulated target test scenario to simulate the execution of the target function to be tested in the target test scenario, and obtain the simulation result. The second determining unit 408 is used to determine the test result of the target function based on the simulation result.

[0177] According to another aspect of the embodiments of this application, embodiments of this application also provide a vehicle, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0178] Figure 5 This is a structural block diagram of an autonomous vehicle according to an embodiment of this application, such as... Figure 5As shown, the components of the autonomous vehicle 500 include, but are not limited to, a memory 510 and a processor 520. The processor 520 and the memory 510 are connected via a bus 530, and the database 560 is used to store data.

[0179] The autonomous vehicle 500 may also include an access device 540, which enables the autonomous vehicle 500 to communicate via one or more networks 550. Examples of these networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of wired or wireless network interface (e.g., a network interface controller (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, a Near Field Communication (NFC) interface, and so on.

[0180] In one embodiment of this disclosure, the aforementioned components of the autonomous vehicle 500 and Figure 5 Other components not shown can also be connected to each other, for example, via a bus. It should be understood that... Figure 5 The illustrated block diagram of an autonomous vehicle is for illustrative purposes only and is not intended to limit the scope of this disclosure. Those skilled in the art can add or replace other components as needed.

[0181] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program runs, it controls the device where the computer-readable storage medium is located to execute the methods of the various embodiments of this application. Embodiments of this application also provide a computer program product including a computer program that, when executed by a processor, implements the methods of the various embodiments of this application. Embodiments of this application also provide a computer program product including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods of the various embodiments of this application.

[0182] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application. In the above embodiments of this application, the descriptions of each embodiment have different focuses; parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments.

[0183] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0184] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0185] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0186] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0187] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of function test of an electrically controlled actuator in a vehicle, characterized by, The method comprises the following steps: in response to a test instruction triggered by a to-be-tested electric control actuator of a vehicle, generating a test case corresponding to the to-be-tested electric control actuator; based on a target test scene indicated by the test case, determining a target simulation model from a simulation model set, and determining a control signal of a motor of the to-be-tested electric control actuator, wherein different simulation models in the simulation model set correspond to different test scenes of the to-be-tested electric control actuator, and the different test scenes are used to provide an environment for testing different functions of the to-be-tested electric control actuator; using the target simulation model, simulating the target test scene, and using the control signal to trigger the motor to drive the to-be-tested electric control actuator in the simulated target test scene to simulate the execution of a target function to be tested in the target test scene, and obtaining a simulation result; based on the simulation result, determining a test result of the target function, wherein the test result is used to represent the accuracy of the to-be-tested electric control actuator in simulating the execution of the target function in the simulated target test scene.

2. The method of claim 1, wherein, determining the control signal of the motor of the to-be-tested electric control actuator comprises: converting the test case into an electrical signal of the vehicle, wherein the electrical signal is used to represent the running state of the vehicle in the process of testing the target function; based on the electrical signal, determining the control signal.

3. The method of claim 2, wherein, The electrical signal comprises a first electrical signal and a second electrical signal, the first electrical signal is used to represent the running state of a network in the vehicle, and the second electrical signal is used to represent the running state of the motor. Based on the electrical signal, the control signal is determined, comprising: using a network simulation module to simulate the running state of the network based on the first electrical signal to obtain a network simulation result, and using a motor signal simulation module to simulate the running state of the motor based on the second electrical signal to obtain a motor simulation result; using a domain controller corresponding to the to-be-tested electric control actuator to determine the control signal based on the network simulation result and the motor simulation result.

4. The method of claim 3, wherein, The second electrical signal comprises a first sub-electrical signal and a second sub-electrical signal, the first sub-electrical signal is used to represent the position state of the motor, and the second sub-electrical signal is used to represent the running state of the motor. The motor signal simulation module comprises a first simulation module and a second simulation module, the first simulation module corresponds to the first sub-electrical signal, and the second simulation module corresponds to the second sub-electrical signal. Converting the test case into the electrical signal of the vehicle comprises: using the first simulation module to convert the position information of the to-be-tested electric control actuator in the test case into the first sub-electrical signal; using the second simulation module to convert the state information of the motor in the test case into the second sub-electrical signal; or, using a motor signal simulation module to simulate the running state of the motor based on the second electrical signal to obtain a motor simulation result, comprising: The first simulation module is used to simulate the position state based on the first sub-electrical signal, and obtain the motor simulation result corresponding to the first sub-electrical signal, The second simulation result is used to simulate the operation state based on the second sub-electrical signal, and obtain the motor simulation result corresponding to the second sub-electrical signal.

5. The method of claim 1, wherein, The target simulation model is used to simulate the target test scene, and the control signal is used to trigger the motor to drive the to-be-tested electric control actuator in the simulated target test scene, so as to simulate the execution of the target function to be tested in the target test scene, and obtain a simulation result, including: The control signal is converted into a physical signal, and the target simulation model is initialized to obtain an initialized target simulation model; The initialized target simulation model is used to simulate the dynamic behavior of the motor in the target test scene based on the physical signal, and obtain the simulation result, wherein the dynamic behavior represents the behavior required by the motor to drive the to-be-tested electric control actuator to simulate the execution of the target function.

6. The method according to any one of claims 1 to 5, characterized in that, Based on the simulation result, the test result of the target function is determined, including: Based on the simulation result, the control result of the to-be-tested electric control actuator is determined, wherein the control result represents whether the to-be-tested electric control actuator simulates the execution of the target function; In response to the control result being that the to-be-tested electric control actuator does not simulate the execution of the target function, or the to-be-tested electric control actuator simulates the execution of a function different from the target function, it is determined that the test result is that the accuracy is lower than the accuracy threshold; In response to the control result being that the to-be-tested electric control actuator simulates the execution of the target function, it is determined that the test result is that the accuracy is greater than or equal to the accuracy threshold.

7. A system for testing the function of an electrically controlled actuator in a vehicle, characterized in that Including: A test software system is used to generate a test case corresponding to a to-be-tested electric control actuator of a vehicle in response to a test instruction triggered by the to-be-tested electric control actuator; A hardware system is used to determine a control signal of a motor of the to-be-tested electric control actuator; A simulation model system is used to determine a target simulation model from a simulation model set included in the simulation model system based on a target test scene indicated by the test case, wherein different simulation models in the simulation model set correspond to different test scenes of the to-be-tested electric control actuator, and different test scenes are used to provide an environment for testing different functions of the to-be-tested electric control actuator; the target simulation model is used to simulate the test scene, and the control signal is used to trigger the motor to drive the to-be-tested electric control actuator in the simulated test scene, so as to simulate the execution of the target function to be tested in the target test scene, and obtain a simulation result. The domain controller is configured to determine a test result of the target function based on the simulation result, wherein the test result is used to represent an accuracy degree of the electric control actuator under the test scenario.

8. The system of claim 7, wherein, The simulation system further comprises an interface model, wherein the interface model is configured to convert the test case into an electrical signal of the vehicle, and the electrical signal is used to represent an operating state of the vehicle during the test of the target function.

9. The system of claim 8, wherein, The electrical signal comprises a first electrical signal and a second electrical signal, the first electrical signal is used to represent an operating state of a network in the vehicle, and the second electrical signal is used to represent an operating state of the electric motor. The hardware system comprises: a network simulation module configured to simulate the first electrical signal to obtain a network simulation result; an electric motor signal simulation module configured to simulate the second electrical signal to obtain an electric motor simulation result; The domain controller is configured to generate the control signal based on the received network simulation result and electric motor simulation result, and send the control signal to the hardware system.

10. The system of claim 7, wherein, The hardware system is configured to send the received control signal to the simulation system. The electric control actuator comprises a tail wing of the vehicle, and the simulation model set corresponding to the tail wing comprises at least one of the following: a tail wing unfolding model configured to simulate an operating state of the tail wing, and simulate a process corresponding to the test scenario, in which the tail wing is switched from a retracted state to a preset unfolded state; a tail wing folding model configured to simulate the operating state, and simulate a process corresponding to the test scenario, in which the tail wing is switched from the preset unfolded state to the retracted state; a tail wing stall model configured to simulate a process corresponding to the test scenario, in which the tail wing is in an abnormal stationary state due to an obstacle encountered during the state switching process; a tail wing anti-pinch model configured to simulate a process corresponding to the test scenario, in which the tail wing is switched to a stop state or a reverse state due to an obstacle encountered during the state switching process; a tail wing ice-breaking model configured to simulate a process corresponding to the test scenario, in which the tail wing is switched from an ice state to the operating state.

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