Active hood active and passive fusion test method based on pre-sensing trigger system

Abstract

The invention relates to the technical field of automobile safety, in particular to an active hood active and passive fusion test method based on a pre-sensing trigger system. Comprising the following steps: constructing an AEB VRU test scene, and configuring a vehicle state, an active hood actuator and hood image sensing equipment; executing a C2VRU AEB scene test to enable a target object to collide with or approach to collide with the test vehicle according to a track, and synchronously acquiring related signals and images; whether the hood is pre-unfolded or not is judged according to the actuator signals and the images, hood unfolding time DT is obtained, and TTC is extracted from the vehicle signals; in combination with a WAD-HIT relational graph, determining dynamic and static conditions of the head test based on DT, TTC and HIT time relations; and selecting a collision point according to a judgment result to execute a dynamic or static head test. According to the technical scheme, the effectiveness and efficiency of test evaluation can be improved, and the test cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of automotive safety technology, specifically to an active hood active-passive fusion test method based on a pre-sensing triggering system. Background Technology

[0002] With the significant improvement in the level of automotive intelligence, intelligent vehicles are widely equipped with diverse sensor devices such as cameras and radar. This has enabled vehicles to achieve a qualitative leap in their ability to perceive traffic environment elements, allowing them to acquire surrounding environmental information more accurately and comprehensively.

[0003] In the field of pedestrian protection, active hood technology has emerged as an important safety measure. The traditional design of an active hood involves placing a long strip of pressure sensors and local acceleration sensors between the vehicle's front bumper and the anti-collision beam. The main function of these sensors is to detect the collision signal generated when the vehicle collides with a pedestrian's legs. When the collision signal received by the sensors reaches a preset threshold, it triggers an actuator at the hinge position. The actuator quickly lifts the hood, thereby increasing the energy absorption space between the hood and the hard points in the engine compartment, effectively reducing the injury suffered by pedestrians or cyclists in a collision.

[0004] However, the sensor solutions used in traditional active hoods have many limitations. Firstly, these sensors are highly susceptible to impact type and environmental factors (such as temperature and humidity). Under different impact conditions, the signal characteristics received by the sensors may vary significantly, and changes in ambient temperature and humidity can interfere with the normal operation of the sensors, leading to unstable performance. This makes traditional active hoods prone to false or missed detonations in practical applications. False detonations not only cause unnecessary damage to the hood and increase maintenance costs but may also interfere with the normal operation of the vehicle; missed detonations fail to protect pedestrians at critical moments, seriously threatening pedestrian safety. Secondly, traditional solutions typically require the active hood to be fully deployed before the pedestrian's head collides with it; otherwise, the hood may fail to provide timely cushioning, potentially causing greater head injuries to the pedestrian.

[0005] With the continuous advancement of automotive technology, active hood solutions based on ADAS (Advanced Driver Assistance Systems) perception are gradually being introduced to the market. ADAS perception solutions offer significant advantages, enabling more accurate collision detection and allowing for flexible adjustment of the detonation threshold based on actual conditions. This not only greatly reduces the incidence of false detonation and improves system reliability, but also enables early detonation operations due to its ability to identify collision risks in advance, further enhancing the protective effectiveness of the active hood. Furthermore, ADAS perception solutions eliminate the need for front-mounted contact sensors, effectively reducing vehicle manufacturing costs and aligning with the automotive industry's trend towards cost reduction and improved cost-effectiveness.

[0006] Currently, testing methods for active hoods primarily focus on traditional active hoods. In the perception verification phase, a leg-like impactor is typically used to strike different locations on the front of the vehicle to simulate a pedestrian's leg impact, thereby verifying the effectiveness of the perception system and the hood's deployment time. The hood's deployment time determines whether the head impact test should be conducted statically or dynamically. The head impactor test involves striking the hood at a speed of 40 km / h to simulate the head injuries suffered by a pedestrian in a collision.

[0007] However, this traditional testing method reveals significant inapplicability when dealing with ADAS-based active engine hoods. ADAS-based active engine hoods possess unique sensing methods and operating principles, relying on advanced sensors and algorithms to achieve accurate collision detection and early assessment, fundamentally different from traditional active engine hoods that solely rely on contact sensors to sense collision signals. Therefore, traditional testing methods cannot comprehensively and accurately evaluate the recognition effectiveness of ADAS-based active engine hoods and their protective performance in real-world collision scenarios, failing to meet their requirements for normal recognition and protection. Summary of the Invention

[0008] The purpose of this invention is to propose an active-passive fusion test method for active shields based on a pre-sensing triggering system. This technical solution can improve the effectiveness and efficiency of test evaluation and reduce test costs.

[0009] To achieve the above objectives, this invention proposes an active-passive fusion test method for an active shroud based on a pre-sensing triggering system, comprising: Set up an AEB VRU test scenario and configure sensing devices for collecting vehicle status signals, active hood actuator signals and hood image information; Conduct C2VRU AEB scenario tests to make the target object collide with or nearly collide with the test vehicle according to a set trajectory, and simultaneously collect the vehicle status signals, actuator signals and image information. Determine whether the active engine cover has deployed before the vehicle collides with the target object based on the actuator signals and image information. The time DT from the start of the active hood to its full deployment is obtained, and the collision time TTC is extracted based on the vehicle status signal. Obtain the WAD and HIT relationship diagram, and determine the dynamic and static conditions of the head shape test based on the time relationship of DT, TTC and HIT; WAD is the envelope distance of the pedestrian dummy's head impacting the engine hood, and HIT is the time from when the dummy's legs contact the front bumper to when the head contacts the engine hood. Based on the judgment results, a collision point is selected for dynamic or static head shape testing.

[0010] Beneficial effects of the basic solution: This invention proposes for the first time a test method for pre-sensing active hoods, filling a technological gap in the current industry. In existing technologies, the testing and verification of active hoods mostly employs single static or dynamic head-up tests, focusing only on the collision protection performance after the hood is deployed. It lacks a test and verification method for the entire "pre-sensing-activation-deployment" process of the active hood in coordination with the AEB system, and therefore cannot realistically simulate the actual working state of the active hood in response to pedestrian collisions during AEB intervention scenarios.

[0011] This solution is the first to deeply integrate the testing and verification of the active hood with the AEB VRU scenario. By fully collecting vehicle status, active hood actuator signals, and hood image information, it achieves accurate capture and judgment of the timing and process of the active hood deployment. This breaks the limitation of existing tests that only focus on post-collision protection, improves the testing and verification system of the active hood system, and provides new testing support for the research and development and optimization of pre-sensing active hoods.

[0012] This invention can be directly integrated into AEB (Active Emergency Braking) tests for simultaneous execution, without requiring additional test procedures, equipment, or costs. In traditional technologies, active hood tests and AEB tests are independent of each other, requiring separate test scenarios and resources. This not only increases the complexity and workload of the tests but may also lead to a lack of correlation in test results due to differences in test scenarios, failing to accurately reflect the actual effect of their collaborative work.

[0013] This solution, through a rationally designed test process, simultaneously completes the acquisition of relevant signals and images of the active hood, the determination of its deployment status, and the extraction of key time parameters during C2VRU AEB scenario testing. This achieves "one test, multiple verifications," significantly improving test efficiency and reducing manpower, material, and time costs. Furthermore, the test scenario closely matches actual pedestrian collision scenarios encountered by vehicles in motion, ensuring the practicality and reference value of the test results.

[0014] The experimental process of this invention is repeatable and the results are consistent. On the one hand, the solution clearly establishes the AEB VRU test scenario and configures dedicated sensing equipment for collecting vehicle status signals, active hood actuator signals, and hood image information, ensuring the accuracy and comprehensiveness of various data collections. This provides precise data support for subsequent deployment status determination, parameter extraction, and head shape test condition determination, avoiding test result deviations caused by missing or incorrect data.

[0015] On the other hand, the test process was strictly carried out according to the set procedures. The trajectory of the target object and the operating status of the test vehicle were all standardized and controlled. By extracting key parameters such as DT (time from activation to full deployment of the active hood), TTC (time to impact), and HIT (time from the dummy's legs contacting the front bumper to the head contacting the hood), and combining the WAD and HIT relationship diagram, the dynamic and static conditions of the head shape test were determined, ensuring the rationality and standardization of the head shape test. The entire test process can be repeated through standardized operations, effectively avoiding the influence of human factors on the test results and improving the consistency and repeatability of the test results.

[0016] This solution can accurately reproduce real-world pedestrian head collision scenarios, providing experimental support for optimizing the performance of the active hood. Existing single-head-shape tests cannot simulate the dynamic process of a vehicle-pedestrian collision when the AEB system intervenes, and cannot accurately reflect the impact of the timing and state of the active hood's deployment on pedestrian head protection in real-world collision scenarios.

[0017] This solution simulates the dynamic process of a collision or near-collision between a target object and the test vehicle by simultaneously conducting active hood tests in AEB scenarios. It accurately captures key information such as the deployment state and time of the active hood before the collision. Furthermore, by determining the dynamic and static conditions of the head-shape test and selecting appropriate collision points, it can precisely evaluate the protective performance of the active hood for pedestrian heads after deployment. The test results directly reflect the performance of the active hood in real-world working scenarios, providing researchers with precise guidance for optimizing the hood's activation strategy, deployment speed, and structural design. This helps improve the pedestrian protection effect of the active hood and reduce the risk of pedestrian injury in collision accidents.

[0018] Meanwhile, the key parameter extraction method and head shape test condition judgment logic proposed in the solution have strong versatility and scalability, and can be adapted to different types of active hood systems and AEB systems.

[0019] As a feasible and preferred option, setting up an AEB VRU test scenario includes: simulating different weather conditions using artificial rain, fog, and snow equipment; controlling the target object to move along a cross-trajectory, rear-end collision, or cutting trajectory through programming; setting different road types, including straight roads and intersections; and preparing various target object styles, including children, adults, and two-wheeled vehicles.

[0020] As a feasible preferred embodiment, the sensing device includes an inertial navigation system, a current clamp, and an external camera; the inertial navigation system is used to record vehicle speed, acceleration, and TTC signals; the current clamp is clamped near the actuator connection line of the drive hood hinge to record current signals; and the external camera is used to record image information of the rear of the drive hood.

[0021] As a feasible and preferred option, before conducting C2VRU AEB scenario tests, the following steps are also included: starting the test vehicle and performing preheating and break-in, activating the pre-sensing active hood system function, and ensuring that the data recorded by each sensing device remains synchronized in time.

[0022] As a feasible preferred solution, determining whether the active hood has been deployed includes: comparing the time when the current signal is generated with the time when the active hood is activated in the image. If both show that the active hood has been deployed before the vehicle collides with the target object, then the triggering is considered successful.

[0023] As a feasible preferred solution, the active hood deployment time DT includes: inputting a preset vehicle speed and sensing signal to start the active hood system while the vehicle is stationary, using a timer to measure the time from start-up to full deployment of the active hood, and repeating the test multiple times to obtain the average value.

[0024] As a feasible and preferred option, the sensing signals include radar signals that simulate pedestrian approach.

[0025] As a feasible and preferred approach, extracting the Time-to-Collision (TTC) involves: selecting a specific speed scenario for testing; determining the vehicle speed and displacement from the collision point at the moment the hood is triggered based on the displacement and velocity curves in the vehicle state signal; and using the formula: TTC = Distance from the point of collision / Vehicle speed.

[0026] As a feasible and preferred approach, the dynamic and static conditions for head shape testing are determined based on the time relationship between DT, TTC, and HIT, including: In a 60km / h speed scenario, if DT ≤ TTC, it is determined that the active hood was deployed during the head shape test in the passive test. In the 40km / h scenario test, if DT ≤ TTC + HIT, then all head shape tests can be performed statically; otherwise, for a pedestrian of a certain height, if the sum of the head collision time and TTC is less than the deployment time DT of the active engine hood, then the envelope corresponding to the pedestrian of that height and the collision point before it should be tested dynamically.

[0027] As a feasible preferred option, conducting dynamic or static head shape tests includes: marking head impact points on a test vehicle; the static test involves impacting a dummy head with an active shield on a stationary vehicle at a preset speed to measure impact force and acceleration parameters; and the dynamic test involves using a traction device to accelerate the dummy head to a preset speed before impacting the active shield. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the architecture of an active-passive fusion test system based on a pre-sensing triggering system.

[0029] Figure 2 This is a schematic diagram of the trigger timing for the main engine cover.

[0030] Figure 3 A schematic diagram defining the CPNSOA scenario.

[0031] Figure 4 This is a schematic diagram for determining the dynamic and static test points.

[0032] Figure 5 This is a WAD diagram illustrating the moment of head impact for a pedestrian.

[0033] Figure 6 A diagram showing the markings of the area where the vehicle's front end collided with the vehicle. Detailed Implementation

[0034] To make the technical solution and advantages of this application clearer, the technical solution of the present invention will be further described in detail below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are only some embodiments of the present invention, and are only used to explain this application, not to limit it. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered isolated; they can be combined with each other to achieve better technical effects. The same reference numerals appearing in the accompanying drawings of the following embodiments represent the same features or components, and can be applied to different embodiments.

[0035] Furthermore, unless otherwise defined, the technical or scientific terms used in this invention description shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains.

[0036] The present invention will now be described in further detail with reference to the accompanying drawings.

[0037] Figure 1 This disclosure provides an active-passive fusion test method for an active shroud based on a pre-sensing triggering system, comprising: Step S100: Set up the AEB VRU test scenario, including: Weather condition simulation uses artificial rain, fog, and snowfall equipment to simulate different weather conditions.

[0038] The target trajectory is set by programming to control the target object (such as a dummy or a two-wheeled vehicle model) to move according to a preset trajectory (crossing, rear-ending, cutting in).

[0039] Road type construction involves setting up different road types such as straight roads and intersections within the test site, and laying corresponding road surface materials.

[0040] Prepare various target object styles, including those for children, adults, and two-wheeled vehicles, to simulate different traffic participants.

[0041] Step S200, Install and preheat the instruments and equipment, including: The installation of instruments and equipment involves mounting an inertial navigation system (INS), current clamp, external camera, and other instruments and equipment on the test vehicle. The INS is used to record vehicle speed, acceleration, and TTC signals; the current clamp is used to hold the actuator connection wires near the drive hood hinge and record current signals; and the external camera is used to record image information of the rear of the drive hood.

[0042] Start the test vehicle and allow it to warm up and break in for a certain period of time to ensure that the vehicle and equipment are in normal working condition. At the same time, activate the pre-sensing active hood system to ensure that it is in a ready-to-trigger state.

[0043] Step S300: Conduct C2VRU AEB scenario testing, including: The scenario test is executed according to the preset AEB VRU test scenario to ensure that the target object moves along the set trajectory and collides or nearly collides with the test vehicle.

[0044] Data recording involves using inertial navigation equipment to record vehicle speed, acceleration, and TTC signals in real time; using current clamps to record the current signals of the active hood actuators; and using an external camera to record image information of the rear of the active hood.

[0045] Time synchronization ensures that the data recorded by the inertial navigation system, current clamp, and external camera are synchronized in time for subsequent analysis.

[0046] Step S400, determine the trigger status of the active cover, including: Data analysis is used to analyze the triggering of the active shroud based on current and image signals. Specifically, the timing of the current signal generation is compared with the timing of the active shroud activation in the image to determine if they are consistent.

[0047] Trigger determination: If both the current signal and the image signal show that the engine cover has been deployed before the vehicle collides with the target object, the engine cover is determined to have been successfully triggered; otherwise, it is determined to have not been triggered.

[0048] Step S500, measure the start-up time of the active hood, including: For stationary testing, with the vehicle stationary, input the preset vehicle speed and sensing signal (such as radar signal simulating pedestrian approach) to activate the active hood system.

[0049] Time measurement: Use a high-precision timer to measure the time DT from startup to full deployment (shell deployed to its highest position). Repeat the test multiple times and take the average value to improve measurement accuracy.

[0050] Step S600, extract the collision time TTC, refer to Figure 2 ,include: Scene selection: Select a specific speed scenario (e.g., an adult crossing an obstruction at 60 km / h, CPNSOA) for testing. TTC calculation: Based on the displacement and velocity curves recorded by the inertial navigation system, determine the vehicle speed and displacement from the collision point at the moment the active hood is triggered. Calculate the TTC value using the formula: TTC = Distance from collision point / Vehicle speed.

[0051] Step S700: Determine the dynamic and static test conditions, referring to... Figure 4 and Figure 5 ,include: The relationship diagram between WAD and HIT was obtained from the vehicle manufacturer.

[0052] Determination of dynamic and static test conditions: In a 60km / h speed scenario, if DT ≤ TTC, it is determined that the active hood was deployed during the head shape test in the passive test.

[0053] In the 40km / h scenario test, if DT ≤ TTC + HIT, then all head shapes can be tested statically; otherwise, for a pedestrian of a certain height, if the sum of the head impact time (HIT) and TTC is less than the deployment time (DT) of the active hood, then the envelope corresponding to the pedestrian of that height and the impact point before it should be tested dynamically.

[0054] Step S800, perform dynamic and static tests, including: Collision point marking: Mark the head impact point on the test vehicle, referring to the relevant test procedures. Figure 6 .

[0055] Dynamic or static test selection: Based on the judgment result of step S7, select the collision point for dynamic or static test.

[0056] In the static test, a dummy's head is impacted with the active shroud of a stationary vehicle at a preset speed. Parameters such as impact force and acceleration are measured to evaluate the energy absorption performance of the shroud.

[0057] In the dynamic test, a traction device is used to accelerate the dummy's head to a preset speed and then impact the active hood, simulating a real collision scenario and evaluating the hood's protective effectiveness in dynamic collisions.

[0058] This method can be used to verify the triggering reliability of the pre-sensing active hood system in the AEB VRU scenario, and determine the dynamic and static conditions of the subsequent pedestrian protection head test based on the triggering time parameter, thereby realizing the integrated verification of active safety system and passive safety test.

[0059] The above content is merely an embodiment of the present invention. Commonly known structures and characteristics of the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can improve and implement this solution based on the guidance provided in this application and their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for active-passive fusion testing of an active shroud based on a pre-sensing triggering system, characterized in that, include: Set up an AEB VRU test scenario and configure sensing devices for collecting vehicle status signals, active hood actuator signals and hood image information; Conduct C2VRU AEB scenario tests to make the target object collide with or nearly collide with the test vehicle according to a set trajectory, and simultaneously collect the vehicle status signals, actuator signals and image information. Determine whether the active engine cover has deployed before the vehicle collides with the target object based on the actuator signals and image information. The time DT from the start of the active hood to its full deployment is obtained, and the collision time TTC is extracted based on the vehicle status signal. Obtain the WAD and HIT relationship diagram, and determine the dynamic and static conditions of the head shape test based on the time relationship of DT, TTC and HIT; WAD is the envelope distance of the pedestrian dummy's head impacting the engine hood, and HIT is the time from when the dummy's legs contact the front bumper to when the head contacts the engine hood. Based on the judgment results, a collision point is selected for dynamic or static head shape testing.

2. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 1, characterized in that, Setting up AEB VRU test scenarios includes: simulating different weather conditions using artificial rain, fog, and snow equipment; controlling the target object to move along a cross-trajectory, rear-end collision, or cutting trajectory through programming; setting different road types, including straight roads and intersections; and preparing various target object styles, including children, adults, and two-wheeled vehicles.

3. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 1, characterized in that, The sensing devices include an inertial navigation system, a current clamp, and an external camera; the inertial navigation system is used to record vehicle speed, acceleration, and TTC signals; the current clamp is clamped near the actuator connection line of the drive hood hinge to record current signals; and the external camera is used to record image information of the rear of the drive hood.

4. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 1, characterized in that, Before conducting C2VRU AEB scenario tests, the following steps are also taken: starting the test vehicle and performing preheating and break-in, activating the pre-sensing active hood system function, and ensuring that the data recorded by each sensing device is synchronized in time.

5. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 1, characterized in that, Determining whether the active hood has deployed involves comparing the time when the current signal is generated with the time when the active hood is activated in the image. If both show that the active hood has deployed before the vehicle collides with the target object, then the activation is considered successful.

6. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 1, characterized in that, The active hood deployment time DT includes: inputting a preset vehicle speed and sensing signal to activate the active hood system while the vehicle is stationary, using a timer to measure the time from activation to full deployment of the active hood, and repeating the test multiple times to obtain the average value.

7. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 6, characterized in that, The sensing signals include radar signals that simulate the approach of a pedestrian.

8. The active-passive fusion test method for an active shroud based on a pre-sensing triggering system according to claim 1, characterized in that, Extracting the Time-to-Collision (TTC) involves: selecting a specific speed scenario for testing; determining the vehicle speed and displacement from the collision point at the moment the hood is triggered based on the displacement and velocity curves in the vehicle status signal; and using the formula: TTC = Distance from the point of collision / Vehicle speed.

9. The method for constructing an active-passive fusion test method based on a pre-sensing triggering system according to claim 1, characterized in that, The dynamic and static conditions for determining head shape based on the time relationship between DT, TTC, and HIT include: In a 60km / h speed scenario, if DT ≤ TTC, it is determined that the active hood was deployed during the head shape test in the passive test. In the 40km / h scenario test, if DT ≤ TTC + HIT, then all head shape tests can be performed statically; otherwise, for a pedestrian of a certain height, if the sum of the head collision time and TTC is less than the deployment time DT of the active engine hood, then the envelope corresponding to the pedestrian of that height and the collision point before it should be tested dynamically.

10. The method for constructing an active-passive fusion test method based on a pre-sensing triggering system according to claim 1, characterized in that, The dynamic or static head shape test includes marking the head impact point on the test vehicle. The static test involves impacting the dummy head with the active motor cover on the stationary vehicle at a preset speed to measure the impact force and acceleration parameters. The dynamic test involves using a traction device to accelerate the dummy head to a preset speed and then impacting the active motor cover.

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