A method of controlling a wing-type panel of an automotive wind deflector and a computer program product
By incorporating motor-driven airfoil panels within the wind choke and adjusting parameters based on predictive models and driving modes, the problem of existing wind chokes being unable to dynamically adjust wind resistance and air intake has been solved, thus enhancing the user's driving experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA AUTOMOTIVE ENG RES INST
- Filing Date
- 2025-11-25
- Publication Date
- 2026-06-26
AI Technical Summary
The existing wind curtain structure cannot dynamically adjust the balance between wind resistance and air intake according to the driver's real-time driving needs, which affects the user's driving experience.
An airfoil that can be driven by a motor is installed inside the windbreak curtain. The target elongation distance is calculated by adjusting parameters through a predictive model and driving mode, so as to achieve adaptive dynamic adjustment of the airfoil.
It achieves a dynamic balance between wind resistance and air intake based on vehicle driving status and driving mode, thereby improving the user's driving experience.
Smart Images
Figure CN121469233B_ABST
Abstract
Description
Technical Field
[0001] The embodiments in this specification belong to the field of automotive engineering technology, and specifically relate to a method for controlling the airfoil of an automotive windbreak curtain and a computer program product. Background Technology
[0002] The amount of air intake at the front of a car significantly impacts the cooling module's heat dissipation, thus determining the performance of the car's air conditioning and the severity of heat damage within the engine compartment. With advancements in aerodynamics, some vehicles now incorporate a wind deflector at the leading edge of the engine compartment's lower skid plate to increase airflow through the cooling module. However, because existing wind deflectors are fixed structures, neither wind resistance nor airflow volume can be adjusted. Consequently, it's impossible to rebalance these factors based on the driver's real-time driving needs, negatively affecting the user's driving experience. Summary of the Invention
[0003] Embodiments of this disclosure provide a method for controlling the airfoil of an automotive windbreak curtain and a computer program product, which are intended to solve one or more of the above-mentioned problems and other potential problems.
[0004] According to a first aspect of this disclosure, a method for controlling the airfoil of an automotive windbreak curtain is provided, applicable to a vehicle equipped with a windbreak curtain. The windbreak curtain guides airflow into a cooling module. An airfoil that can extend vertically beyond the windbreak curtain is disposed within the windbreak curtain. The method includes acquiring the vehicle speed and the temperature of the cooling module, and outputting the extension distance of the airfoil based on the vehicle speed and temperature using a trained prediction model. The extension distance is inversely proportional to the vehicle speed at the same temperature and directly proportional to the temperature at the same vehicle speed. The method further includes determining the current driving mode of the vehicle, querying the distance adjustment parameters corresponding to the current driving mode, and calculating a target extension distance based on the extension distance and the distance adjustment parameters. Finally, the method includes generating a control command to control the current extension distance of the airfoil as the target extension distance.
[0005] According to a second aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method provided according to the first aspect.
[0006] The solution provided in this specification can predict the optimal airfoil extension distance based on the current vehicle speed and cooling module temperature using a predictive model. Then, it calculates the final target extension distance by combining this with distance adjustment parameters determined by the current driving mode. The airfoil is then adjusted according to this target extension distance, allowing for adaptive dynamic adjustment of the airfoil extension distance based on the vehicle's current driving state and mode. This enables dynamic adjustment of the balance between wind resistance and air intake volume based on the vehicle's actual driving needs (e.g., a greater need to reduce wind resistance or increase air intake volume), resulting in a better user driving experience. (See attached figures.)
[0007] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:
[0008] Figure 1 Schematic diagrams of the structure of windbreak curtains according to some embodiments of the present disclosure are shown;
[0009] Figure 2 A schematic diagram showing a comparison of the pressure difference at the cooling module between a conventional air baffle and an air baffle with a concave arc surface, according to some embodiments of this disclosure;
[0010] Figure 3 A schematic flowchart of an airfoil control method for an automotive windbreak curtain according to some embodiments of the present disclosure is shown.
[0011] Among them, 1-Airfoil, 2-Windproof curtain. Detailed Implementation
[0012] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.
[0013] The terms “comprising” and “having”, and any variations thereof, in this specification, claims, and the foregoing drawings are intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. Depending on the context, the word “if” as it applies herein may be interpreted as “when”, “in response to determination”, or “in response to detection”.
[0014] A wind deflector is essentially an airflow guide plate installed in front of the cooling module. During vehicle movement, the airflow from the front of the car is redirected by the wind deflector, reducing the air pressure on the back of the wind deflector (the side closest to the cooling module). This creates a pressure difference between the front and back of the cooling module, guiding the airflow through it and carrying away heat. In traditional methods, because the structure of the wind deflector is fixed, the wind resistance generated by the airflow acting on the wind deflector and the airflow through the cooling module remain constant at a constant vehicle speed. This cannot adapt to the driving needs of users in different driving environments (for example, sometimes reducing wind resistance to save energy, and sometimes increasing airflow to ensure heat dissipation). Therefore, as... Figure 1 As shown, this application includes an airfoil 1 inside the windbreak curtain 2, which can move vertically from inside the windbreak curtain 2 to outside the windbreak curtain 2 under the drive of a motor. Thus, the airfoil 1 can be adjusted in terms of its extension distance under the control of subsequent methods, dynamically adjusting wind resistance and air intake volume. Furthermore, by... Figure 2 As shown in the pressure simulation analysis diagram, the traditional straight-plate air curtain will affect the airflow passing over its top due to the tip effect, causing it to deflect inward. However, if the shape of the windward side of the air curtain is modified to a concave arc surface, the airflow passing through the air curtain will be deflected more in the vertical direction and the speed in the horizontal direction will be lower. This will generate a larger pressure difference between the front and rear ends of the cooling module and increase the air intake of the cooling module. Therefore, air curtains with concave arc surfaces can be preferred.
[0015] Figure 3 A schematic flowchart of a method 300 for controlling the airfoil of an automotive windbreak curtain, according to some embodiments of this disclosure, is shown. Method 300 can, for example, be executed by the vehicle's onboard controller. Figure 3 As shown in block 302, method 300 can obtain the vehicle speed and the temperature of the cooling module, and output the extension distance of the airfoil by the trained prediction model based on the vehicle speed and temperature. The extension distance is inversely proportional to the vehicle speed at the same temperature and directly proportional to the temperature at the same vehicle speed.
[0016] In this embodiment, by simulating the vehicle in a test environment beforehand, the temperature change of the cooling module over a certain period of time can be collected under different vehicle speeds, temperatures, and airfoil extension distances (a larger temperature change indicates a larger air intake). Then, based on the temperature change, a suitable extension distance is selected for each combination of vehicle speed and temperature (for example, the shortest extension distance that meets the required temperature change threshold can be selected, thus satisfying the air intake requirement while avoiding excessive airfoil extension leading to an excessively large overall force-bearing area between the windbreak and the airfoil, resulting in excessive wind resistance). A predictive model is then trained using this method. Specifically, at the same temperature, the faster the vehicle speed, the greater the amount of air flowing through the front of the vehicle, and the smaller the airflow that needs to be specifically guided to the cooling module to enhance heat dissipation, thus requiring a shorter extension distance. Conversely, at the same vehicle speed, the higher the temperature, the greater the need for heat dissipation, requiring more air to be diverted to the cooling module, thus requiring a longer extension distance. During actual driving, the required extension distance can be predicted by the predictive model based on the vehicle speed and temperature collected in real time by onboard sensors.
[0017] In box 304, method 300 can determine the current driving mode of the vehicle, query the distance adjustment parameters corresponding to the current driving mode, and calculate the target extension distance based on the extension distance and the distance adjustment parameters.
[0018] In this embodiment, when driving the vehicle, the user can select a driving mode, such as an energy-saving mode or a sport mode. Different driving modes indicate different driving needs. For example, the energy-saving mode indicates that the user wants to save energy as much as possible, so reducing the drag coefficient should be prioritized to reduce the vehicle's energy consumption, thus the extension distance should be reduced. Conversely, the sport mode indicates that the user wants to drive at higher speeds, which will cause the engine to heat up more. To ensure the cooling module's heat dissipation, the extension distance should be increased to improve the air intake to the cooling module. Based on human experience and simulation test results, corresponding distance adjustment parameters can be pre-set for different driving modes, and a mapping relationship between driving modes and distance adjustment parameters can be established in a database. Thus, during actual driving, only the current driving mode of the vehicle needs to be read to retrieve the corresponding distance adjustment parameters from the database. The sum of these distance adjustment parameters and the extension distance output by the prediction model is the target extension distance. In this way, the target extension distance is obtained after fully considering the vehicle's current speed, temperature and other parameters, as well as the user's current tendency to adjust wind resistance and air intake. Compared with the extension distance obtained by directly using the prediction model, the target extension distance can better meet the user's current driving needs and make the user's driving experience better.
[0019] In box 306, method 300 can generate control commands to control the current extension distance of the airfoil as the target extension distance.
[0020] In this embodiment, control commands will be generated to drive the motor responsible for controlling the airfoil height, so that the current extension distance of the airfoil is adjusted to the target extension distance (the extension distance of the airfoil is 0 when it is fully retracted into the windbreak curtain), thus completing the adaptive adjustment of the extension distance of the airfoil.
[0021] In one possible implementation, the method further includes:
[0022] Based on historical test data, a training set is determined. The training set includes data pairs constructed from vehicle speed samples and temperature samples, as well as stretch distance samples that correspond one-to-one with the data pairs. The stretch distance sample is the minimum stretch distance that enables the temperature sample to reach a safe temperature within a preset time.
[0023] Based on the data pairs, the predicted elongation distance is generated from the initial model; and
[0024] Using the extended distance samples as supervision signals, the initial model is trained for at least one round to obtain the prediction model.
[0025] In this embodiment, based on historical test data, matched vehicle speed samples and temperature samples can be associated to construct data pairs. A training set for the model is then built based on these data pairs and the extension distance samples. Since the prediction model is used to initially determine an extension distance that achieves a good balance between wind resistance and air intake, the extension distance sample represents the minimum extension distance required for the temperature sample to reach a safe temperature within a preset time, ensuring sufficient air intake while minimizing wind resistance. During the initial model training using the training set, the model's generator can generate predicted extension distances based on the data pairs. The generator loss is obtained by comparing the extension distance samples with the predicted extension distances. This generator loss is then used to assess the loss of the predicted extension distances, using a comparison loss function (e.g., labeled smoothed cross-entropy loss). The generator loss can be a large value, and it can then be backpropagated to the generator to guide parameter optimization, achieving a round of supervised training of the generator. This training process can be iterated round after round until the generator can produce more accurate predictions of the stretch distance, that is, until the loss value calculated by the loss function is smaller. After training, the resulting prediction model can output the stretch distance.
[0026] The initial model can be a linear regression model, a recurrent neural network model, a convolutional neural network model, etc. Taking a convolutional neural network model as an example, the model can include an input layer, at least one convolutional layer (such as Conv1D or Conv2D) + activation function (such as ReLU), a pooling layer (such as MaxPooling or AveragePooling), and a fully connected layer for final prediction.
[0027] In one possible implementation, a training set is determined based on historical test data, including:
[0028] The vehicle speed and temperature samples with the same timestamp in the historical test data are associated to obtain data pairs. The duration of temperature change for the data pairs under different candidate elongation distances is then queried. The duration of temperature change is the time it takes for the temperature sample to change to the safe temperature.
[0029] Based on the duration of each temperature change, elongation distance samples are determined from each candidate elongation distance; and
[0030] A training set is constructed based on the data pairs and the extended distance samples.
[0031] In this embodiment, firstly, vehicle speed samples and temperature samples with the same timestamp from historical test data are grouped together to obtain data pairs. Next, the temperature change duration of each data pair under different candidate extension distances is queried from the historical test data. The temperature change duration can, to some extent, indicate the intake air volume; a longer temperature change duration indicates a smaller intake air volume, resulting in slower heat dissipation. Generally, as long as the temperature change duration is within a preset duration, meaning the cooling module temperature can change to a safe temperature within the preset duration, the current intake air volume can be considered sufficient. Therefore, it is only necessary to select the candidate extension distance with the smallest distance from among all candidate extension distances that meet this condition as the extension distance sample. Finally, the data pairs and the selected extension distance samples are mapped one-to-one to construct a training set.
[0032] In one possible implementation, before the trained prediction model outputs the airfoil elongation distance based on vehicle speed and temperature, the method further includes:
[0033] Determine the current deflection angle of the airfoil and query the prediction model that matches the current deflection angle.
[0034] In this embodiment, the airfoil itself can also have a certain deflection angle. This deflection angle can be controlled by an additional motor driving the airfoil's rotation shaft, and can also be adjusted by the user via buttons on the vehicle's screen. Different deflection angles will result in different pressure distributions between the air curtain and the cooling module, thus affecting the pressure difference before and after the cooling module and the amount of air intake passing through the cooling module. Assuming the deflection angle is 0 degrees when the airfoil is parallel to the vertical direction (if the airfoil is not straight but has a certain curvature, the line connecting the two ends of the curvature is used as the baseline for calculating the deflection angle), generally speaking, for the same extension distance, the smaller the deflection angle, the larger the air intake. The user can adjust the deflection angle according to their preference. Since different deflection angles will result in different air intakes at the cooling module, a prediction model needs to be trained specifically for each deflection angle. During vehicle operation, based on the current deflection angle of the airfoil, the prediction model matching the current deflection angle will be queried, and this prediction model will be used to predict the extension distance.
[0035] In one possible implementation, querying a prediction model that matches the current deflection angle includes:
[0036] Determine the angle range corresponding to the current deflection angle, and then query the prediction model corresponding to the angle range.
[0037] In this embodiment, if the deflection angle is rounded down and the prediction model is trained with a gradient of 1 degree, too many prediction models would need to be trained, and adjustments of one or two degrees would not significantly change the intake volume. Therefore, several angle intervals can be divided into intervals of 5 degrees or 10 degrees, and the median angle of each interval can be used as the standard angle to train the prediction model. The trained prediction model can then be used as the prediction model for that angle interval. After determining the current deflection angle, the angle interval to which the current deflection angle belongs can be queried, and the prediction model for that angle interval can be used as the prediction model for predicting the extension distance in the current state.
[0038] In one possible implementation, generating control commands includes:
[0039] Query the vehicle speed-force mapping relationship corresponding to the current deflection angle, and then query the estimated vehicle speed corresponding to the current force on the airfoil based on the vehicle speed-force mapping relationship; and
[0040] A control command is generated in response to the difference between the estimated vehicle speed and the current vehicle speed being less than a difference threshold.
[0041] In this embodiment, vehicle speed data and airfoil force data at different deflection angles can be collected through vehicle simulation testing or actual testing in a test environment, thereby constructing a speed-force mapping relationship for each deflection angle. Considering that vehicle speed is generally detected in real time by wheel speed sensors, although accurate speed measurement is possible in most cases, in rare cases, sensor damage or tire slippage may lead to inaccurate speed measurements, resulting in inaccurate airfoil extension distances. Therefore, given a fixed deflection angle, the current force on the airfoil collected by the pressure sensor can be used to determine the estimated speed based on the speed-force mapping relationship, thus verifying the currently measured speed. If the difference between the estimated speed and the current speed collected by the wheel speed sensor is less than a threshold difference, the current speed is considered normal, and a control command is generated to adjust the airfoil.
[0042] In one possible implementation, the distance adjustment parameter is negative when the current driving mode is energy-saving mode, positive when the current driving mode is sport mode, and maximum when the current driving mode is off-road mode.
[0043] In this embodiment, in energy-saving mode, wind resistance should be prioritized to reduce energy consumption; therefore, the airfoil should retract more aggressively, and the distance adjustment parameter is negative (the specific value can be set according to requirements). In sport mode, heat dissipation performance should be prioritized; therefore, the airfoil should tend to extend further to increase air intake, and the distance adjustment parameter is positive (the specific value can be set according to requirements). In off-road mode, to prevent impact from flying rocks or cement blockage, the distance adjustment parameter can be adjusted to its maximum value. That is, regardless of the original extension distance, the final target extension distance will be adjusted to the maximum possible extension distance to protect the rear cooling module and radiator as much as possible through the extension of the wind curtain and airfoil. In off-road mode, forced cooling can be achieved using an internal fan.
[0044] In one possible implementation, the method further includes:
[0045] Based on the current driving mode, determine the time interval for generating control commands.
[0046] In this embodiment, the vehicle speed is not constant during actual driving but changes dynamically. If the target extension distance for the airfoil is re-determined and adjusted every time the speed changes, the load on the vehicle system would be too high. Therefore, the sensitivity requirement for airfoil adjustment can be determined based on the current driving mode, and the generation interval of control commands can be adjusted accordingly. Control commands are then generated periodically according to this interval to achieve periodic adjustment of the airfoil. As an example, in energy-saving mode, the user's driving speed is generally not high, and because wind resistance is prioritized, the airfoil is retracted as much as possible or is already fully retracted. Therefore, frequent adjustments to the airfoil are not necessary, and the generation interval can be set slightly longer (e.g., 10 seconds). In sport mode, the user's driving speed is generally higher, and the airfoil is needed to better guide airflow to dissipate heat from the cooling module. Therefore, the generation interval can be set shorter (e.g., 5 seconds) to more accurately adjust the airfoil and ensure sufficient air intake at the cooling module.
[0047] In one possible implementation, the method further includes:
[0048] In response to a vehicle entering a frequently used road segment, a correction parameter is determined based on the vehicle speed range corresponding to the historical average speed of the vehicle in the frequently used road segment. The target extension distance in the frequently used road segment is corrected according to the correction parameter. The frequently used road segment is the road segment with a historical number of trips greater than a preset number.
[0049] In this embodiment, the vehicle can record the road segments it has traveled on the map. If the number of times a certain road segment has been traveled exceeds a preset number, it will be considered a frequently used road segment. Because frequently used road segments are familiar to the user, they may adopt some different driving strategies than usual. For example, although the driving mode is usually kept in energy-saving mode, on frequently used road segments, due to familiar road conditions and less traffic, the user may drive faster. In this case, a strategy closer to sport mode should be adopted, increasing the extension distance and improving the intake volume to avoid engine overheating. Therefore, correction parameters can be determined based on the vehicle's historical average speed corresponding to the speed range on the frequently used road segment (the mapping relationship between the correction parameters and the speed range is preset based on experience; generally, the higher the average speed of the speed range, the larger the correction parameter). When the vehicle is on a frequently used road segment, the target extension distance is further adjusted based on the correction parameters so that the extension of the airfoil can better balance wind resistance and heat dissipation to meet the user's driving needs on that road segment.
[0050] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this specification is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).
[0051] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0052] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. Furthermore, although operations are depicted in a specific order, this should be understood as requiring that such operations be performed in the specific order shown or in sequential order, or requiring that all illustrated operations be performed to achieve the desired result. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations.
[0053] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.
Claims
1. A method for controlling the airfoil of an automotive windbreak curtain, characterized in that, The method, applicable to vehicles equipped with air deflectors, wherein the air deflector guides airflow into a cooling module, and the air deflector includes an airfoil that extends vertically beyond the air deflector, comprises: The vehicle speed and the temperature of the cooling module are obtained, and based on the vehicle speed and temperature, the airfoil extension distance is output by a trained prediction model. The extension distance is inversely proportional to the vehicle speed at the same temperature and directly proportional to the temperature at the same vehicle speed. Determine the current driving mode of the vehicle, query the distance adjustment parameters corresponding to the current driving mode, and calculate the target extension distance based on the extension distance and the distance adjustment parameters; and Generate control commands to control the current extension distance of the airfoil as the target extension distance.
2. The airfoil control method for an automotive windbreak curtain according to claim 1, characterized in that, The method further includes: Based on historical test data, a training set is determined. The training set includes data pairs constructed from vehicle speed samples and temperature samples, as well as stretching distance samples that correspond one-to-one with the data pairs. The stretching distance sample is the minimum stretching distance that enables the temperature sample to reach a safe temperature within a preset time. Based on the data pairs, the predicted elongation distance is generated from the initial model; and Using the elongation distance sample as a supervision signal, the initial model is trained for at least one round to obtain the prediction model.
3. The airfoil control method for an automotive windbreak curtain according to claim 2, characterized in that, The process of determining the training set based on historical test data includes: The vehicle speed samples and temperature samples with the same timestamp in the historical test data are associated to obtain data pairs. The duration of temperature change of the data pairs under different candidate elongation distances is queried. The duration of temperature change is the time it takes for the temperature sample to change to a safe temperature. Based on the duration of each temperature change, an elongation distance sample is determined from each of the candidate elongation distances; and A training set is constructed based on the data pairs and the elongation distance samples.
4. The airfoil control method for an automotive windbreak curtain according to claim 1, characterized in that, Before the airfoil elongation distance is output by the trained prediction model based on the vehicle speed and temperature, the process also includes: Determine the current deflection angle of the airfoil and query the prediction model that matches the current deflection angle.
5. The airfoil control method for an automotive windbreak curtain according to claim 4, characterized in that, The query for the prediction model that matches the current deflection angle includes: Determine the angle range corresponding to the current deflection angle, and query the prediction model corresponding to the angle range.
6. The airfoil control method for an automotive windbreak curtain according to claim 4, characterized in that, The generation control instructions include: Query the vehicle speed-force mapping relationship corresponding to the current deflection angle, and then query the estimated vehicle speed corresponding to the current force on the airfoil based on the vehicle speed-force mapping relationship; and A control command is generated in response to the difference between the estimated vehicle speed and the current vehicle speed being less than a difference threshold.
7. The airfoil control method for an automotive windbreak curtain according to claim 1, characterized in that, The distance adjustment parameter is negative when the current driving mode is Eco mode, positive when the current driving mode is Sport mode, and maximum when the current driving mode is Off-road mode.
8. The airfoil control method for an automotive windbreak curtain according to claim 1, characterized in that, The method further includes: Based on the current driving mode, the time interval for generating the control commands is determined.
9. The airfoil control method for an automotive windbreak curtain according to claim 1, characterized in that, The method further includes: In response to the vehicle entering a frequently used road segment, a correction parameter is determined based on the vehicle speed range corresponding to the historical average speed of the vehicle in the frequently used road segment, so as to correct the target extension distance in the frequently used road segment according to the correction parameter. The frequently used road segment is a road segment with a historical number of trips greater than a preset number.
10. A computer program product, characterized in that, The system includes a computer program that, when executed by a processor, implements a method for controlling the airfoil of an automotive windbreak curtain according to any one of claims 1-9.