Vehicle spoiler control method, device and electronic equipment

Abstract

This application relates to the field of vehicle technology. Addressing the problem of how to adapt a vehicle's rear wing to its driving state, this application provides a vehicle rear wing control method, device, and electronic device. The method of this application is applied to a vehicle, which includes a rear wing. The method includes: acquiring vehicle driving data; predicting the future aerodynamic performance requirements and aerodynamic performance state of the vehicle based on the driving data; calculating rear wing control parameters based on the future aerodynamic performance requirements and aerodynamic performance state, with the future aerodynamic performance of the vehicle as the optimization target; and generating corresponding rear wing control commands based on the rear wing control parameters, the rear wing control commands being used to control the rear wing. According to the method of this application, based on predictive control, the rear wing state responds in advance to changes in vehicle state, which can improve the vehicle's driving performance.

Description

Technical Field

[0001] This application relates to the field of vehicles, and in particular to a method, apparatus and electronic device for controlling a vehicle's rear wing. Background Technology

[0002] A vehicle rear wing, also known as a spoiler or aerodynamic wing, is a protruding device installed on the rear of a vehicle's trunk lid or roof, and is part of an aerodynamic kit. Its core function is to change the direction of airflow, generating downward pressure to counteract the lift generated when the vehicle is traveling at high speeds, thereby improving tire grip and driving stability, while also optimizing the drag coefficient and indirectly saving fuel.

[0003] Since the driving state of a vehicle is not constant, a vehicle rear wing control method is needed to make the vehicle rear wing adapt to the vehicle's driving state. Summary of the Invention

[0004] To address the problem of how to adapt a vehicle's rear wing to its driving conditions, this application provides a vehicle rear wing control method, device, and electronic device. This application also provides a computer program product and a computer-readable storage medium.

[0005] The embodiments of this application adopt the following technical solutions:

[0006] In a first aspect, this application provides a vehicle rear wing control method, the method being applied to a vehicle, the vehicle including a rear wing, the method comprising:

[0007] Obtain vehicle driving data;

[0008] Based on vehicle driving data, predict the future time-domain aerodynamic performance requirements and aerodynamic performance status of the vehicle.

[0009] With the aerodynamic performance of future time-domain vehicles as the optimization target, the tail wing control parameters are calculated based on aerodynamic performance requirements and aerodynamic performance status.

[0010] The tail fin control command is generated based on the tail fin control parameters, and the tail fin control command is used to control the tail fin.

[0011] The method according to the embodiments of this application can achieve dynamic optimization of the tail fin's aerodynamic performance across the entire operating range.

[0012] According to the method in the embodiments of this application, predictive control enables the tail wing to respond in advance to changes in vehicle state, thereby improving the vehicle's driving performance.

[0013] In one implementation of the first aspect, the vehicle driving data includes driver operation data and vehicle status data;

[0014] Based on vehicle driving data, predict future time-domain aerodynamic performance requirements and aerodynamic performance status of the vehicle, including:

[0015] A fuzzy neural network model is used to map driver operation data and vehicle status data into performance requirement vectors.

[0016] In one implementation of the first aspect, based on vehicle driving data, the aerodynamic performance requirements and aerodynamic performance status of the vehicle in the future time domain are predicted, including:

[0017] Predicting aerodynamic performance based on vehicle dynamics models, where the vehicle dynamics model combines a two-degree-of-freedom bicycle model with an aerodynamic model.

[0018] In one implementation of the first aspect, the aerodynamic performance of the future time-domain vehicle is taken as the optimization objective. Based on the aerodynamic performance requirements and aerodynamic performance status, the tail wing control parameters are calculated, including:

[0019] In each control cycle, the optimization problem is calculated using a linear time-varying model predictive control algorithm to obtain the tail fin control parameter sequence. The first tail fin control parameter in the tail fin control parameter sequence is taken as the tail fin control parameter.

[0020] In one implementation of the first aspect, the vehicle includes an air blowing system for applying air blowing to the surface of the tail fin;

[0021] The method also includes:

[0022] Apply airflow to the tail fin surface to delay flow separation and / or suppress vortices.

[0023] In one implementation of the first aspect, the vehicle also includes a surface flow sensor for measuring the airflow velocity close to the surface of the tail fin.

[0024] The method also includes:

[0025] The starting point of flow separation is identified based on the measurement results from the surface flow sensor;

[0026] The blowing momentum coefficient is calculated based on the starting point of flow separation, and the blowing momentum coefficient is used to control the blowing system.

[0027] In one implementation of the first aspect, the vehicle includes a pressure sensor array for measuring the surface pressure of the tail fin;

[0028] The method also includes:

[0029] Calculate the actual downforce distribution and pressure center location generated by the tail fin based on the surface pressure of the tail fin.

[0030] Adjust the tail fin control commands based on the actual downforce distribution and pressure center position generated by the tail fin, and / or adjust the model parameters of the calculation model used to calculate the tail fin control parameters.

[0031] Secondly, this application provides an electronic device, which includes a memory and a processor;

[0032] The processor executes instructions stored in memory to cause the electronic device to perform the method as described in the first aspect.

[0033] Thirdly, this application provides a computer program product containing instructions that, when executed by a computing device system, cause a cluster of computing devices to perform the method as described in the first aspect.

[0034] Fourthly, this application provides a computer-readable storage medium including computer program instructions, which, when executed by a computer system, cause the computer system to perform the method as described in the first aspect. Attached Figure Description

[0035] Figure 1 The diagram shown is a schematic diagram of an electronic device structure according to an embodiment of this application;

[0036] Figure 2 The diagram shown is a structural schematic of a vehicle rear wing control device according to an embodiment of this application;

[0037] Figure 3 The diagram shown is a schematic flowchart of a vehicle rear wing control method according to an embodiment of this application.

[0038] Figure 4 This is a schematic diagram of the vehicle rear wing control process according to an embodiment of this application;

[0039] Figure 5 This is a schematic diagram of an electronic device structure according to an embodiment of this application. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] The terminology used in the implementation section of this application is for the purpose of explaining specific embodiments of this application only, and is not intended to limit this application.

[0042] To address the issue of how to adapt the vehicle's rear wing to the vehicle's driving conditions, a feasible technical solution is to control the vehicle's rear wing according to the vehicle's current driving speed, adjusting the geometry and / or structure of the rear wing so that the disturbance of airflow by the rear wing adapts to the vehicle's current driving speed.

[0043] However, adjusting the vehicle's rear spoiler based on a fixed speed threshold triggering mechanism lacks adaptability to complex driving conditions, and the compatibility between the vehicle's rear spoiler and the vehicle's driving state is not ideal.

[0044] To address the above issues, this application provides a vehicle rear wing control method in one embodiment. In this method, vehicle driving data is collected; based on the vehicle's aerodynamic coupling dynamics model, the future time-domain aerodynamic performance of the vehicle is predicted according to the driving data; rear wing control parameters are calculated using the future time-domain aerodynamic performance as the optimization objective; and corresponding rear wing control commands are generated based on the calculated rear wing control parameters.

[0045] The methods described in this application are applied to electronic devices. This application does not specifically limit the electronic devices to which the methods of this application are applied. For example, the electronic device may be a vehicle (the vehicle's infotainment system), a local device installed in the vehicle to provide energy management strategies for the vehicle, or a remote device (e.g., a cloud server) remotely connected to the vehicle to provide energy management strategies for the vehicle.

[0046] Specifically, the method provided in any embodiment of this application can be applied to electronic devices such as in-vehicle systems, mobile phones, tablet computers, personal digital assistants (PDAs), desktop computers, laptop computers, ultra-mobile personal computers (UMPCs), handheld computers, and netbooks. This application does not impose any special restrictions on the specific form of the aforementioned electronic devices.

[0047] Figure 1 The diagram shown is a schematic diagram of an electronic device structure according to an embodiment of this application.

[0048] The method provided in any embodiment of this application can be applied to... Figure 1 In the electronic device 100 shown.

[0049] Electronic device 100 may include processor 110, external memory interface 120, internal memory 121, interface 130, power management module 141, antenna 1, communication module 150, audio module 170, sensor module 180, camera 193, display screen 194, etc.

[0050] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0051] The processor 110 may be an on-chip device (SOC) or other architecture. The processor 110 may include a central processing unit (CPU) and may further include other types of processors.

[0052] Processor 110 may include one or more processing units. For example, the processing units of processor 110 may include any combination of one or more of the following: Central Processing Unit (CPU), Digital Signal Processor (DSP), Microcontroller Unit (MCU), Digital Signal Processor (DSP), Application Processor (AP), Graphics Processing Unit (GPU), Neural-network Processing Units (NPU), Image Signal Processing (ISP), Modem Processor, Controller, Video Codec, and Baseband Processor. Processing units of processor 110 may also include other processing units besides those described above.

[0053] In processor 110, different processing units can be independent devices or integrated into one or more processors. The controller can generate operation control signals based on the instruction opcode and timing signals to control instruction fetching and execution.

[0054] The processor may also include necessary hardware accelerators or logic processing hardware circuitry, such as an ASIC, or one or more integrated circuits for controlling the execution of the program in this application. Furthermore, the processor may have the capability to operate one or more software programs, which may be stored in a storage medium.

[0055] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0056] In some embodiments, processor 110 may include one or more interfaces.

[0057] The interfaces of processor 110 may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0058] Interface 130 is used to provide an interface for external access of electronic device 100 to processor 110.

[0059] In one embodiment, interface 130 is an interface of processor 110. In another embodiment, interface 130 includes an interface conversion module for converting one type of interface to another. One end of the interface conversion module provides external access for electronic device 100, and the other end of the interface conversion module is connected to the interface of processor 110.

[0060] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may also employ different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0061] Internal memory 121 can be used to store computer executable program code, which includes instructions.

[0062] The internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function (such as sound playback, image playback, etc.). The data storage area may store data generated during the use of the electronic device 100 (such as vehicle driving data, navigation data, etc.).

[0063] Internal memory 121 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc. Processor 110 executes various functional applications and data processing of electronic device 100 by running instructions stored in internal memory 121 and / or instructions stored in memory disposed in the processor.

[0064] The internal memory 121 may be a read-only memory (ROM), other types of static storage devices that can store static information and instructions, random access memory (RAM), or other types of dynamic storage devices that can store information and instructions. It may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), a magnetic disk storage medium, or other magnetic storage devices. Alternatively, it may be any computer-readable medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer.

[0065] Processor 110 and internal memory 121 can be combined into a single processing device, or more commonly they are separate components.

[0066] The external storage interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, music, video, and other files can be saved on the external memory card.

[0067] The power management module 141 manages the power supply to various components of the electronic device 100. In one embodiment, the power management module 141 includes a charging management module and a battery. The charging management module receives charging input from a charger (e.g., a charging station).

[0068] The power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle count, and battery health status (leakage current, impedance). In some other embodiments, the power management module 141 may also be located within the processor 110. In other embodiments, the power management module 141 and the charging management module 140 may also be located in the same device.

[0069] The wireless communication function of electronic device 100 can be realized through antenna 1, communication module 150, etc.

[0070] Antenna 1 is used to transmit and receive electromagnetic wave signals. Antenna 1 may include one or more physical antennas. Each antenna in electronic device 100 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization.

[0071] The communication module 150 may be one or more devices integrating at least one communication processing module. The communication module 150 can provide wireless communication solutions, including 2G / 3G / 4G / 5G, for use on the electronic device 100. The communication module 150 can also provide wireless communication solutions, including wireless local area networks (WLANs) (such as Wireless Fidelity (Wi-Fi) networks), Bluetooth (BT), Global Navigation Satellite System (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies, for use on the electronic device 100.

[0072] The display screen 194 is used to display images, videos, etc. In some embodiments, the electronic device 100 may include one or N display screens 194, where N is a positive integer greater than 1.

[0073] Camera 193 is used to capture still images or videos. In some embodiments, electronic device 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0074] The audio module 170 is used to convert digital audio information into analog audio signals for output, and also to convert analog audio input into digital audio signals. The audio module 170 can also be used for encoding and decoding audio signals. In some embodiments, the audio module 170 may be located in the processor 110, or some functional modules of the audio module 170 may be located in the processor 110.

[0075] In some embodiments, the electronic device 100 further includes a speaker, a microphone, etc. The electronic device 100 can implement audio functions through the audio module 170, the speaker, the microphone, and an application processor, such as music playback and voice control.

[0076] The sensor module 180 may include pressure sensors, gyroscope sensors, barometric pressure sensors, magnetic sensors, accelerometers, distance sensors, proximity sensors, fingerprint sensors, temperature sensors, touch sensors, ambient light sensors, bone conduction sensors, etc.

[0077] In some embodiments, the electronic device 100 also includes buttons, indicators, etc.

[0078] For example, buttons include vehicle start button, volume buttons, air conditioning control buttons, etc. Buttons can be mechanical buttons or touch-sensitive buttons. Electronic device 100 can receive button input and generate key signal inputs related to user settings and function control of electronic device 100.

[0079] Indicators can be indicator lights, used to indicate vehicle status such as speed, charging status, and battery level; they can also be used to indicate messages such as fault alarms and low battery alarms.

[0080] In addition to the aforementioned components, the electronic device runs an operating system. For example, iOS. ® Operating system, Android ® Operating system, Windows ® Operating systems, such as vehicle operating systems, can be used to install and run applications. The software system of electronic device 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture.

[0081] Furthermore, in one embodiment, the method of this application embodiment can be applied to an electronic device. This electronic device may refer in whole or in part to electronic device 100.

[0082] In another embodiment, the method of this application can be applied to a system composed of multiple electronic devices, where each electronic device in the system executes a portion of the method steps. Any electronic device in the system can refer to electronic device 100 in whole or in part.

[0083] In order to implement the vehicle rear wing control method proposed in the embodiments of this application, an embodiment of this application also proposes a vehicle rear wing control device.

[0084] Figure 2 The diagram shown is a structural schematic of a vehicle tail wing control device according to an embodiment of this application.

[0085] like Figure 2 As shown, the vehicle tail wing control device 200 includes a data acquisition module 201 and an instruction calculation module 202.

[0086] The data acquisition module 201 is used to acquire vehicle driving data.

[0087] The instruction calculation module 202 is used to generate tail control instructions for controlling the tail fin.

[0088] The vehicle rear wing control device of this application embodiment is applied to an electronic device, which can refer to electronic device 100.

[0089] This application does not limit the specific method of implementing the vehicle tail wing control device. Those skilled in the art can design the implementation method of the device according to the actual situation.

[0090] For example, in one embodiment, the device is installed on the electronic device in hardware (e.g., a functional chip). In another embodiment, the device is installed in the operating system of the electronic device as software code. Yet another embodiment, the device is installed on the electronic device as a combination of hardware and software.

[0091] Furthermore, in one embodiment, the device is mounted on an electronic device.

[0092] In another embodiment, the device is mounted on multiple electronic devices, which together form a complete device structure. Different electronic devices may install the same functional modules, or different electronic devices may install different functional modules.

[0093] In the description of the embodiments of this application, for the sake of convenience, the device is described by dividing it into various modules according to its functions. The division of each module is only a logical functional division. When implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware.

[0094] Specifically, the apparatus proposed in this application can be fully or partially integrated onto a single physical entity (e.g., a GPU or other type of processor), or it can be physically separated. These modules can be implemented entirely in software via processing element calls; entirely in hardware; or some modules can be implemented in software via processing element calls, while others are implemented in hardware. For example, the detection module can be a separate processing element or integrated into a chip in an electronic device. The implementation of other modules is similar. Furthermore, these modules can be fully or partially integrated together or implemented independently. During implementation, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0095] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs). Alternatively, these modules can be integrated together as a system-on-a-chip (SOC).

[0096] Specifically, in one embodiment, the instruction calculation module 202 is implemented in the vehicle's controller (e.g., an electronic control unit (ECU)).

[0097] Figure 3 The diagram shown is a schematic flowchart of a vehicle rear wing control method according to an embodiment of this application.

[0098] In one embodiment, the electronic device performs as follows Figure 3 The following process is shown to generate rear wing control commands for controlling the vehicle's rear wing.

[0099] S300, acquires vehicle driving data.

[0100] In one embodiment, the electronic device is equipped with Figure 2 The vehicle rear wing control device 200 shown is executed by the data acquisition module 201 in step S300.

[0101] S301, based on the vehicle's aerodynamic coupling dynamics model, predicts the future time-domain aerodynamic performance requirements and aerodynamic performance status of the vehicle based on vehicle driving data; takes the future time-domain aerodynamic performance as the optimization target, calculates the tail wing control parameters based on the predicted aerodynamic performance requirements and aerodynamic performance status; and generates corresponding tail wing control commands based on the calculated tail wing control parameters.

[0102] In one embodiment, the electronic device is equipped with Figure 2 The vehicle rear wing control device 200 shown is executed by the command calculation module 202 in step S300.

[0103] The method according to the embodiments of this application can achieve dynamic optimization of the tail fin's aerodynamic performance across the entire operating range.

[0104] According to the method in the embodiments of this application, predictive control enables the tail wing to respond in advance to changes in vehicle state, thereby improving the vehicle's driving performance.

[0105] In one embodiment, the vehicle driving data acquired in S300 includes driver operation data and vehicle status data. In S301, the driver operation data and vehicle status data are mapped into a performance requirement vector to obtain the vehicle's aerodynamic performance requirements.

[0106] The method according to the embodiments of this application maps performance demand vectors based on driver operation data and vehicle status data, and has good adaptability to complex environments and driver operations.

[0107] Specifically, in one embodiment, a fuzzy neural network model is used to map driver operation data and vehicle status data into a performance requirement vector based on fuzzy logic.

[0108] Specifically, the inputs to the fuzzy neural network model are driver operation data and vehicle state data, including: steering wheel angle change rate, brake pedal force gradient, accelerator pedal gradient, and vehicle speed.

[0109] The output of the fuzzy neural network model is a three-dimensional performance requirement vector, the contents of which are defined by the following formula 1:

[0110]

[0111] In formula 1, This indicates downward pressure demand. This is expressed as drag reduction requirement. This indicates a need for stability.

[0112] In Formula 1, 0≤ ≤1, 0≤ ≤1, 0≤ ≤1.

[0113] Specifically, in one embodiment, the fuzzy rule for determining the vector of Formula 1 includes:

[0114] Downforce demand when emergency braking is detected and To maximize, set and A relatively high value (e.g., 1). For example, a relatively low value (e.g., 0); for example, the performance requirement vector at this point. ;

[0115] When an emergency obstacle avoidance is detected, set and For relatively high values, For example, the performance requirement vector at this point is a relatively low value; ;

[0116] When in high-speed cruise mode and cornering at high speed, set For relatively high values, For relatively low values, The value is between the first two; for example, the performance requirement vector at this point. ;

[0117] When in track mode and cornering at high speeds, downforce demand is maximized while maintaining stability. (Settings are needed.) and For relatively high values, For example, the performance requirement vector at this point is a relatively low value; .

[0118] In one embodiment, in S301, the aerodynamic performance state of the vehicle in the future time domain (e.g., 2 seconds later) is predicted based on the vehicle dynamics model. Specifically, a hierarchical intelligent control architecture runs within the ECU, employing a model predictive control framework to run hierarchical control algorithms.

[0119] In one embodiment, the vehicle dynamics model includes a simplified two-degree-of-freedom bicycle model combined with an aerodynamic model.

[0120] Specifically, the two-degree-of-freedom bicycle model includes:

[0121] Lateral dynamics: m a_y = F_yf + F_yr + F_aero_lat; (Formula 2)

[0122] Yaw dynamics: I_z d²ψ / dt² = l_f F_yf - l_r F_yr + M_z_aero (Formula 3)

[0123] In formulas 2 and 3:

[0124] m is the mass; a_y is the lateral acceleration; F_yf and F_yr are the lateral forces on the front and rear axes, respectively; I_z is the yaw moment of inertia; ψ is the yaw angle; l_f and l_r are the distances from the center of mass to the front / rear axis.

[0125] Aerodynamic models that use the tail fin as the primary contributor include:

[0126] Lateral aerodynamic force: F_aero_lat = 0.5 ρ V² A C_Y(β, θ); (Formula 4)

[0127] Downforce: F_downforce = 0.5 ρ V² A C_L(θ, Re, BL_Status); (Formula 5)

[0128] Yaw moment: M_z_aero = 0.5 ρ V² A l_w C_N(β, θ_asym). (Formula 6)

[0129] In Equations 4-6: ρ is air density; V is vehicle speed; A is reference area; C_Y, C_L, and C_N are aerodynamic coefficients, which are functions of sideslip angle β, tail fin angle of attack θ, Reynolds number Re, boundary layer state BL_Status, and left and right asymmetric angle of attack θ_asym.

[0130] In one embodiment, a fluid dynamics simulation data table containing aerodynamic coefficients is pre-calculated and obtained, and the fluid dynamics simulation data table is saved to an electronic device.

[0131] In one embodiment, a rolling optimization strategy is adopted to calculate and obtain optimized tail wing control parameters based on the future time-domain aerodynamic performance requirements of the vehicle and the predicted aerodynamic performance state.

[0132] Specifically, in one embodiment, in each control cycle k, the following finite-time optimization problem is solved:

[0133] min J = Σ [ W_df (F_df_desired - F_df_predicted(k+i))²

[0134] + W_drag (C_d_predicted(k+i))²

[0135] + W_stab (β_predicted(k+i))²

[0136] + W_control Δθ(k+i)² ]. (Formula 7)

[0137] In formula 7:

[0138] F_df_desired is the expected value of the downforce (F_downforce), which is determined by the performance requirement vector R;

[0139] F_df_predicted is the predicted value of downforce (F_downforce);

[0140] W_df, W_drag, W_stab, and W_control are weighting coefficients that are dynamically adjusted according to the performance requirement vector R.

[0141] The constraints of Formula 7 are:

[0142] Angle of attack range: θ_min ≤ θ(k+i) ≤ θ_max;

[0143] The rate of change of angle of attack is limited by: |Δθ(k+i)| ≤ Δθ_max.

[0144] The optimization variable in Formula 7 is the future tail control parameter sequence [θ(k), θ(k+1), ..., θ(k+N)].

[0145] Solve the optimization problem of Equation 7 to obtain the optimal tail fin control parameter sequence. Generate tail fin control commands for controlling the tail fin based on the first control parameter θ(k) in the tail fin control parameter sequence.

[0146] Specifically, in one embodiment, a linear time-varying model predictive control (MPC) algorithm is used to solve the optimization problem in Equation 7. Specifically, the aerodynamic coefficients are linearized at the current operating point, and then a sequential quadratic programming algorithm is used to solve the optimization problem.

[0147] According to the method of the embodiments of this application, the MPC framework is used to enable the tail wing to "prepare for a rainy day", such as adjusting in advance before entering a curve, so as to achieve a smooth transition and optimal global performance.

[0148] In one embodiment, the vehicle's tail wing includes: a variable camber main wing surface, independently extendable / deflectable ailerons, and an actuator for adjusting the main wing surface and the ailerons. The tail wing control command generated in S301 is used to control the actuator to adjust the main wing surface and / or the ailerons so that the tail wing meets the tail wing control parameters.

[0149] Specifically, in one embodiment, the main airfoil adopts a variable camber design, using multiple internal micro servo motors to drive a linkage mechanism, achieving continuous and smooth changes in the airfoil's mid-curvature. Specifically, the main airfoil employs a distributed micro servo motor drive mechanism and a shape memory alloy skeleton, enabling continuous and smooth changes in the airfoil's mid-curvature, with a camber adjustment range of 1.2 to 1.8 times the base camber.

[0150] The ailerons consist of ailerons on either side of the main wing surface. The ailerons can deflect and extend independently. Deflection adjusts the local angle of attack, while extension increases the effective span and lift coefficient when needed. Specifically, the ailerons have independent deflection and extension degrees of freedom, with an extension range of 0-150mm and a deflection range of -15° to +30°. The left and right ailerons can move asymmetrically to generate a corrective yaw moment.

[0151] Specifically, in one embodiment, the control parameter θ in Formula 7 includes the tail wing angle of attack α_w, the wing camber δ_f, and the difference in angle of attack between the left and right ailerons Δδ_f.

[0152] Furthermore, in S301, tail wing control parameters are calculated based on the desired aerodynamic effect produced by the tail wing, and tail wing control commands are generated based on the calculated tail wing control parameters, so that the tail wing is controlled according to the tail wing control commands to produce the desired aerodynamic effect.

[0153] However, in actual vehicle driving scenarios, due to the unpredictability of actual airflow, controlling the tail wing according to the tail wing control commands may not necessarily produce the expected aerodynamic effect.

[0154] To address the aforementioned issues, in one embodiment, a global perception network is configured in the vehicle. The global perception network transmits data based on standard vehicle bus data (CAN). The global perception network is connected to a pressure sensor array configured on the rear wing.

[0155] The pressure sensor array is distributed at key locations on the upper and lower surfaces of the tail fin to measure the surface pressure of the tail fin in real time, thereby calculating the actual downforce distribution and pressure center location generated by the tail fin. By integrating these pressure data, the actual downforce, lift coefficient, and pressure center location generated by the tail fin can be calculated.

[0156] During vehicle operation, the control commands for the rear wing can be dynamically adjusted based on feedback from the pressure sensor array to produce the desired aerodynamic effect.

[0157] Furthermore, in one embodiment, based on feedback from the pressure sensor array, the difference between the expected aerodynamic effect corresponding to the tail fin control parameters and the actual aerodynamic effect produced by the tail fin is identified, and the model parameters of the calculation model used to calculate the tail fin control parameters are adjusted according to the difference, thereby optimizing the calculation effect of the calculation model.

[0158] According to the method in the embodiments of this application, real-time measurement and closed-loop control of downforce are achieved through a pressure sensor array, ensuring that aerodynamic performance always matches the design intent. Figure 1 To.

[0159] Furthermore, in one embodiment, the global perception network also accesses information from front-facing vision / radar sensors to obtain predictive information such as the curvature and slope of the road ahead, assisting in predicting the aerodynamic performance requirements and aerodynamic performance status of the vehicle in the future time domain.

[0160] According to the method of the embodiments of this application, crosswind compensation is performed in combination with predictive road information, enabling the tail wing control to cope with comprehensive and complex operating conditions.

[0161] Furthermore, in actual vehicle driving scenarios, unexpected disturbances exist in the airflow over the rear wing surface, including flow separation and / or vortices. The presence of these unexpected disturbances can prevent the rear wing from producing the expected aerodynamic effects.

[0162] Therefore, in one embodiment, the vehicle rear wing control method further includes applying airflow to the surface of the rear wing to suppress unintended disturbances in the airflow over the rear wing surface.

[0163] Specifically, in one embodiment, an air blowing system is configured on the vehicle. The air blowing system is used to apply pulsed or continuous airflow to a specific area of ​​the tail fin surface to address unexpected disturbances in airflow over the tail fin surface. Specifically, in one embodiment, the air blowing system includes a high-speed solenoid valve controlled by an ECU and a miniature air pump to achieve the air blowing.

[0164] Specifically, in one embodiment, the blowing hole array is used to blow air into the high-pressure gradient region on the upper surface of the tail fin, injecting energy into the boundary layer so that the airflow can better adhere to the fin surface, thereby maintaining the attached flow at a larger angle of attack, significantly improving the stall angle of attack critical value and the maximum lift coefficient, thereby delaying flow separation.

[0165] In one embodiment, the air-blowing array is used to perform targeted air blowing in the wingtip region of the tail fin to control the generation and development of wingtip vortices, reduce induced drag, and thus suppress vortices.

[0166] Specifically, regarding BL_Status in Equation 5, the constraint condition in Equation 7 also includes: BL_Status(k+i) == Attached (the boundary layer state is a non-separated flow state). Air blowing control ensures non-separation of the flow, thus maintaining BL_Status(k+i) == Attached.

[0167] Specifically, in one embodiment, the blowing system includes an array of blowing holes distributed on the leading edge and upper surface of the wing, with a blowing hole diameter of 0.2-0.5 mm and an adjustable air source pressure of 2-8 bar, supporting both pulse and continuous blowing modes.

[0168] In one embodiment, the parameters of the air blowing system are:

[0169] Air pore array: 20-30 at the leading edge, 40-60 micropores on the upper surface;

[0170] - Aperture size: 0.2-0.5mm;

[0171] - Gas source pressure: Adjustable from 2 to 8 bar;

[0172] - Control method: Independent pulse / continuous blowing in zones.

[0173] According to the method of the embodiments of this application, active flow control of the tail fin surface is achieved through the blowing system, which can achieve higher downforce or lower drag at the same downforce without changing the external environment.

[0174] In one embodiment, the global sensing network further includes a surface flow sensor that measures the airflow velocity close to the tail fin surface to detect the boundary layer state and identify the initiation point of flow separation. Based on feedback from the surface flow sensor, flow separation is delayed and / or eddies are suppressed by adjusting the blowing momentum coefficient of the blowing system.

[0175] Specifically, if the surface flow sensor detects that the separation initiation point has moved forward, it will initiate air blowing in the corresponding area.

[0176] Specifically, the blowing process involves deriving the opening command (pulse width modulation signal) of the blowing valve based on the corresponding blowing momentum coefficient.

[0177] The blowing momentum coefficient C_μ is adjusted by a proportional-integral-derivative (PID) controller:

[0178] C_μ(t) = K_p e(t) + K_i ∫e(t)dt + K_d de(t) / dt. (Formula 8)

[0179] In Formula 8: the error signal e(t) is the deviation between the desired separation point position (S_desired) and the actual measured separation point position (S_measured), that is:

[0180] e(t) = S_desired - S_measured. (Formula 9)

[0181] Figure 4 This is a schematic diagram of the vehicle tail wing control process according to an embodiment of this application.

[0182] In one embodiment, the vehicle performs as follows Figure 4 The following process is shown to achieve vehicle rear wing control.

[0183] S400, the initialization phase, includes: sensor calibration and self-test; pneumatic database loading; and control parameter initialization.

[0184] S401, Real-time control loop phase (e.g., with a period of 10ms).

[0185] Step 1: Data acquisition and preprocessing, including:

[0186] Collect all sensor data, such as driver operation data and vehicle status data;

[0187] Data validity testing and filtering.

[0188] Step 2: Vehicle state estimation and driver intent recognition, including:

[0189] Vehicle state estimation, for example, processing vehicle state data based on Kalman filtering to estimate vehicle state;

[0190] Driver intent recognition, for example, recognizing driver intent based on driver operation data using a fuzzy neural network;

[0191] Performance requirement vector calculation includes calculating the performance requirement vector based on vehicle status and driver intent.

[0192] Step 3: Model predictive control, including:

[0193] Current state linearization includes linearizing the aerodynamic coefficients at the current operating point;

[0194] Predicting time-domain states, for example, predicting the future time-domain aerodynamic performance state of a vehicle based on Equation 2-6;

[0195] Optimize the problem-solving process, for example, by solving Equation 7.

[0196] Control commands are generated.

[0197] Step 4: Breathing control, including:

[0198] Boundary layer condition monitoring, for example, using surface flow sensors to identify the starting point of flow separation;

[0199] Decisions on blowing strategies, for example, calculating the blowing momentum coefficient based on formulas 8 and 9;

[0200] Executor instruction output

[0201] Step 5: Execution and feedback, including:

[0202] Tail wing surface shape adjustment;

[0203] Real-time performance monitoring, for example, using a pressure sensor array to monitor the pressure on the tail fin surface;

[0204] Model parameter correction, for example, based on the detection results of the tail wing surface pressure, identify the deviation between the expected dynamic effect and the actual dynamic effect of tail wing control, and adjust the model parameters of the calculation model in Step 2 and Step 3 according to the deviation.

[0205] The following describes the implementation process of a vehicle rear wing control method according to an embodiment of this application, using a specific vehicle driving scenario as an example.

[0206] In a vehicle driving scenario, when the vehicle is traveling at 120 km / h in a straight line on a highway and the driving mode is "Comfort", the rear wing is at its minimum angle of attack (5°) to reduce wind resistance.

[0207] When the vehicle's radar system and camera detect that the vehicle in front has suddenly decelerated and is undergoing emergency braking, the emergency braking signal of the vehicle in front is transmitted to the vehicle controller (ECU) via the CAN bus.

[0208] The vehicle's sensors detect and collect information in real time, including road surface information, vehicle speed, steering wheel angle, brake pedal pressure signal, yaw angle signal, lateral driving degree, obstacle information, and driver intention. The vehicle's sensors update and detect information every 10ms.

[0209] When the driver applies the brakes in response to the emergency braking of the vehicle ahead, the brake pedal pressure sensor detects that the brake pressure increases from 0 bar to 100 bar within 50 ms (emergency braking); the steering wheel sensor detects that the steering wheel turns 60° to the left within 100 ms (obstacle avoidance); the vehicle speed sensor detects that the vehicle speed drops rapidly from 120 km / h; the yaw rate sensor detects that the vehicle begins to generate yaw rate; and the lateral acceleration sensor detects lateral acceleration.

[0210] After detecting the above signals, the signals are transmitted to the ECU via the CAN bus. The ECU then obtains the performance requirement vector based on the received signals.

[0211] Specifically, based on the detected braking pressure gradient (dP_brake / dt=100 / 0.05=2000bar / s, belonging to VL), steering wheel angle gradient (dδ / dt=600° / s, belonging to VL), and current speed (120km / h, belonging to H), according to the fuzzy rule, it is determined to be an emergency obstacle avoidance and emergency braking. Therefore, the performance requirement vector obtained by the ECU is R=[0.95,0.0,1.0]. T This means requiring maximum downforce (to improve braking performance and lane change stability), disregarding resistance, and demanding the highest stability.

[0212] The ECU calculates the optimal tail wing control parameters based on the performance demand vector.

[0213] Specifically, based on the vehicle's current longitudinal velocity u=33.3m / s, lateral acceleration of 0, and yaw angle r=0, a combination of bicycle and aerodynamic models is used to predict the state in the next 2 seconds (Np=20, control period 0.1s). Simultaneously, under the constraint conditions, the objective function J is minimized. The weights in the priority objective function are set according to the R vector, where W1=1.0 (downforce tracking), W2=0.0 (drag negligible), W3=1.0 (stability), and W4=1.0 (yaw tracking). The constraint conditions are: the angle of attack changes from 5° to 25°, and the rate of change is limited to 60° per second.

[0214] By solving the optimization problem, the tail fin control parameters are obtained as follows:

[0215] First control interval: angle of attack increased from 5° to 20° (maximizing downforce), while the ailerons are adjusted to be asymmetrical: left aileron angle of attack 18°, right aileron 22° (generating an additional positive yaw moment to assist steering).

[0216] The ECU generates corresponding tail wing control commands based on the tail wing control parameters. The ECU sends the tail wing control commands to the tail wing actuators. Upon receiving the tail wing control commands, the actuators begin to execute the corresponding actions. For example, the main wing angle of attack is adjusted from 5° to 20° within 100ms (meeting the maximum rate of change limit). The asymmetrical adjustment of the left and right ailerons is completed within 100ms.

[0217] Furthermore, when the pressure sensor array and flow sensor detect a tendency for boundary layer separation on the upper surface of the tail fin at an angle of attack of 20°, the ECU controls the blowing system to blow air onto the leading edge of the tail fin with a blowing momentum coefficient C_u=0.01, ensuring the flow remains attached and preventing stall at the 20° angle of attack. The blowing system is activated, and air begins to blow through the micro-holes at the leading edge.

[0218] The vehicle's sensors monitor the vehicle and rear wing status in real time for aerodynamic effect and rear wing control tracking. At this time, it is detected that the vehicle's braking distance has shortened, the yaw rate during lane changes follows an ideal model, and the sideslip angle remains within 2°. The pressure sensor array measures that the actual downforce increases from 800N to 3500N. When it is detected that the driver has completed obstacle avoidance, returned to the original lane, released the brake pedal, and straightened the steering wheel, and the driver's operation has returned to smoothness, the performance demand vector is adjusted to R=[0.3,0.7,0.5]T; the ECU gradually reduces the rear wing angle of attack to 10° based on the performance demand vector (balancing downforce and drag).

[0219] An embodiment of this application also proposes an electronic device. This electronic device is used to execute the method flow or part of the method flow described in the embodiments of this application. This electronic device is a terminal device, base station device, or server device as described in the embodiments of this specification.

[0220] Figure 5 This is a schematic diagram of an electronic device structure according to an embodiment of this application.

[0221] like Figure 5 As shown, the electronic device 2500 includes a memory 2502 for storing computer program instructions and a processor 2501 for executing the program instructions. When the computer program instructions are executed by the processor 2501, the electronic device 2500 is triggered to execute the method steps performed by the terminal device, base station device, or server device as described in the embodiments of this application.

[0222] Specifically, in one embodiment of this application, the aforementioned one or more computer programs are stored in the aforementioned memory 2502. The aforementioned one or more computer programs include instructions that, when executed by the aforementioned electronic device 2500, cause the aforementioned electronic device 2500 to perform the method steps described in the embodiments of this application.

[0223] It is understood that the structural description of the electronic device 2500 in this application does not constitute a specific limitation on the electronic device 2500. In other embodiments of this application, the electronic device 2500 may include other components besides the processor 2501 and the memory 2502.

[0224] In one embodiment, electronic device 2500 may refer to electronic device 100, wherein processor 2501 may refer to processor 110, and memory 2502 may refer to internal memory 121.

[0225] Processor 2501 and memory 2502 can be combined into a single processing device, but more commonly they are separate components.

[0226] An embodiment of this application also provides an electronic chip. This electronic chip is used to execute the method flow or part of the method flow described in the embodiments of this application.

[0227] Specifically, the electronic chip includes a processor for executing program instructions. When the computer program instructions are executed by the processor, the electronic chip is triggered to perform the steps described in the embodiments of this application. The processor of the electronic chip can refer to the processor of the above-described electronic device.

[0228] Optionally, the devices, apparatuses, and modules described in the embodiments of this application may be implemented by computer chips or physical entities, or by products with certain functions.

[0229] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0230] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, 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 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, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0231] Specifically, one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when run on a computer, causes the computer to execute the method provided in the embodiment of this application.

[0232] An embodiment of this application also provides a computer program product, which includes a computer program that, when run on a computer, causes the computer to perform the method provided in the embodiment of this application.

[0233] The embodiments described in this application are described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0234] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0235] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0236] It should also be noted that in the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0237] In this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0238] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0239] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0240] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments of this application can be implemented using electronic hardware, computer software, or a combination of electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0241] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0242] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method of controlling a vehicle spoiler, characterized by, The method is applied to a vehicle, the vehicle including a rear wing, and the method includes: Obtain the vehicle's driving data; Based on the vehicle driving data, predict the future time-domain aerodynamic performance requirements and aerodynamic performance status of the vehicle. Taking the aerodynamic performance of the vehicle in the future time domain as the optimization target, the tail wing control parameters are calculated based on the aerodynamic performance requirements and the aerodynamic performance state. The tail fin control command is generated based on the tail fin control parameters, and the tail fin control command is used to control the tail fin.

2. The method of claim 1, wherein, The vehicle driving data includes driver operation data and vehicle status data; The step of predicting the future time-domain aerodynamic performance requirements and aerodynamic performance status of the vehicle based on the vehicle driving data includes: A fuzzy neural network model is used to map the driver operation data and the vehicle status data into a performance requirement vector.

3. The method according to claim 1 or 2, characterized in that, The step of predicting the future time-domain aerodynamic performance requirements and aerodynamic performance status of the vehicle based on the vehicle driving data includes: The aerodynamic performance state is predicted based on a vehicle dynamics model, wherein the vehicle dynamics model includes a combination of a two-degree-of-freedom bicycle model and an aerodynamic model.

4. The method according to any one of claims 1 to 3, characterized in that, The optimization objective is the aerodynamic performance of the vehicle in the future time domain. Based on the aerodynamic performance requirements and the aerodynamic performance state, the tail wing control parameters are calculated, including: In each control cycle, the optimization problem is calculated using a linear time-varying model predictive control algorithm to obtain the tail fin control parameter sequence, and the first tail fin control parameter in the tail fin control parameter sequence is taken as the tail fin control parameter.

5. The method according to any one of claims 1-4, characterized in that, The vehicle includes an air blowing system for applying air to the surface of the tail fin; The method further includes: Air is applied to the tail fin surface to delay flow separation and / or suppress eddies.

6. The method of claim 5, wherein, The vehicle also includes a surface flow sensor for measuring the airflow velocity close to the surface of the tail fin; The method further includes: The starting point of flow separation is identified based on the measurement results of the surface flow sensor; The blowing momentum coefficient is calculated based on the starting point of the flow separation, wherein the blowing momentum coefficient is used to control the blowing system.

7. The method according to any one of claims 1-4, characterized in that, The vehicle includes a pressure sensor array for measuring the surface pressure of the tail fin. The method further includes: Calculate the actual downforce distribution and pressure center location generated by the tail fin based on the surface pressure of the tail fin; The tail fin control command is adjusted based on the actual downforce distribution and pressure center position generated by the tail fin, and / or the model parameters of the calculation model used to calculate the tail fin control parameters are adjusted.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor; The processor is configured to execute instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-7.

9. A computer program product containing instructions, characterized in that, When the instruction is executed by the computing device system, it causes the computing device cluster to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It includes computer program instructions, which, when executed by a computer system, perform the method as described in any one of claims 1-7.

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