Dynamic compensation control method, electronic equipment and vehicle

Abstract

The embodiment of the invention provides a dynamic compensation control method, electronic equipment and a vehicle, and relates to the technical field of vehicle control. The method is applied to a vehicle comprising a steer-by-wire system and comprises the steps that a vehicle door state signal and a steering wheel torque signal of the vehicle are detected; based on the vehicle door state signal and the steering wheel torque signal, whether a dynamic compensation triggering condition is met or not is determined; and controlling an actuator to output dynamic compensation force opposite to the pulling force of the steering wheel under the condition that the triggering condition is met. Based on the method, on the premise that hardware transformation is not needed, stable leveraging support can be provided for a driver, the leveraging failure risk caused by unconstrained rotation of the steering wheel in the getting-on process is reduced, and getting-on convenience and safety are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, in particular to a dynamic compensation control method, an electronic device and a vehicle. BACKGROUND

[0002] In a vehicle, a steer by wire (SBW) system transmits a steering wheel steering instruction through an electrical signal, and cancels the mechanical connection between the steering wheel and the steering gear through the system, thereby improving the design freedom and intelligent level of the vehicle.

[0003] When the driver gets on the vehicle, there may be an action of pulling the steering wheel to assist entering the cab. Since the SBW system cancels the mechanical connection between the steering wheel and the steering gear, when the steering wheel is pulled, the steering wheel cannot be subjected to a counterforce through the steering gear and the mechanical connection to offset the pulling force of the steering wheel, which may cause the driver to fail to assist and fall out of the flash injury.

[0004] Therefore, for a vehicle with a steer by wire system, a dynamic compensation control method is needed to reduce the probability of failure to assist when pulling the steering wheel while taking into account lower hardware modification. SUMMARY

[0005] The embodiments of the present application provide a dynamic compensation control method, an electronic device and a vehicle, which are used in a vehicle with a steer by wire system, and reduce the probability of failure to assist when pulling the steering wheel while taking into account lower hardware modification.

[0006] In a first aspect, the embodiments of the present application provide a dynamic compensation control method, which is applied to a vehicle including a steer by wire system, and the method comprises:

[0007] detecting a vehicle door state signal and a steering wheel torque signal;

[0008] determining whether a dynamic compensation trigger condition is met based on the vehicle door state signal and the steering wheel torque signal;

[0009] controlling an actuator to output a dynamic compensation force opposite to the steering wheel pulling force when it is determined that the trigger condition is met.

[0010] In a possible implementation, the actuator is controlled to output the dynamic compensation force opposite to the steering wheel pulling force, comprising:

[0011] calculating the size of the dynamic compensation force by using a proportional compensation model according to the size of the steering wheel pulling force;

[0012] controlling the actuator to output a holding force opposite to the steering wheel pulling force, the holding force being a sustained dynamic compensation force.

[0013] In a possible implementation, the size of the dynamic compensation force is calculated by using a proportional compensation model, including:

[0014] According to the vehicle type and / or the steering wheel size of the vehicle, the compensation coefficient in the proportional compensation model is adjusted, and the size of the dynamic compensation force is calculated according to the adjusted compensation coefficient;

[0015] The controller outputs a holding force opposite to the steering wheel pulling force, including:

[0016] The direction of the steering wheel pulling force is determined by using a sliding average algorithm, and the direction of the dynamic compensation force is determined according to the direction of the steering wheel pulling force;

[0017] According to the direction and size of the dynamic compensation force, the controller outputs a holding force opposite to the steering wheel pulling force.

[0018] In a possible implementation, the method further includes:

[0019] Obtaining a plurality of historical operation data of pulling the steering wheel;

[0020] The self-learning model is trained according to the plurality of historical operation data of pulling the steering wheel, and the self-learning model is used to output an adjustment strategy of dynamically adjusting the compensation coefficient of the proportional compensation model and the direction of the steering wheel pulling force.

[0021] In a possible implementation, the self-learning model includes a neural network and a decision tree algorithm, and the method further includes:

[0022] The pulling direction preference of the steering wheel of the vehicle is identified by using the neural network in the self-learning model;

[0023] According to the pulling direction preference, the adjustment strategy of dynamically adjusting the compensation coefficient of the proportional compensation model and the direction of the steering wheel pulling force is output by using the decision tree algorithm in the self-learning model.

[0024] In a possible implementation, based on the vehicle door state signal and the steering wheel torque signal, it is determined whether the trigger condition of the dynamic compensation is met, including:

[0025] Based on the vehicle door state signal and the steering wheel torque signal, it is determined whether the vehicle door state signal and the steering wheel torque signal simultaneously meet the trigger condition by using a preset logic gate circuit or a preset program algorithm.

[0026] In a possible implementation, the vehicle door state signal includes a vehicle door opening angle signal, and the method further includes:

[0027] The current vehicle door state is determined according to the vehicle door opening angle signal in the vehicle door state signal, and the vehicle door state includes a fully open state and a half open state;

[0028] Based on the door status, configure the pulling force threshold and / or the compensation coefficient in the proportional compensation model. The pulling force threshold is used to determine whether the steering wheel pulling force is an effective pulling force.

[0029] In one possible implementation, after controlling the actuator output to generate a dynamic compensation force opposite to the steering wheel pulling force, the method further includes:

[0030] Based on the door closing signal and / or the signal of the disappearance of pulling force, a stop command is sent to the actuator via the vehicle's controller area network bus to control the actuator to stop outputting dynamic compensation force.

[0031] Secondly, embodiments of this application provide a dynamic compensation control device applied to a vehicle including a steer-by-wire system, the device comprising:

[0032] The detection module is used to detect the vehicle door status signal and steering wheel torque signal;

[0033] The determination module is used to determine whether the triggering conditions for dynamic compensation are met based on the door status signal and the steering wheel torque signal.

[0034] The control module is used to control the actuator to output a dynamic compensation force that is opposite to the steering wheel pulling force when the triggering conditions are met.

[0035] In one possible implementation, the control module is specifically used for:

[0036] The magnitude of the dynamic compensation force is calculated using a proportional compensation model based on the magnitude of the steering wheel pulling force.

[0037] The control actuator outputs a holding force that is opposite to the steering wheel pulling force; this holding force is a continuous, dynamic compensation force.

[0038] In one possible implementation, the control module is specifically used for:

[0039] Adjust the compensation coefficients in the proportional compensation model according to the vehicle type and / or steering wheel size, and calculate the magnitude of the dynamic compensation force based on the adjusted compensation coefficients;

[0040] The direction of the steering wheel pulling force is determined by the moving average algorithm, and the direction of the dynamic compensation force is determined based on the direction of the steering wheel pulling force.

[0041] Based on the direction and magnitude of the dynamic compensation force, the actuator outputs a holding force that is opposite to the steering wheel pulling force.

[0042] In one possible implementation, the device further includes a training module, which is used for:

[0043] Acquire historical data from multiple steering wheel pull operations;

[0044] A self-learning model is trained based on historical data of multiple steering wheel pulls. The self-learning model is used to output the compensation coefficient of the dynamic adjustment proportional compensation model and the adjustment strategy for the direction of the steering wheel pulling force.

[0045] In one possible implementation, the self-learning model includes a neural network and a decision tree algorithm, and the device further includes an adjustment module for:

[0046] The neural network in the self-learning model identifies the pulling direction preference of the vehicle's steering wheel when it is pulled;

[0047] Based on the pulling direction preference, the decision tree algorithm in the self-learning model makes a decision output that dynamically adjusts the compensation coefficient of the proportional compensation model and the adjustment strategy for the direction of the steering wheel pulling force.

[0048] In one possible implementation, the determining module is specifically used for:

[0049] Based on the door status signal and the steering wheel torque signal, a preset logic gate circuit or a preset program algorithm is used to determine whether the door status signal and the steering wheel torque signal simultaneously meet the triggering conditions.

[0050] In one possible implementation, the door status signal includes a door opening angle signal, and the control module is further used for:

[0051] The current door status is determined based on the door opening angle signal in the door status signal. The door status includes fully open and half open.

[0052] Based on the door status, configure the pulling force threshold and / or the compensation coefficient in the proportional compensation model. The pulling force threshold is used to determine whether the steering wheel pulling force is an effective pulling force.

[0053] In one possible implementation, the control module is also used for:

[0054] Based on the door closing signal and / or the signal of the disappearance of pulling force, a stop command is sent to the actuator via the vehicle's controller area network bus to control the actuator to stop outputting dynamic compensation force.

[0055] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0056] Fourthly, embodiments of this application provide a vehicle that includes a steer-by-wire system and electronic equipment as described in the third aspect.

[0057] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0058] Sixthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0059] The dynamic compensation control method, electronic device, and vehicle provided in this application are applied to vehicles including steer-by-wire systems. This method accurately identifies the scenario of pulling the steering wheel upon entering the vehicle by coordinating the processing of door status signals and steering wheel torque signals, avoiding false triggering based on global states such as vehicle speed and gear position. When the triggering condition is met, the actuator outputs a dynamic compensation force opposite to the steering wheel pulling force, matching the magnitude and direction of the steering wheel pulling force in real time, ensuring the steering wheel maintains a stable posture during the pulling process. This method replaces hardware-based locking schemes with software logic, eliminating the need to add or modify additional hardware, thus reducing system complexity and modification costs. Furthermore, because the output of the dynamic compensation force can respond to changes in steering wheel pulling force in real time, it avoids steering wheel wobbling or locking failure due to control delays or insufficient torque matching. Therefore, this method provides stable traction support for the driver without hardware modifications, reducing the risk of traction failure caused by unrestrained steering wheel rotation during entry, and improving entry convenience and safety. Attached Figure Description

[0060] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0061] Figure 1 A flowchart illustrating the dynamic compensation control method provided in the embodiments of this application. Figure 1 ;

[0062] Figure 2 A flowchart illustrating the dynamic compensation control method provided in the embodiments of this application. Figure 2 ;

[0063] Figure 3 A schematic diagram of a locking steering wheel provided in an embodiment of this application;

[0064] Figure 4 A flowchart illustrating the dynamic compensation control method provided in the embodiments of this application. Figure 3 ;

[0065] Figure 5This is a schematic diagram of the structure of the dynamic compensation control device provided in the embodiments of this application;

[0066] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0067] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0068] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0069] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize or refuse.

[0070] Furthermore, the technical solution involved in this application, which involves big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.) and the use of artificial intelligence technology for automated decision-making, and makes decisions that have a significant impact on personal rights based on the results of automated decision-making, provides users with corresponding operation entry points for users to choose to agree to or reject the results of automated decision-making; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0071] The following is an explanation of some terms and concepts used in the embodiments of this application:

[0072] Steer-by-wire system: Decoupling the steering wheel and steering gear is achieved by replacing the mechanical connection with an electrical signal.

[0073] Hand Wheel Actuator (HWA): A power unit used to control the rotation of the steering wheel.

[0074] Vehicle Control Unit (VCU): Used to integrate and execute control logic.

[0075] Controller Area Network (CAN) bus: a serial communication bus used in automotive, industrial control and other fields.

[0076] In this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0077] In the embodiments of this application, the use of terms such as "first" and "second" is to distinguish between identical or similar items that have essentially the same function and effect. For example, "first electronic device" and "second electronic device" are merely used to distinguish different electronic devices and do not limit their order of execution. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0078] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0079] For example, steer-by-wire systems are one of the steering components of a vehicle. They use electrical signals to replace traditional mechanical connections, decoupling the steering wheel from the steering actuator. This technology is widely used in new energy vehicles, autonomous vehicles, and high-end intelligent cockpits. Its core advantages lie in increasing vehicle design freedom, reducing mechanical transmission losses, and providing a foundation for intelligent control of the steering system. However, in real-world applications, steer-by-wire systems have functional limitations in specific scenarios.

[0080] For example, when a driver gets into a car, they need to pull on the steering wheel to get up. However, because the steering wheel is completely mechanically decoupled from the steering mechanism, the fixed characteristics of the steering wheel in the traditional mechanical structure are broken, causing the steering wheel to easily rotate under the pulling force. This problem is more pronounced for people who habitually pull on the steering wheel when getting into the car, obese people, the elderly, or people with mobility impairments. On the one hand, the rotation of the steering wheel after being pulled cannot provide stable support, which prolongs the time spent getting into the car; on the other hand, the unrestrained rotation of the steering wheel may cause the driver to lose their grip and collide with their body (such as the knees or abdomen), creating a safety hazard.

[0081] Some methods rely on control logic based on factors such as vehicle speed and gear position, such as proportional-integral-derivative (PID) adjustment and dynamic model compensation, to achieve steering wheel locking control. However, these methods struggle to accurately identify the specific scenario of "getting into the car and pulling the steering wheel," leading to the control strategy being falsely triggered or failing in non-driving situations.

[0082] Therefore, there is an urgent need for a software control method for this scenario that can achieve stable locking of the steering wheel posture through dynamic reverse force compensation without increasing hardware costs, thereby improving the convenience and safety of getting into the vehicle.

[0083] Existing steer-by-wire systems mainly achieve steering wheel locking or auxiliary control through two methods: hardware modification and software control.

[0084] Hardware modification solution: Some systems use electronic column locks or brake motors as steering wheel locking devices. Electronic column locks fix the steering wheel through an electromagnetic locking mechanism, but require additional mechanical structures, increasing the complexity of the vehicle structure and manufacturing costs; brake motors limit steering wheel rotation by outputting resistance torque, but their control logic depends on preset conditions (such as vehicle speed being 0 and gear being P), and cannot dynamically adapt to complex scenario requirements.

[0085] Software control scheme: Existing software logic is mostly based on global state trigger control strategies such as vehicle speed and gear position. For example, when the vehicle is parked (vehicle speed is 0) and in P gear, the steering wheel actuator output resistance torque is adjusted through a PID algorithm.

[0086] However, the software control scheme has at least two shortcomings. First, the triggering conditions are not optimized for the "getting into the car and pulling the steering wheel" scenario, making it impossible to distinguish between normal driver operation and the act of getting into the car and pulling the steering wheel, and difficult to identify the pulling action itself. Second, the unrestrained nature of the steering wheel after mechanical decoupling causes the pulling force to act directly on the steering column. The existing reverse force control strategy does not consider the dynamic characteristics of the pulling force (such as direction and duration), and is prone to steering wheel wobbling or locking failure due to control delay or insufficient torque matching.

[0087] Furthermore, existing solutions fail to achieve accurate scene recognition through sensor fusion (such as the coordinated judgment of door status and steering wheel torque), resulting in the control logic being triggered erroneously in non-target scenarios, affecting the user experience.

[0088] As the above analysis shows, existing steer-by-wire systems have significant shortcomings in the "getting into the car and pulling the steering wheel" scenario. Because the steering wheel and steering actuator are completely mechanically decoupled, the steering wheel is prone to rotating unrestrained when the driver pulls it, resulting in a lack of stable support and making it difficult to assist getting into the car, thus prolonging the time spent getting in. Furthermore, the unrestrained rotation of the steering wheel may cause a collision with the driver, posing a safety hazard.

[0089] Existing technical solutions (such as electronic column locks and brake motors) still rely on hardware modifications, which are costly and have poor adaptability. Software control logic based on vehicle speed and gear cannot accurately identify pulling behavior, leading to false triggering or control failure. In addition, existing reverse force control strategies do not consider the dynamic characteristics of pulling force (such as direction and duration), resulting in high control latency and inaccurate torque matching, further affecting the user experience.

[0090] Starting with the shortcomings found in existing technologies, the inventors first analyzed the characteristics of the "pulling the steering wheel to get up" scenario: the driver needs to pull the steering wheel to gain leverage to get up, but the steering wheel is easily rotated due to mechanical decoupling, leading to failure of leverage and safety risks. To address this shortcoming, the inventors proposed dynamically locking the steering wheel's posture through software logic, without requiring additional hardware modifications. Secondly, the inventors found that existing control logic, based on global states such as vehicle speed and gear position, cannot accurately identify pulling behavior. Therefore, they proposed a collaborative triggering mechanism combining door status and steering wheel torque, improving the accuracy of scene recognition through sensor data fusion.

[0091] Furthermore, the inventors realized that existing reverse force control strategies do not dynamically match the characteristics of the pulling force (such as direction and duration), so they designed a dynamic force compensation algorithm based on a proportional compensation model (dynamic compensation force = k × steering wheel pulling force) to achieve real-time torque matching.

[0092] In addition, the inventors optimized parameter calibration (such as force threshold and compensation coefficient) and exit mechanism (such as door closing and pulling force disappearance) to ensure that the control logic is accurately activated in the target scenario and avoid false triggering, thereby forming a complete software control solution.

[0093] In view of this, this application provides a dynamic compensation control method. This method, through software logic innovation, combines a collaborative triggering mechanism of door status and steering wheel torque to dynamically control the steering wheel actuator to output a counterforce, thereby achieving stable locking of the steering wheel posture. This technical concept is based on the native hardware resources of the steer-by-wire system (such as door sensors, steering wheel torque sensors, and HWA actuators), requiring no additional hardware modifications. Through sensor data fusion and a dynamic counterforce compensation algorithm, it accurately identifies the specific scenario of "driver pulling the steering wheel to get into the car" and adjusts the control strategy in real time, thereby improving the convenience of getting into the car while reducing hardware costs and system complexity.

[0094] The method provided in this application can be applied to a variety of vehicles, such as intelligent vehicles equipped with steer-by-wire systems, especially new energy vehicles, autonomous vehicles, and vehicles in the field of high-end intelligent cockpits.

[0095] For example, door status sensors can monitor door opening and closing status in real time, and combined with steering wheel torque sensors to detect driver pulling behavior, the vehicle controller integrates control logic and communicates with the HWA via the CAN bus to achieve dynamic locking of the steering wheel posture. This technology is adaptable to different vehicle models and door states (half-open, fully open), such as sedans or sport utility vehicles (SUVs), supports multi-scenario compatibility and parameter calibration, and is applicable to intelligent vehicle products worldwide.

[0096] The technical solutions of this application will be described in detail below with reference to specific embodiments. The specific embodiments described below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0097] Figure 1 A flowchart illustrating the dynamic compensation control method provided in the embodiments of this application. Figure 1 The subject executing this method can be an electronic device with corresponding data storage and computing capabilities, such as a vehicle or vehicle controller. The electronic device may include one processor unit, or it can be understood as including multiple processor units. For example, the electronic device may include one processor chip, or it may include multiple processor chips.

[0098] Taking in-vehicle electronic devices as an example, when executing this method, the in-vehicle electronic devices can perform the method through coordinated data processing between processor units such as the vehicle controller, electronic control unit (ECU), and in-vehicle telematics box (T-BOX). It should be understood that the specific form of the electronic device is not limited in the embodiments of this application.

[0099] The method provided in this application is applied to vehicles including steer-by-wire systems. For example, the vehicle may further include a door status sensor for real-time detection of door open / close status (open / close signal), with a detection accuracy of, for example, a response time of 0.1 seconds. The vehicle may also include a steering wheel torque sensor, which can be integrated into the steering column to detect the direction, magnitude, and duration of the steering wheel pulling force. For example, the sampling frequency is ≥100Hz, and the steering wheel pulling force threshold can be calibrated; for example, a radial pulling force >5N is considered an effective pulling force by default.

[0100] The vehicle may also include a steering wheel actuator with a built-in brushless motor, for example, a maximum output torque of 15 N·m, a response delay of <20 ms, and support for dynamic compensation force output for counterforce. The vehicle may also include a vehicle control unit (VCU): equipped with a control chip for integrating control logic, and capable of communicating with sensors and actuators via a CAN bus (500 kbps baud rate). Figure 1 As shown, the method includes steps S101, S102 and S103.

[0101] S101 detects the vehicle door status signal and steering wheel torque signal.

[0102] For example, the door status signal includes a signal characterizing whether the door is open or closed, such as an electrical signal detected by a sensor to indicate whether the door is open or closed. The steering wheel torque signal can be understood as a signal characterizing the steering wheel pulling force, such as an electrical signal detected by a torque sensor to indicate the magnitude and direction of the steering wheel's radial pulling force.

[0103] S102 determines whether the triggering conditions for dynamic compensation are met based on the door status signal and the steering wheel torque signal.

[0104] For example, the triggering condition for dynamic compensation can be understood as a condition for determining whether dynamic compensation of steering wheel pull force is triggered. The detected door status signal and steering wheel torque signal are matched with the triggering condition. If the match is successful, the triggering condition is deemed met; if the match fails, the triggering condition is deemed not met. For example, the triggering condition may include the combination of a door being open and a steering wheel pull force being detected.

[0105] S103, when the triggering conditions are met, controls the actuator to output a dynamic compensation force that is opposite to the steering wheel pulling force.

[0106] For example, an actuator can be understood as a device for outputting dynamic compensation force, such as a steering wheel actuator HWA, which outputs a reverse force through motor drive. Dynamic compensation force can be understood as a dynamically output and continuously adjustable reverse force based on the characteristics of the steering wheel pulling force (such as direction and magnitude). For example, the magnitude of the dynamic compensation force can be calculated using a proportional compensation model.

[0107] It should be understood that the output dynamic compensation force, which is opposite to the steering wheel pulling force, can be understood as the component of the dynamic compensation force in the tangential direction of the steering wheel and the component of the steering wheel pulling force in the tangential direction of the steering wheel being two forces with opposite directions and equal magnitudes. Since these two components can achieve a balance between the two forces, the steering wheel can remain stationary.

[0108] Through the aforementioned steps S101 to S103, dynamic locking control of the steering wheel attitude can be achieved through the coordinated processing of the door status signal and the steering wheel torque signal. When executing the above steps, for example, it can be done through... Figure 2 The process shown is implemented.

[0109] Figure 2 A flowchart illustrating the dynamic compensation control method provided in the embodiments of this application. Figure 2 ,like Figure 2 As shown, firstly, electronic devices can detect door status signals (such as a signal indicating a door is open) and steering wheel torque signals (such as the magnitude and direction of steering wheel pulling force) via sensors. These two sets of signals are then transmitted to a control unit (such as the VCU). The control unit processes the signals and determines whether triggering conditions are met, such as a door being open and a steering wheel pulling force being detected.

[0110] If the trigger condition is met, the actuator (such as HWA) outputs a dynamic compensation force opposite to the steering wheel pulling force. This reverse torque output can be achieved by driving the steering wheel actuator with a brushless motor. If the trigger condition is not met, the process returns to the sensor signal detection step to continue signal detection.

[0111] Based on this, the above-mentioned execution process can realize signal transmission and control command issuance through vehicle communication protocols (such as CAN bus), enabling the actuator to respond quickly (e.g., delay <20ms), thereby dynamically matching the characteristics of the steering wheel pulling force and achieving stable locking of the steering wheel posture.

[0112] The dynamic compensation control method provided in this application solves the problems of the steering wheel's inability to leverage the pulling force and the risk of collision caused by mechanical decoupling in the steer-by-wire system through dynamic compensation force control technology.

[0113] Specifically, the electronic equipment accurately identifies the "getting into the car and pulling the steering wheel" scenario by coordinating the processing of door status signals and steering wheel torque signals, avoiding false triggers based on global states such as vehicle speed and gear. When the triggering conditions are met, the actuator outputs a dynamic compensation force in the opposite direction to the steering wheel pulling force, matching the magnitude and direction of the steering wheel pulling force in real time, so that the steering wheel maintains a stable posture during the pulling process.

[0114] The method based on the embodiments of this application replaces hardware-based locking schemes (such as electronic column locks or brake motors) with software logic, eliminating the need to add or modify additional hardware equipment and significantly reducing system complexity and modification costs. Furthermore, due to the output of dynamic compensation force, it can respond in real time to changes in steering wheel pulling force, avoiding steering wheel wobbling or locking failure caused by control delays or insufficient torque matching. Therefore, this method can provide stable traction support for the driver without hardware modifications, reducing the risk of traction failure due to unrestrained steering wheel rotation during vehicle entry, and improving entry convenience and safety.

[0115] In one possible implementation, controlling the actuator output a dynamic compensation force opposite to the steering wheel pulling force includes: calculating the magnitude of the dynamic compensation force using a proportional compensation model based on the magnitude of the steering wheel pulling force; and controlling the actuator output a holding force opposite to the steering wheel pulling force, wherein the holding force is a continuous dynamic compensation force.

[0116] For example, the proportional compensation model can be understood as an algorithm that dynamically calculates the counterforce based on the magnitude of the pulling force. For instance, the dynamic compensation force = k × steering wheel pulling force, where k represents the compensation coefficient. k can be calibrated and set according to different vehicle types, steering wheel sizes, or application scenario requirements. For example, k can be calibrated within the range of 0.8-1.2, such as k=1. The holding force can be understood as the continuous dynamic compensation force output by the actuator, such as generating a continuous torque by driving the steering wheel actuator through a brushless motor. The duration of the holding force can be the same as the duration of the steering wheel pulling force. Alternatively, when the steering wheel pulling force is small (e.g., less than the steering wheel pulling force threshold), the duration of the holding force can be less than the duration of the steering wheel pulling force. This means that when the steering wheel is slightly pulled, a dynamic compensation force may or may not be output.

[0117] Understandably, since pulling the steering wheel to get into the car is usually a continuous action, the magnitude and direction of the force applied when the user applies steering wheel pulling force to assist in getting into the car will change randomly. This change may be large or small. Because the dynamic compensation force has dynamic characteristics, the holding force can also be understood as a counterforce that dynamically changes with the applied steering wheel pulling force, and can continue until the steering wheel pulling force disappears and the output of dynamic compensation force stops.

[0118] Figure 3 This is a schematic diagram of a locking steering wheel provided in an embodiment of this application, as shown below. Figure 3 As shown, when the user pulls the steering wheel, a steering wheel pulling force F1 is applied. By judging the trigger condition and executing the dynamic compensation control logic, the actuator can be controlled to output a dynamic compensation force F2 to counteract the steering wheel pulling force F1. Since F1 and F2 can achieve a balance between the two forces, the steering wheel can remain locked and not turn, thus providing pulling support for the user.

[0119] The proportional compensation model can be expressed as: Dynamic compensation force = k × steering wheel pulling force. This expression can also be expressed as F2 = k × F1, where F1 represents the steering wheel pulling force applied to the steering wheel; k represents the compensation coefficient; and F2 represents the dynamic compensation force, which is the reverse force controlled to counteract the steering wheel pulling force.

[0120] When the dynamic compensation force is calculated using a proportional compensation model and the holding force is output by the actuator, the execution process can be as follows: The control unit (such as VCU) inputs the proportional compensation model according to the steering wheel pulling force signal (such as magnitude and direction), calculates the magnitude of the reverse dynamic compensation force (such as dynamic compensation force = k × steering wheel pulling force), and converts the calculation result into a control command and sends it to the actuator.

[0121] After receiving the command, the actuator (such as HWA) drives a brushless motor to output a holding force opposite to the steering wheel pulling force, continuously outputting the force until the door closes or the pulling force disappears. The above execution process can be achieved through vehicle communication protocols (such as CAN bus) to transmit signals and issue control commands, enabling the actuator to respond quickly (e.g., delay <20ms), thereby dynamically matching the characteristics of the steering wheel pulling force.

[0122] In this embodiment, the magnitude of the dynamic compensation force is dynamically calculated using a proportional compensation model to ensure that the dynamic compensation force accurately matches the steering wheel pulling force. Specifically, by calculating and adjusting the magnitude of the dynamic compensation force in real time using the proportional compensation model, under-control or over-control caused by a fixed torque can be avoided. For example, when the driver continuously pulls the steering wheel, the proportional compensation model can adjust the magnitude of the dynamic compensation force according to the real-time changes in the pulling force to ensure that the steering wheel posture is in a stable locked state. This method, through the collaboration of algorithms and hardware, improves the flexibility and adaptability of the control strategy, further optimizing vehicle accessibility and safety.

[0123] For example, if the reverse force control strategy does not consider the dynamic characteristics of the pulling force (such as magnitude, direction, and duration), resulting in high control latency or inaccurate torque matching, it will affect the user experience. Therefore, the method provided in this application, when calculating the magnitude of the dynamic compensation force using a proportional compensation model, can dynamically adapt the control strategy by incorporating the dynamic characteristics of the pulling force.

[0124] In one possible implementation, the calculation of the dynamic compensation force using a proportional compensation model includes: adjusting the compensation coefficient in the proportional compensation model according to the vehicle type and / or steering wheel size, and calculating the magnitude of the dynamic compensation force based on the adjusted compensation coefficient; controlling the actuator output to maintain a holding force opposite to the steering wheel pulling force includes: determining the direction of the steering wheel pulling force using a moving average algorithm, and determining the direction of the dynamic compensation force based on the direction of the steering wheel pulling force; and controlling the actuator output to maintain a holding force opposite to the steering wheel pulling force based on the direction and magnitude of the dynamic compensation force.

[0125] For example, vehicle type can be understood as a classification of vehicles, such as sedans or SUVs. Different vehicle types and different steering wheel sizes have certain differences in pulling force characteristics. The moving average algorithm can be understood as an algorithm that dynamically corrects the current value by calculating the average value of historical data, such as smoothing the long-term trend of the pulling force direction. By adjusting the compensation coefficient and the moving average algorithm for determining the force direction, the calculation of the magnitude and determination of the dynamic compensation force can be optimized.

[0126] For example, the Vehicle Control Unit (VCU) dynamically adjusts the compensation coefficients in the proportional compensation model based on the vehicle type (e.g., sedan or SUV) and steering wheel size; for instance, k=1.0 for sedans and k=1.2 for SUVs. Furthermore, by employing a moving average algorithm, the current steering wheel pull force direction is corrected and determined based on multiple historical pull directions, allowing for a relatively accurate determination of the current steering wheel pull force direction.

[0127] For example, when a driver frequently pulls in a certain direction, the moving average algorithm can correct the long-term trend of the pulling force direction, ensuring the stability of the dynamic compensation force output in the opposite direction. This process achieves data transmission and algorithm execution through vehicle communication protocols (such as CAN bus), improving the accuracy of the dynamic compensation force.

[0128] Furthermore, the control logic can also incorporate the duration of the steering wheel pulling force (e.g., a duration > 0.5 seconds is considered a valid trigger) to avoid interference from short-term invalid signals. In this way, through the collaboration of algorithms and hardware, dynamic torque adjustment is achieved, ensuring the steering wheel maintains a stable posture during pulling, thereby improving control reliability and user experience.

[0129] In this embodiment, by adjusting the compensation coefficient and optimizing the direction determination of the dynamic compensation force using a moving average algorithm, the adaptability of the control strategy can be improved. For example, in SUVs, due to the larger steering wheel size, the compensation coefficient needs to be increased to ensure sufficient output torque of the reverse dynamic compensation force. When the driver frequently pulls in a certain direction, the moving average algorithm can correct the long-term trend of the steering wheel pulling force direction, avoiding short-term fluctuations. Based on this, through differentiated parameter configuration and algorithm optimization, the scenario compatibility of the control logic and the user experience are further improved.

[0130] For example, if the control logic does not consider the driver's personalized operating habits (such as a preference for pulling on the left or right), the direction of the counterforce will not match the driver's intention, affecting the control effect. To address this, the method provided in this application integrates machine learning (such as lightweight neural networks) and trains a self-learning model by collecting historical data (such as door status, steering wheel torque, and driver operating mode), which can dynamically adapt to the steering wheel pulling force.

[0131] In one possible implementation, the method further includes: acquiring multiple historical operation data of pulling the steering wheel; training a self-learning model based on the multiple historical operation data of pulling the steering wheel, wherein the self-learning model is used to output the compensation coefficient of the dynamic adjustment proportional compensation model and the adjustment strategy of the direction of the steering wheel pulling force.

[0132] For example, a self-learning model can be understood as a machine learning model obtained by training on historical data of pulling the steering wheel, such as neural networks and / or decision trees.

[0133] By sifting through accumulated vehicle history data, multiple historical steering wheel pulling operation data can be extracted. This historical operation data can be used to train machine learning models, enabling the models to output adjustment strategies. These adjustment strategies can be understood as dynamic adjustment rules for adjusting compensation coefficients and the direction of steering wheel pulling force. For example, for a pulling habit that prefers to pull to the left, an adjustment strategy can be developed to determine how to adjust the compensation coefficients and how to determine the direction of the steering wheel pulling force.

[0134] In this embodiment, by training the self-learning model, a better adjustment strategy for the compensation coefficient and the direction of the pulling force can be output.

[0135] For example, the Vehicle Control Unit (VCU) collects historical data on steering wheel pulls (such as door status, steering wheel torque, and driver pull direction) and inputs it into an initial self-learning model for training. By analyzing the common and individual characteristics of the input data, the initial self-learning model can learn the driver's pulling habits, such as a preference for pulling the steering wheel to the left or right. This allows for the output of adjustment strategies that better match the driver's habits, enabling more accurate adjustment of the compensation coefficient and determination of the steering wheel pull direction.

[0136] For example, to address the driver's preference for pulling the steering wheel to the left, the trained self-learning model can prioritize activating the dynamic compensation force output in the left direction, improving the accuracy of the locking effect. Optimizing the dynamic compensation force output through the self-learning model allows the actuator's output to better match the driver's personalized operating habits. Personalized optimization driven by historical operating data can further enhance the adaptability of the steer-by-wire dynamic compensation control strategy and the user experience.

[0137] During the implementation of the above scheme, data transmission and self-learning model updates can also be achieved through vehicle communication protocols (such as CAN bus), enabling personalized and effective adaptation of adjustment strategies.

[0138] In this embodiment, a self-learning model is trained, and its output can dynamically adjust the compensation coefficient and the direction of the steering wheel pulling force, thereby improving the personalized adaptability of the control strategy. Based on the self-learning model, the magnitude and direction of the dynamic compensation force can be dynamically adjusted to ensure the accuracy of the locking effect.

[0139] In one possible implementation, the self-learning model includes a neural network and a decision tree algorithm. The method further includes: identifying the pulling direction preference of the vehicle's steering wheel by the neural network in the self-learning model; and, based on the pulling direction preference, using the decision tree algorithm in the self-learning model, deciding on the dynamic adjustment strategy of the compensation coefficient of the proportional compensation model and the direction of the steering wheel pulling force.

[0140] For example, a neural network can be understood as a machine learning model that mimics the connection structure and information transmission method of neurons in the biological brain, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). A decision tree algorithm can be understood as a machine learning algorithm that makes decisions through a tree-like structure; for example, decision tree paths can be pre-constructed for decision-making.

[0141] In this embodiment, to achieve a lightweight configuration, the neural network can be a lightweight neural network. A lightweight neural network can be understood as a neural network with a low number of model parameters and / or low computational resource consumption. For example, whether a neural network is lightweight can be determined by preset thresholds for the number of model parameters and / or thresholds for the computational resource consumption during model runtime. Lightweight neural networks include, for example, lightweight CNN models for edge computing.

[0142] For example, a vehicle control unit (VCU) can analyze the characteristics of steering wheel pull actions in historical data from multiple steering wheel pulls using a lightweight neural network, and summarize the pull direction preference by learning the patterns of these characteristics. In inference applications, the current steering wheel pull force is detected and input into the lightweight neural network for identification, determining the driver's pull direction preference. Based on the identified pull direction preference, a decision tree algorithm is input, and a decision is made by matching decision paths. When the decision process reaches the endpoint of a certain decision path, the corresponding compensation coefficient and the adjustment strategy for the steering wheel pull force direction can be determined based on that endpoint.

[0143] By using a decision tree algorithm, the compensation coefficient and the adjustment strategy for the direction of the steering wheel pulling force can be determined based on the long-term trend of the pulling direction preference (e.g., the number of pulls to the left is much greater than the number of pulls to the right). This determined adjustment strategy allows for dynamic adjustment of the compensation coefficient and correction and determination of the direction of the current steering wheel pulling force, resulting in a more precise dynamic compensation force output in both magnitude and direction.

[0144] During the execution of the method in this embodiment, data transmission and model decision-making can also be achieved through vehicle communication protocols (such as CAN bus) to ensure the effective execution of the strategy.

[0145] In this embodiment, neural networks and decision tree algorithms can improve the high degree of adaptation between the adjustment strategy and user behavior. For example, neural networks can accurately identify the driver's pulling direction preference, while decision tree algorithms can efficiently determine the adjustment strategy, thereby accurately determining the compensation coefficient and the direction of the steering wheel pulling force, further improving the applicability of dynamic compensation force control.

[0146] For example, if the triggering logic for dynamic compensation force is based on the vehicle's global state, such as speed and gear, it is difficult to accurately identify the specific scenario of "getting into the car and pulling the steering wheel," which may lead to the control strategy being falsely triggered or failing in other scenarios. To address this, the method provided in this application constructs a dual-condition judgment logic of "door opening + steering wheel pulling force" through a collaborative triggering mechanism of the door state sensor and the steering wheel torque sensor, accurately identifying the "getting into the car and pulling the steering wheel" scenario.

[0147] In one possible implementation, determining whether the triggering conditions for dynamic compensation are met based on the door status signal and the steering wheel torque signal includes: determining whether the door status signal and the steering wheel torque signal simultaneously meet the triggering conditions by using a preset logic gate circuit or a preset program algorithm.

[0148] For example, a preset logic gate circuit can be understood as a hardware circuit used to implement logical judgments, such as an AND gate circuit used to determine whether multiple conditions are true simultaneously. A preset program algorithm can be understood as a logical judgment method implemented through computer program code, such as using a conditional statement (if-else) to determine whether the door status signal and the steering wheel torque signal simultaneously meet the triggering conditions.

[0149] When determining trigger conditions using preset logic gate circuits or preset program algorithms, for example, the control unit (VCU) can receive door status signals (such as door open) and steering wheel torque signals (such as pulling force > 5N and duration > 0.5s), and then use preset logic gate circuits or preset program algorithms to determine whether the door is currently open and whether the pulling force is greater than a pulling force threshold. Alternatively, it can also determine whether the duration of the steering wheel pulling force is greater than a preset duration threshold (such as 0.5s).

[0150] For example, the AND gate circuit or the logical AND operation in the preset program can ensure that the trigger condition is met only when the door is opened and the steering wheel detects a valid pulling force. Here, the valid pulling force can be understood as the pulling force of the steering wheel whose magnitude and / or duration meets a preset threshold. This process can also be implemented through vehicle communication protocols (such as CAN bus) to improve the real-time performance and reliability of the trigger condition determination.

[0151] In this embodiment, by fusing multi-source data on door status and steering wheel torque, the accuracy of scene recognition is improved, and the probability of false triggering based on vehicle speed, gear position and other global vehicle statuses is reduced.

[0152] For example, the VCU simultaneously collects data from the door status sensor (detecting whether the door is open) and the steering wheel torque sensor (detecting the direction and magnitude of the pulling force). It then uses a preset logic gate circuit or a preset program algorithm to determine whether both conditions are met simultaneously. For instance, when the door is open and a radial pulling force is detected on the steering wheel, it is determined to be a "getting into the car and pulling the steering wheel" scenario, triggering the HWA control logic. In this way, by extracting scene features (coordinated judgment of door opening status and pulling force), the scenario adaptability of the control logic is significantly improved, avoiding accidental triggering during normal driving. This ensures that the control strategy is activated only in the target scenario, enhancing the user experience.

[0153] In this embodiment, precise determination of triggering conditions is achieved through preset logic gate circuits or preset program algorithms, which reduces the probability of false triggering and improves reliability. For example, when the car door is open but no effective pulling force is detected on the steering wheel, the triggering condition is not met, and the control logic for dynamic compensation force is not activated. However, when the car door is open and an effective pulling force is detected on the steering wheel, the triggering condition is met, and the control logic for dynamic compensation force is activated. Based on this, the accuracy of scene recognition is improved through multi-source data fusion, ensuring that the control strategy is activated only in the specific scenario of "getting into the car and pulling the steering wheel," thereby improving the reliability of control.

[0154] For example, if the influence of different door states (such as half-open or fully open) on the pulling force threshold and compensation coefficient is not considered during control, the dynamic compensation force may be insufficient and difficult to adapt to the steering wheel pulling force. To this end, the method provided in this application includes a door opening angle signal in the door state signal. The door state can be determined through this signal, achieving a more granular judgment of the current door state. Then, a pulling force threshold and / or compensation coefficient with a higher matching degree can be configured according to different door states.

[0155] In one possible implementation, the door status signal includes a door opening angle signal, and the method further includes: determining the current door status based on the door opening angle signal in the door status signal, the door status including a fully open state and a half open state; configuring a pulling force threshold and / or a compensation coefficient in a proportional compensation model based on the door status, the pulling force threshold being used to determine whether the steering wheel pulling force is an effective pulling force.

[0156] For example, the pulling force threshold can be understood as a threshold for determining whether the steering wheel pulling force is an effective pulling force. The pulling force threshold can be preset according to the vehicle type or specific application scenario, or it can be determined adaptively according to the door status. For example, the preset pulling force threshold for sedans is 5N by default, and the preset pulling force threshold for SUVs is 7N by default, or the pulling force threshold can be dynamically adapted to the current scenario based on the door status.

[0157] The door opening angle signal can be understood as the degree of door opening, such as the door opening angle detected by an angle sensor as 30°, 60°, or 90°. For example, the control unit (VCU) receives the door opening angle signal (such as 30°, 60°, 90°) and, through a preset mapping relationship, can determine the corresponding pulling force threshold and / or compensation coefficient in the proportional compensation model.

[0158] For example, a fully open door can be defined as a door opening of 60° or more, which corresponds to a compensation coefficient of 1.2 and / or a pulling force threshold of 7N. A partially open door can be defined as a door opening of less than 60° but greater than 30°, which corresponds to a compensation coefficient of 1.1 and / or a pulling force threshold of 5N. Of course, these compensation coefficient values ​​and pulling force thresholds are just examples, and the actual values ​​used in real-world applications may differ from these examples.

[0159] In this embodiment, the door opening angle signal in the door status signal allows for a more granular determination of whether the current door is half-open or fully open. Furthermore, for different door states, more suitable pulling force thresholds and / or compensation coefficients in the proportional compensation model can be configured. Based on this, it is possible to more accurately determine whether the current steering wheel pulling force is effective, and thus output a dynamic compensation force that effectively counteracts the steering wheel pulling force. For example, configuring a lower pulling force threshold in the half-open state can reduce the probability of false triggering; configuring a higher pulling force threshold in the fully open state ensures effective triggering of the dynamic compensation force. Through scene segmentation and parameter differentiation configuration, the adaptability of the control strategy and the user experience can be further optimized.

[0160] In one possible implementation, after controlling the actuator to output a dynamic compensation force opposite to the steering wheel pulling force, the method further includes: sending a stop command to the actuator via the vehicle's controller area network bus based on a door closing signal and / or a pulling force disappearance signal, so as to control the actuator to stop outputting the dynamic compensation force through the stop command.

[0161] For example, when detecting the door status signal, a door closing signal can also be detected. The door closing signal can be understood as a signal indicating whether the door is fully closed. For instance, a detected door closing signal of 0 indicates the door is open, and a detected door closing signal of 1 indicates the door is closed. The disappearance of pulling force signal can be understood as a signal indicating that the steering wheel pulling force is not an effective pulling force.

[0162] The vehicle's Controller Area Network (CAN) bus can be understood as an in-vehicle network communication protocol, such as a CAN bus with a baud rate of 500kbps. When transmitting commands via the CAN bus, the number of bytes in the data field of the CAN bus message can be identified by the Data Length Code (DLC).

[0163] When the actuator is controlled to stop outputting dynamic compensation force by means of a door closing signal and / or a pull force disappearance signal, for example, the control unit (VCU) detects the door closing signal (e.g., the signal value changes from 0 to 1) and the pull force disappearance signal (e.g., the steering wheel pull force is <2N and lasts for 1 second), and sends a stop command to the actuator (e.g., HWA) via the CAN bus.

[0164] After receiving the stop command, the actuator stops outputting dynamic compensation force, and the steering wheel can return to its free state. This process is achieved through signal transmission and control command issuance via the CAN bus vehicle communication protocol, ensuring the accuracy of the control logic's exit mechanism.

[0165] In this embodiment, controlling the actuator to stop outputting dynamic compensation force via a door closing signal and / or a signal indicating the disappearance of pulling force ensures the accuracy of the control logic's exit mechanism. For example, when the door is fully closed or the pulling force disappears, the actuator stops outputting a dynamic compensation force opposite to the steering wheel pulling force, thus promptly restoring the steering wheel to its free state. This prevents the control logic from continuously activating in scenarios other than "getting into the car and pulling the steering wheel," improving the robustness of the exit control and further enhancing the user experience.

[0166] In one possible implementation, the method can further enhance the use of a camera or millimeter-wave radar as auxiliary sensors, in addition to the door status sensor and steering wheel torque sensor, to detect driver posture, such as body tilt angle or leg movements. By fusing multi-source data, such as door status, steering wheel torque, and driver posture, a more accurate scene recognition model can be constructed. For example, a machine learning classifier such as weighted logic gates or random forests can be used to comprehensively determine the "getting into the car and pulling the steering wheel" scenario.

[0167] By incorporating driver posture information, it is possible to further distinguish between normal driver operations (such as pulling the steering wheel while adjusting the seat) and pulling behavior upon entering the vehicle, thereby reducing the false trigger rate.

[0168] For example, when a car door opens and the steering wheel detects a pulling force, if the camera does not detect the driver's leg movement, it is determined that the dynamic compensation force will not be triggered, thus avoiding activation of the control logic in non-target scenarios. Furthermore, multi-source data fusion can improve the robustness of scene recognition. Even if data from a single sensor is abnormal (such as a false alarm from the steering wheel torque sensor), the judgment result can still be corrected using data from other sensors, thereby improving the reliability of the control logic and the user experience.

[0169] Below, through Figure 4 The dynamic compensation control method provided in the embodiments of this application will be further described. Figure 4 A flowchart illustrating the dynamic compensation control method provided in the embodiments of this application. Figure 3 ,like Figure 4 As shown, the control flow includes:

[0170] S401, Scene trigger condition judgment.

[0171] For example, the VCU synchronously collects the door status signal (door open but not fully closed, door lock signal is 0) and the steering wheel torque signal (radial pulling force > 5N and lasting > 0.5s). When both conditions are met simultaneously, it is determined to be a "getting into the car and pulling the steering wheel" scenario, triggering the HWA control logic.

[0172] S402, Dynamic Compensation Force Control.

[0173] For example, the direction of the dynamic compensation force is determined as follows: the HWA outputs a holding force opposite to the steering wheel pull force to counteract the steering wheel rotation tendency. For instance, when the pull force is radially outward along the steering wheel, the HWA outputs an inward resistance. The magnitude of the dynamic compensation force is determined using a proportional compensation model (dynamic compensation force = k × steering wheel pull force). The duration of the holding force is determined as follows: from the moment the trigger condition is met until the door is fully closed (lock signal is 1) or the pull force is <2N and lasts for 1 second, there is a 2-second delay before control is released.

[0174] S402, execute the exit mechanism.

[0175] For example, the VCU sends a stop command to the HWA when any of the following conditions are met: (1) the door lock signal changes from 0 to 1 (fully closed); (2) the steering wheel pulling force is <2N and lasts for 1s; (3) the vehicle detects a shift signal (D / R gear) or the vehicle speed is >0km / h.

[0176] In one possible implementation, adaptive pulling force threshold calibration includes: adaptively adjusting the pulling force threshold using a VCU algorithm based on the vehicle model (sedan / SUV) and steering wheel size (e.g., a default threshold of 7N for SUV models). In another possible implementation, multi-door state compatibility includes: supporting unified recognition of front door half-open (opening angle > 30°) and fully open scenarios to avoid false triggering due to differences in door opening angles.

[0177] In this embodiment, since existing sensors (torque sensor, door sensor) and actuators (HWA) can be reused, the method can be implemented simply by upgrading the software logic, resulting in low implementation cost and low hardware modification cost. Because the control strategy is activated only in the scenario of "getting into the vehicle and pulling the steering wheel," false triggering during normal driving can be avoided, resulting in a low false trigger rate of the control logic. This method is applicable to vehicles with steer-by-wire systems of different tonnages and models, and can be adapted through parameter calibration, demonstrating strong compatibility.

[0178] This method provides stable support for drivers, such as obese individuals, who rely on the steering wheel for leverage when getting into the vehicle, effectively shortening the time required and improving vehicle convenience. By locking the steering wheel, the risk of the steering wheel hitting the driver's body during the entry process is effectively reduced, thus enhancing safety.

[0179] Compared to electronic column lock solutions, the method in this application has lower hardware costs, requires no changes to the vehicle's mechanical structure, and offers greater adaptability and economic advantages. Furthermore, the method in this application has a low response delay from triggering to execution, meeting ergonomic requirements for real-time performance and achieving high control efficiency.

[0180] Figure 5 This is a schematic diagram of the structure of the dynamic compensation control device provided in the embodiments of this application, as shown below. Figure 5 As shown, this application provides a dynamic compensation control device applied to a vehicle including a steer-by-wire system. The device includes:

[0181] The detection module 501 is used to detect the vehicle door status signal and steering wheel torque signal;

[0182] The determination module 502 is used to determine whether the triggering conditions for dynamic compensation are met based on the door status signal and the steering wheel torque signal.

[0183] The control module 503 is used to control the actuator to output a dynamic compensation force that is opposite to the steering wheel pulling force when the triggering conditions are met.

[0184] In one possible implementation, the control module 503 is specifically used for:

[0185] The magnitude of the dynamic compensation force is calculated using a proportional compensation model based on the magnitude of the steering wheel pulling force.

[0186] The control actuator outputs a holding force that is opposite to the steering wheel pulling force; this holding force is a continuous, dynamic compensation force.

[0187] In one possible implementation, the control module 503 is specifically used for:

[0188] Adjust the compensation coefficients in the proportional compensation model according to the vehicle type and / or steering wheel size, and calculate the magnitude of the dynamic compensation force based on the adjusted compensation coefficients;

[0189] The direction of the steering wheel pulling force is determined by the moving average algorithm, and the direction of the dynamic compensation force is determined based on the direction of the steering wheel pulling force.

[0190] Based on the direction and magnitude of the dynamic compensation force, the actuator outputs a holding force that is opposite to the steering wheel pulling force.

[0191] In one possible implementation, the device further includes a training module, which is used for:

[0192] Acquire historical data from multiple steering wheel pull operations;

[0193] A self-learning model is trained based on historical data of multiple steering wheel pulls. The self-learning model is used to output the compensation coefficient of the dynamic adjustment proportional compensation model and the adjustment strategy of the direction of the steering wheel pulling force.

[0194] In one possible implementation, the self-learning model includes a neural network and a decision tree algorithm, and the device further includes an adjustment module for:

[0195] The neural network in the self-learning model identifies the pulling direction preference of the vehicle's steering wheel when it is pulled;

[0196] Based on the pulling direction preference, the decision tree algorithm in the self-learning model makes a decision output that dynamically adjusts the compensation coefficient of the proportional compensation model and the adjustment strategy for the direction of the steering wheel pulling force.

[0197] In one possible implementation, the determining module 502 is specifically used for:

[0198] Based on the door status signal and the steering wheel torque signal, a preset logic gate circuit or a preset program algorithm is used to determine whether the door status signal and the steering wheel torque signal simultaneously meet the triggering conditions.

[0199] In one possible implementation, the door status signal includes a door opening angle signal, and the control module 503 is further used for:

[0200] The current door status is determined based on the door opening angle signal in the door status signal. The door status includes fully open and half open.

[0201] Based on the door status, configure the pulling force threshold and / or the compensation coefficient in the proportional compensation model. The pulling force threshold is used to determine whether the steering wheel pulling force is an effective pulling force.

[0202] In one possible implementation, the control module 503 is further configured to:

[0203] Based on the door closing signal and / or the signal of the disappearance of pulling force, a stop command is sent to the actuator via the vehicle's controller area network bus to control the actuator to stop outputting dynamic compensation force.

[0204] The dynamic compensation control device provided in this application embodiment can be used to execute the technical solution of the dynamic compensation control method in any of the above embodiments of this application. Its implementation principle and technical effect are similar, and will not be described again in this embodiment.

[0205] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 6As shown, the electronic device of this embodiment may include: at least one processor 601; and a memory 602 communicatively connected to the at least one processor; wherein the memory 602 stores instructions that can be executed by the at least one processor 601, and the instructions are executed by the at least one processor 601 to cause the electronic device to perform the method as described in any of the above embodiments.

[0206] Optionally, the memory 602 can be either standalone or integrated with the processor 601.

[0207] The implementation principle and technical effects of the electronic device provided in this embodiment can be found in the foregoing embodiments, and will not be repeated here.

[0208] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method of any of the foregoing embodiments.

[0209] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method of any of the foregoing embodiments.

[0210] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0211] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0212] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU) or other general-purpose processors. The processor can also be a Digital Signal Processor (DSP) or an Application Specific Integrated Circuit (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0213] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be various media that can store program code, such as USB flash drives, portable hard drives, read-only memory (ROM), disks or optical discs.

[0214] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Examples of storage media include Static Random-Access Memory (SRAM) or Electrically Erasable Programmable Read Only Memory (EEPROM).

[0215] Storage media can be, for example, erasable programmable read-only memory (EPROM) or programmable read-only memory (PROM). Storage media can also be read-only memory (ROM), magnetic storage, flash memory, magnetic disks, or optical disks. Storage media can be any available medium accessible to general-purpose or special-purpose computers.

[0216] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside within an application-specific integrated circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components within an electronic device or host device.

[0217] It should be noted that, in this document, 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. Unless otherwise specified, 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 that element.

[0218] The sequence numbers of the embodiments in this application are merely for description and do not represent the superiority or inferiority of the embodiments. Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0219] Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0220] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0221] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0222] It should be further noted that although the steps in the flowchart are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders.

[0223] Furthermore, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0224] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0225] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0226] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A dynamic compensation control method, characterized in that, The method is applied to a vehicle including a steer-by-wire system, and the method includes: Detect the vehicle door status signal and steering wheel torque signal; Based on the door status signal and the steering wheel torque signal, determine whether the triggering conditions for dynamic compensation are met; When the triggering conditions are met, the actuator outputs a dynamic compensation force that is opposite to the steering wheel pulling force.

2. The method according to claim 1, characterized in that, The control actuator outputs a dynamic compensation force that is opposite to the steering wheel pulling force, including: The magnitude of the dynamic compensation force is calculated using a proportional compensation model based on the magnitude of the steering wheel pulling force. The actuator is controlled to output a holding force that is opposite to the steering wheel pulling force, and the holding force is a continuous dynamic compensation force.

3. The method according to claim 2, characterized in that, The calculation of the dynamic compensation force using a proportional compensation model includes: Based on the vehicle type and / or steering wheel size, adjust the compensation coefficient in the proportional compensation model, and calculate the magnitude of the dynamic compensation force based on the adjusted compensation coefficient; The control of the actuator to output a holding force opposite to the steering wheel pulling force includes: The direction of the steering wheel pulling force is determined by a moving average algorithm, and the direction of the dynamic compensation force is determined based on the direction of the steering wheel pulling force. Based on the direction and magnitude of the dynamic compensation force, the actuator is controlled to output a holding force that is opposite to the steering wheel pulling force.

4. The method according to claim 2, characterized in that, The method further includes: Acquire historical data from multiple steering wheel pull operations; A self-learning model is trained based on the historical operation data of the multiple steering wheel pulls. The self-learning model is used to output the compensation coefficient of the proportional compensation model and the adjustment strategy of the direction of the steering wheel pull force.

5. The method according to claim 4, characterized in that, The self-learning model includes neural networks and decision tree algorithms, and the method further includes: The neural network in the self-learning model identifies the pulling direction preference of the vehicle's steering wheel; Based on the pulling direction preference, the decision tree algorithm in the self-learning model makes a decision output that dynamically adjusts the compensation coefficient of the proportional compensation model and the adjustment strategy for the direction of the steering wheel pulling force.

6. The method according to claim 2, characterized in that, The step of determining whether the triggering conditions for dynamic compensation are met based on the door status signal and the steering wheel torque signal includes: Based on the door status signal and the steering wheel torque signal, a preset logic gate circuit or a preset program algorithm is used to determine whether the door status signal and the steering wheel torque signal simultaneously meet the triggering condition.

7. The method according to claim 6, characterized in that, The door status signal includes a door opening angle signal, and the method further includes: The current door status is determined based on the door opening angle signal in the door status signal, and the door status includes a fully open state and a half open state. Based on the door status, a pulling force threshold and / or a compensation coefficient in the proportional compensation model are configured. The pulling force threshold is used to determine whether the steering wheel pulling force is an effective pulling force.

8. The method according to any one of claims 1-7, characterized in that, After the control actuator outputs a dynamic compensation force opposite to the steering wheel pulling force, the method further includes: Based on the door closing signal and / or the signal of the disappearance of pulling force, a stop command is sent to the actuator via the vehicle's controller area network bus, so as to control the actuator to stop outputting the dynamic compensation force through the stop command.

9. An electronic device, characterized in that, include: Memory and processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

10. A vehicle, characterized in that, The vehicle includes a steer-by-wire system and the electronic equipment as described in claim 9.

Images