Automobile steering system and method capable of adaptively adjusting damping coefficient

Abstract

The invention discloses an automobile steering system and method capable of adaptively adjusting a damping coefficient according to driving working conditions, and belongs to the technical field of automobile chassis steering, the automobile steering system comprises a central control unit, and the central control unit is in communication connection with a working condition sensing module, a damping calculation module and an execution adjustment module. According to the method, closed-loop control logic of working condition sensing-parameter calculation-damping adjustment is constructed, active adaptation of the steering system to the driving working condition is achieved through multi-dimensional working condition data real-time collection, optimal damping coefficient dynamic operation and continuous adjustment signal output, any manual intervention of a driver is not needed, and the driving efficiency is improved. The requirement of an intelligent automobile for a steering system is met, and the defect that complex working conditions cannot be automatically adapted in the prior art is overcome; automatic real-time continuous adjustment of steering damping is achieved, sudden road conditions can be rapidly adapted, and the pause feeling caused by traditional manual multi-gear adjustment is eliminated.

Description

Technical Field

[0001] This application belongs to the field of automotive chassis steering technology, and specifically relates to an automotive steering system and method that can adaptively adjust the damping coefficient according to driving conditions. Background Technology

[0002] Currently, the mainstream damping adjustment methods in automotive chassis steering systems are fixed damping or manual multi-position adjustment. The damping coefficient of a fixed damping steering system is set at the factory, and its damping structure is a mechanically fixed design with no dynamic adjustment capability, making it impossible to adjust according to actual driving scenarios. In low-speed maneuvering scenarios, fixed damping can lead to excessive steering resistance, requiring significant effort from the driver; in high-speed driving scenarios, insufficient damping can cause overly sensitive steering, resulting in a floating steering wheel and increasing driving safety risks.

[0003] While manual multi-gear adjustable steering systems support gear switching between different modes, the adjustment process relies on active driver input, and the damping coefficients between gears are discrete values. Their control logic only supports fixed parameter calls for preset gears, lacking real-time calculation and continuous output capabilities, thus failing to achieve continuous real-time adaptation. This adjustment method has significant drawbacks. On one hand, it struggles to handle sudden road conditions, such as encountering a bumpy road at high speed, requiring a rapid increase in damping to stabilize steering, but drivers often lack the time to shift gears. On the other hand, the discreteness of gears leads to jerky damping transitions, affecting the continuity of steering feel. With the development of automotive intelligence, drivers' demands for adaptive steering systems based on driving conditions are constantly increasing. However, current technologies either cannot adjust damping or rely on manual operation with discontinuous adjustments, failing to achieve closed-loop control based on real-time perception of driving conditions, dynamic calculation of optimal damping, and continuous output of adjustment signals. This makes it difficult to balance handling and comfort in different driving scenarios and cannot meet the needs of intelligent vehicles for proactive, intervention-free steering system adaptation. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a vehicle steering system and method that can adaptively adjust the damping coefficient according to driving conditions, enabling the steering system to actively adapt to driving conditions without any manual intervention from the driver. This meets the requirements of intelligent vehicles for steering systems and overcomes the shortcomings of existing technologies that cannot automatically adapt to complex conditions.

[0005] In a first aspect, embodiments of this application provide a vehicle steering system capable of adaptively adjusting the damping coefficient according to driving conditions, including a central control unit, which is communicatively connected to: The working condition perception module is used to collect multi-dimensional working condition data such as vehicle speed, steering angle, steering angular velocity and road vibration acceleration in real time during vehicle operation. The damping calculation module has a built-in multi-parameter coupled damping algorithm. It takes multi-dimensional working condition data as input and generates the optimal damping coefficient under the current working condition in real time through preset formulas. The adjustment module, consisting of an electromagnetic damping regulator, receives a control signal from the central control unit corresponding to the optimal damping coefficient. By changing the magnitude of the electromagnetic coil current, it adjusts the cross-sectional area of ​​the oil passage inside the electromagnetic damping regulator in real time, thereby achieving automatic, real-time, and continuous adjustment of the damping coefficient of the vehicle steering system.

[0006] In some embodiments of this application, the working condition sensing module includes a Hall effect vehicle speed sensor, a non-contact photoelectric steering angle sensor, and a piezoelectric acceleration sensor. The data acquisition process of the operating condition sensing module includes: The Hall effect vehicle speed sensor detects the rotation of the wheel axle gear ring and outputs a pulse signal proportional to the vehicle speed to obtain real-time vehicle speed data. The rotation of the steering wheel shaft grating disk is detected by a non-contact photoelectric steering angle sensor, which outputs an analog signal and simultaneously collects steering angle and steering angular velocity data. The vertical vibration of the vehicle frame is detected by a piezoelectric accelerometer, and the road surface smoothness is judged based on the magnitude of the vibration acceleration, thus collecting road surface condition data. The data collected by the three types of sensors are transmitted to the central control unit through their respective transmission links.

[0007] In some embodiments of this application, the signal transmission and synchronization mechanism of the working condition sensing module includes: Hall effect vehicle speed sensors transmit pulse signals via a bus, non-contact photoelectric steering angle sensors transmit analog signals via a dedicated bus, and piezoelectric accelerometers transmit vibration signals via analog signal lines. Each transmission link is set independently to avoid signal interference. Establish a multi-source signal synchronization calibration mechanism, using the system clock of the central control unit as a reference, to align the signal acquisition timestamps of different sensors and eliminate signal transmission delay differences; Set a threshold for monitoring signal transmission quality. When signal loss, distortion, or transmission rate failure is detected, the signal retransmission or backup acquisition mode will be automatically activated.

[0008] In some embodiments of this application, the multi-parameter coupled damping algorithm design of the damping calculation module includes: Using vehicle speed, steering angular velocity, and road vibration acceleration as input variables, the formula C=K1× v +K2× ω +K3× a The computational model is constructed using +C0, where C is the optimal damping coefficient, and K1, K2, and K3 are weighting coefficients. v For vehicle speed, ω For the steering angular velocity, a C0 represents the road surface vibration acceleration, and C0 is the basic damping coefficient. Multi-dimensional operating condition data is read at fixed time intervals, and the optimal damping coefficient is calculated by substituting the data into the formula. The output is a continuous damping coefficient value covering a wide range.

[0009] In some embodiments of this application, the optimization mechanism of the multi-parameter coupled damping algorithm includes: Establish a working condition data sample library and continuously accumulate multi-dimensional working condition data and corresponding optimal damping coefficient feedback data under different driving scenarios; Machine learning algorithms are used to train and update the data in the working condition data sample library, and the values ​​of weight coefficients and basic damping coefficients are dynamically adjusted. A working condition similarity matching mechanism is introduced. When a new working condition is detected, the optimized parameters of the same working condition in the working condition data sample library are quickly matched, thereby shortening the calculation response time of the optimal damping coefficient.

[0010] In some embodiments of this application, the signal conversion and output mechanism of the central control unit includes: The optimal damping coefficient generated by the receiving damping calculation module is used to establish a linear mapping relationship between the optimal damping coefficient and the duty cycle of the pulse width modulation signal. The optimal damping coefficient is converted into a pulse width modulation signal with the corresponding duty cycle through the internal signal processing unit; An anti-interference transmission strategy is adopted to output the pulse width modulation signal to the execution and regulation module, and a signal transmission verification mechanism is established simultaneously to provide real-time feedback on the signal reception status of the execution and regulation module.

[0011] In some embodiments of this application, the working mechanism of the electromagnetic damping regulator that executes the adjustment module includes: It receives the pulse width modulation signal output by the central control unit, converts the signal into a current proportional to the duty cycle through the internal drive circuit, and passes it into the electromagnetic coil. The magnetic field strength generated by the current changes dynamically with the magnitude of the current. The magnetic field exerts an axial attraction on the internal piston, driving the piston to make continuous displacement motion along the inner wall of the outer shell. During piston displacement, the effective flow cross-sectional area of ​​the oil passage is changed synchronously. Through the linkage control of magnetic field strength, piston displacement and passage cross-sectional area, the dynamic adaptation of the steering system damping coefficient is achieved.

[0012] In some embodiments of this application, the damping adjustment logic of the electromagnetic damping regulator includes: The piston displacement is positively correlated with the current flowing through the electromagnetic coil. The larger the current, the longer the piston displacement distance and the smaller the cross-sectional area of ​​the oil passage. The cross-sectional area of ​​the oil passage is inversely related to the oil flow resistance. The smaller the cross-sectional area of ​​the passage, the greater the oil flow resistance and the higher the damping coefficient of the steering system. By employing a multi-level linear correlation design involving current, displacement, cross-sectional area, resistance, and damping coefficient, the optimal damping coefficient is precisely determined, enabling continuous damping adjustment.

[0013] In some embodiments of this application, the adaptive damping adjustment method of the system includes: Multi-dimensional operating condition data is acquired in real time, and the multi-dimensional operating condition data is received and stored by the central control unit at fixed time intervals. The optimal damping coefficient corresponding to the current working condition is generated by calculating multi-dimensional working condition data through a multi-parameter coupled damping algorithm. The optimal damping coefficient is converted into a pulse width modulation signal and transmitted to the execution adjustment module to drive the electromagnetic damping regulator to adjust the cross-sectional area of ​​the oil passage; The system receives piston displacement and hydraulic pressure data from the control module in real time, and performs linkage verification by combining the latest multi-dimensional operating condition data collected synchronously by the operating condition sensing module. Based on the real-time verification deviation, the weight coefficient of the multi-parameter coupled damping algorithm and the duty cycle of the pulse width modulation signal are dynamically corrected, forming a closed-loop adjustment process of data acquisition, coefficient calculation, damping adjustment and feedback correction, to ensure that the damping coefficient is adapted to the driving conditions in real time.

[0014] In some embodiments of this application, the system further includes a fault diagnosis and protection module, the working mechanism of which includes: Real-time monitoring of the working status of each module, detection of sensor signal integrity, central control unit operation status and electromagnetic damping regulator execution status; When a fault is detected, the system automatically determines the type and severity of the fault, issues a corresponding fault alarm signal, and records the time of the fault occurrence, operating parameters, and fault code. When the fault protection mode is activated, the central control unit switches to the basic damping coefficient C0 according to the fault type.

[0015] Secondly, embodiments of this application provide a vehicle steering method that can adaptively adjust the damping coefficient according to driving conditions, applied to a vehicle steering system, including the following steps: S1: Real-time acquisition of multi-dimensional operating condition data, which is received and stored by the central control unit at fixed time intervals; S2: The multi-parameter coupled damping algorithm is used to calculate the multi-dimensional working condition data and generate the optimal damping coefficient corresponding to the current working condition. S3: Convert the optimal damping coefficient into a pulse width modulation signal and transmit it to the execution adjustment module to drive the electromagnetic damping regulator to adjust the cross-sectional area of ​​the oil passage; S4: Receives piston displacement and oil pressure data from the execution adjustment module in real time, combines them with the latest multi-dimensional operating condition data synchronously collected by the operating condition sensing module for linkage verification, dynamically corrects the weight coefficients of the multi-parameter coupled damping algorithm and the duty cycle of the pulse width modulation signal, and forms a closed-loop adjustment process.

[0016] Compared with the prior art, this application has the following advantages: 1. Construct a closed-loop control logic of working condition perception, parameter calculation and damping adjustment. Through real-time acquisition of multi-dimensional working condition data, dynamic calculation of the optimal damping coefficient and continuous adjustment signal output, the steering system can actively adapt to driving conditions without any manual intervention from the driver. This meets the needs of intelligent vehicles for steering systems and solves the shortcomings of existing technologies that cannot automatically adapt to complex working conditions.

[0017] 2. It achieves automatic, real-time, and continuous adjustment of steering damping. The working condition sensing module captures changes in driving status, and the damping calculation and execution adjustment response is rapid, which can quickly adapt to sudden road conditions. At the same time, the damping coefficient is continuously output over a wide range, eliminating the jerking feeling caused by traditional manual multi-gear adjustment, improving the smoothness of steering feel, and effectively solving the problems of existing technology relying on manual operation, insufficient ability to cope with sudden road conditions, and discontinuous damping switching.

[0018] 3. Dynamically optimize the steering damping characteristics under different vehicle speed scenarios. When driving at low speeds, automatically reduce the damping coefficient to reduce steering resistance, making maneuvering and other operations easier. When driving at high speeds, actively increase the damping coefficient to reduce steering sensitivity and eliminate steering wheel floatiness. While ensuring steering comfort, improve high-speed driving safety, and successfully solve the problems of difficult low-speed steering and floatiness at high speeds in existing fixed damping systems.

[0019] 4. The fully automated damping adjustment process significantly reduces the driver's workload, eliminating the need for the driver to be distracted by gear shifting. This allows the driver to focus more on observing and judging the driving environment, reducing safety hazards caused by distracted operation, indirectly reducing the risk of steering-related accidents, and further improving overall driving safety and driving experience.

[0020] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This invention illustrates the collaborative logic and data flow of each module provided by the present invention; Figure 2 A schematic diagram of the overall structure provided by the present invention is shown; Figure 3 A partially enlarged view of the working condition sensing module provided by the present invention is shown. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] First, it should be noted that after analyzing the practical application of existing automotive steering systems, it was found that the damping coefficient of traditional fixed-damping steering systems is set at the factory and cannot be adjusted according to actual driving scenarios. This results in difficult steering at low speeds and a feeling of instability at high speeds, increasing driving safety risks. Manual multi-position adjustable steering systems require manual operation by the driver, and the damping coefficients between positions are discrete values, making them unable to cope with sudden road conditions. The damping switching also results in a jerky feeling, affecting the continuity of steering feel. These problems combined make it impossible to balance the handling and comfort of the steering system, making it difficult to meet the core requirement of intelligent vehicles for steering systems that actively adapt and require no intervention.

[0025] This invention constructs a car steering system that can adaptively adjust the damping coefficient according to driving conditions. The system is centered on a central control unit and connects a condition sensing module, a damping calculation module, an execution adjustment module, and a fault diagnosis and protection module to achieve end-to-end adaptive damping adjustment. The specific implementation methods of each module are described in detail below with reference to the embodiments.

[0026] refer to Figure 2 This diagram illustrates the overall structure of the system provided in this embodiment. The system includes a central control unit and, through communication with it, a condition sensing module, a damping calculation module, an execution adjustment module, and a fault diagnosis and protection module. These modules work together to achieve complete functions of data acquisition, coefficient calculation, damping adjustment, and fault protection. The specific implementation method is as follows: The operating condition perception module collects and reliably transmits multi-dimensional operating condition data during vehicle operation in real time, providing an accurate data foundation for subsequent calculation of the optimal damping coefficient.

[0027] It should be noted that the driving conditions of a car are complex and varied, involving dynamic changes in vehicle speed, differences in steering operation, and varying road surface smoothness. These operating parameters directly affect the damping requirements of the steering system. The accuracy, real-time performance, and transmission stability of data acquisition are prerequisites for achieving adaptive adjustment. Therefore, this module needs to solve the above problems through collaborative acquisition of multiple types of sensors and a dedicated transmission mechanism.

[0028] The working condition perception module includes three types of sensors: Hall effect vehicle speed sensor, non-contact photoelectric steering angle sensor, and piezoelectric acceleration sensor. Each sensor is responsible for collecting different working condition parameters. The selection and installation method of each sensor have been precisely matched to ensure the accuracy of data acquisition and environmental adaptability.

[0029] The Hall effect vehicle speed sensor used is the DS-200H model. It outputs pulse signals by sensing the rotation of the gear ring on the wheel axle. The pulse frequency is proportional to the vehicle speed, thus obtaining real-time vehicle speed data. The sensor is mounted on the outside of the front wheel axle and fixed to the frame with M8×20 bolts. The gap between the sensor probe and the gear ring is strictly controlled within 0.5 to 1 mm to ensure that the signal acquisition error is ≤0.5 km / h. Its signal output terminal is connected to the J1939 signal input interface of the central control unit via a CAN bus, with a data transmission rate of 500 kbps, enabling it to quickly capture dynamic changes in vehicle speed and provide timely feedback even in scenarios with drastic speed fluctuations.

[0030] The non-contact photoelectric steering angle sensor uses the SAS-300 model, which integrates a light-emitting diode and a photoresistor. It outputs a 0-5V analog signal by detecting the rotation of a grating disk on the steering shaft, simultaneously acquiring steering angle and steering angular velocity data. The sensor's steering angle acquisition range covers -900° to +900° with an accuracy of ±0.1°, and its steering angular velocity acquisition range is 0-500° / s with an accuracy of ±1° / s, accurately capturing subtle changes in steering operation. The non-contact photoelectric steering angle sensor is installed at the connection between the steering shaft and the steering gear, fixed to the shaft via a spline. The housing is connected to the steering gear housing using a 6061 aluminum alloy bracket, effectively preventing installation misalignment due to vibration and ensuring the stability of the acquired data. The signal output is connected to the central control unit via a LIN bus, with a data update frequency of 100Hz, enabling real-time tracking of the dynamic process of steering operations.

[0031] The piezoelectric accelerometer selected is the ACC-500 model. It determines road surface smoothness by sensing the vertical vibration acceleration of the vehicle frame; a higher vibration acceleration indicates a bumpier road surface, thus collecting road condition data. The sensor's vibration acceleration acquisition range is -5g to +5g, with an accuracy of ±0.01g, enabling it to sensitively capture differences in road surface roughness. The sensor is installed at the connection point between the lower control arm of the front suspension and the vehicle frame, secured to the lower control arm with an M6×15 thread. The sensor's sensitive axis is perpendicular to the ground, ensuring accurate acquisition of vertical vibration signals. The signal output is connected to the analog input interface of the central control unit via an RVVP2×0.5 analog signal cable. The signal sampling frequency is 100Hz, allowing for rapid response to changes in road surface roughness and timely feedback of complex road condition information.

[0032] Data collected by the three types of sensors needs to be transmitted to the central control unit through corresponding transmission links. The Hall effect vehicle speed sensor transmits pulse signals through the CAN bus, the non-contact photoelectric steering angle sensor transmits analog signals through the LIN bus, and the piezoelectric accelerometer transmits vibration signals through analog signal lines. Each transmission link is set independently to avoid interference between different types of signals and ensure the purity of signal transmission.

[0033] To ensure time consistency of multi-source signals, the operating condition perception module establishes a multi-source signal synchronization calibration mechanism. Using the system clock of the central control unit as a reference, it aligns the timestamps of signal acquisition from different sensors, eliminating signal transmission delay differences. This ensures that vehicle speed, steering angle, steering angular velocity, and road vibration acceleration data can accurately match the same driving moment, providing a time-synchronized data foundation for the subsequent accurate calculation of the optimal damping coefficient. Simultaneously, a signal transmission quality monitoring threshold is set to detect the signal transmission status in real time. When signal loss, distortion, or insufficient transmission rate is detected, signal retransmission or backup acquisition mode is automatically activated to ensure a continuous supply of operating condition data. This prevents data interruptions from affecting normal system operation and ensures that the system can stably acquire operating condition data even in complex electromagnetic environments.

[0034] refer to Figure 3 The image shows a magnified view of a portion of the operating condition perception module. It should be noted that the sensor installation of the operating condition perception module must be adapted to the steering system structure of different vehicle models to ensure stable installation without affecting the vehicle's original functions; the sensors must have good environmental adaptability during operation, maintaining stable data acquisition accuracy under different temperature and humidity conditions; furthermore, the data collected by the sensors needs to undergo preliminary screening to remove obvious extreme interference signals, further improving data quality and laying the foundation for the reliable operation of subsequent modules.

[0035] The damping calculation module is based on the multi-dimensional operating condition data collected by the operating condition sensing module. It uses a built-in multi-parameter coupled damping algorithm to perform real-time calculations and generate the optimal damping coefficient under the current operating condition, providing a precise adjustment basis for the execution adjustment module.

[0036] It should be noted that the requirements for steering damping vary significantly under different driving conditions. When maneuvering at low speeds, smaller damping is needed to achieve light steering, while larger damping is needed to ensure steering stability during high-speed cruising. On bumpy roads, dynamic adjustment of damping is required to cope with sudden situations. A single parameter or fixed algorithm cannot meet the precise adaptation to complex conditions. Therefore, this module needs to solve the above problems through multi-parameter coupling algorithms and dynamic optimization mechanisms.

[0037] The multi-parameter coupled damping algorithm of the damping calculation module is integrated into the central control unit. The hardware structure of the central control unit is specially designed, with a waterproof and dustproof casing, achieving an IP67 protection rating. Made of ABS engineering plastic, it can withstand the harsh working environment of the vehicle chassis. The internal core chip is a 32-bit STM32H743 microcontroller with a main frequency of up to 480MHz, possessing powerful data processing capabilities to meet the real-time calculation requirements of multiple parameters at 100Hz, ensuring the high efficiency of the algorithm. It also integrates a CAN / LIN bus interface, a 12-bit ADC analog input interface, and a 16-bit resolution PWM output interface, used to connect to the vehicle speed sensor, steering angle sensor, road surface smoothness sensor, and actuator adjustment module, respectively, enabling flexible input and output of various signal types. The power supply uses the vehicle's 12V power supply, and a voltage regulator circuit stabilizes the output voltage to 5V and 3.3V, providing stable power to the chip and peripheral circuits, ensuring continuous and reliable operation of all components.

[0038] The multi-parameter coupled damping algorithm uses vehicle speed, steering angular velocity, and road vibration acceleration as core input variables. It constructs a computational model using the formula C=K1×V+K2×ω+K3×a+C0. The formula includes the optimal damping coefficient C, weighting coefficients K1, K2, K3, and the basic damping coefficient C0. The weighting coefficients are calibrated using a large amount of real vehicle test data, which can quantify the influence of different input variables on the damping coefficient. Among them, K1=0.08 N·s / (m·km / h), K2=0.02 N·s / (m·° / s), K3=1.5 N·s / (m·g), and C0=0.1 N·s / m.

[0039] The algorithm is trained and generated based on a large amount of real-vehicle test data, covering various operating conditions such as vehicle speed 0–120 km / h, steering angle -600°–+600°, and road vibration acceleration 0–3g. This ensures that the algorithm can accurately output the optimal damping coefficient under different driving scenarios. The algorithm runs in real time through a microcontroller, completing data reading and damping coefficient calculation every 10 ms, and outputting a continuous damping coefficient value covering the range of 0.1–10 N·s / m. This avoids the discreteness problem of traditional manual multi-level adjustment and achieves seamless and continuous adjustment of the damping coefficient.

[0040] To improve the adaptability and response speed of the algorithm, the damping calculation module has established a working condition data sample library, continuously accumulating multi-dimensional working condition data and corresponding optimal damping coefficient feedback data under different driving scenarios. The sample library covers typical scenarios such as low-speed vehicle maneuvering, high-speed cruising, and bumpy roads, as well as various complex working condition combinations, providing rich data support for algorithm optimization.

[0041] Machine learning algorithms are used to train and update the data in the working condition data sample library, and the values ​​of weight coefficients and basic damping coefficients are dynamically adjusted so that the algorithm can continuously adapt to the steering characteristics and driving environment changes of different vehicle models, and continuously improve the accuracy of damping coefficient calculation.

[0042] By introducing a working condition similarity matching mechanism, when a new working condition is detected, the working condition data sample library is quickly retrieved to match the optimized parameters of similar working conditions, shortening the calculation response time of the optimal damping coefficient, ensuring that adjustment commands can be quickly output under sudden working conditions, and improving the system's adaptability to complex working conditions.

[0043] It should be noted that the operation frequency of the damping calculation module is precisely matched with the data acquisition frequency of the operating condition sensing module to ensure real-time data reception and timely calculation, achieving synchronous response to changes in operating conditions and damping adjustment. During the algorithm calculation process, the validity of the input data needs to be verified, and invalid data needs to be eliminated to avoid affecting the calculation results, ensuring the reliability of the output damping coefficient. In addition, the adjustment of the weighting coefficient and the basic damping coefficient needs to establish a constraint mechanism to ensure that the adjustment range is within a safe and reasonable range and does not affect the stability and handling safety of the steering system.

[0044] As the core hub of the system, the central control unit, in addition to integrating the hardware structure and algorithm of the damping calculation module, is also responsible for receiving the data collected by the operating condition sensing module, outputting control signals to the execution and adjustment module, and realizing signal conversion and transmission verification functions.

[0045] It should be noted that the central control unit needs to adapt to different types of input and output signals to ensure the accuracy and real-time performance of data transmission. At the same time, a reliable signal conversion mechanism needs to be established to convert the optimal damping coefficient into a control signal that can be recognized by the execution and adjustment module. Therefore, this unit needs to achieve the above functions through multi-type interface integration and signal processing mechanism.

[0046] The signal conversion and output mechanism of the central control unit includes three stages: signal conversion, anti-interference transmission, and verification feedback. In the signal conversion stage, the optimal damping coefficient generated by the damping calculation module is received, and a linear mapping relationship is established between the optimal damping coefficient and the duty cycle of the PWM signal. The duty cycle range of the PWM signal is 0% to 100%, which precisely corresponds linearly to the damping coefficient range of 0.1 to 10 N·s / m. For every 1% increase in the duty cycle, the damping coefficient increases by 0.099 N·s / m. The internal signal processing unit converts the optimal damping coefficient into a PWM signal with the corresponding duty cycle, ensuring the accuracy and real-time performance of the signal conversion and providing precise control commands to the control module.

[0047] In the anti-interference transmission stage, an anti-interference transmission strategy is adopted to output the PWM signal to the execution adjustment module. Through signal encoding and encryption processing, the interference of the vehicle's electromagnetic environment on signal transmission is reduced, ensuring the complete transmission of control commands and avoiding abnormal damping adjustment due to signal interference.

[0048] In the verification and feedback phase, a signal transmission verification mechanism is established synchronously to receive the signal reception status feedback from the execution adjustment module in real time. When an abnormal signal transmission is detected, the signal is automatically resent to ensure the reliable transmission of adjustment commands, forming a closed-loop verification of signal transmission and improving the stability of the system.

[0049] The adjustment module receives control signals from the central control unit and adjusts the damping coefficient of the steering system through the mechanical action of the electromagnetic damping adjuster to achieve the precise implementation of the optimal damping coefficient.

[0050] It should be noted that the response speed and adjustment accuracy of the adjustment module directly affect the handling feel of the steering system. The working mechanism and correlation logic of the electromagnetic damping adjuster are the key to achieving continuous and smooth adjustment. Therefore, this module needs to solve the above problems through the linkage control of magnetic field, displacement, and cross-sectional area and the design of multi-level linear correlation.

[0051] The core component of the adjustment module is an electromagnetic damping adjuster, installed at the connection between the steering gear tie rod and the vehicle frame. Its structure includes a housing, an electromagnetic coil, an oil passage, a piston, and a return spring. The housing is made of 45# steel, possessing sufficient strength and rigidity to withstand the forces and vibrations during steering system operation. The electromagnetic coil is wound with QZ-2 / 155 enameled wire, with 500 turns, providing good electromagnetic conversion efficiency and heat dissipation performance. The oil passage has a diameter of 8mm and passes through the piston, which is made of 304 stainless steel. It slides against the inner wall of the housing, with a clearance controlled between 0.02 and 0.03mm to ensure smooth piston movement and sealing. The return spring has a stiffness coefficient of 5N / mm, providing a stable return force. The outer casing is connected to the Φ20×100 steering gear tie rod and the chassis at both ends via flanges, ensuring a secure and reliable connection. It is filled with ATFIII hydraulic oil, which has a viscosity of 37 mm² / s at 40℃, exhibiting excellent viscosity characteristics and temperature stability to ensure stable damping adjustment at various operating temperatures. An electromagnetic coil is wound on the outside of the casing, 5 mm away from the piston, ensuring effective magnetic field drive of the piston.

[0052] The working mechanism of the electromagnetic damping regulator includes three stages: signal conversion, magnetic field drive, and cross-sectional area adjustment. In the signal conversion stage, the electromagnetic damping regulator receives the PWM signal output from the central control unit, converts the signal into a current proportional to the duty cycle through the internal drive circuit, and passes it into the electromagnetic coil. The current range is 0A to 2A, reaching 2A when the duty cycle is 100% and 0A when the duty cycle is 0%.

[0053] In the magnetic field drive stage, the magnetic field strength generated by the current changes dynamically with the magnitude of the current. The magnetic field generates an axial attraction on the internal piston, driving the piston to make continuous displacement motion along the inner wall of the outer shell. The piston movement distance ranges from 0 to 5 mm. The larger the current, the stronger the magnetic field strength, and the longer the piston displacement distance.

[0054] In the cross-sectional area adjustment stage, the effective flow cross-sectional area of ​​the oil passage is changed synchronously during the piston displacement. The greater the piston movement distance, the smaller the cross-sectional area of ​​the oil passage. Through the linkage control of magnetic field strength, piston displacement and passage cross-sectional area, the dynamic adaptation of the steering system damping coefficient is achieved.

[0055] The damping adjustment logic of the electromagnetic damping adjuster is based on a multi-level linear correlation design. The piston displacement is positively correlated with the current flowing through the electromagnetic coil; the larger the current, the longer the piston displacement and the smaller the cross-sectional area of ​​the hydraulic passage. Conversely, the cross-sectional area of ​​the hydraulic passage is inversely correlated with the hydraulic flow resistance; the smaller the cross-sectional area, the greater the hydraulic flow resistance and the higher the damping coefficient of the steering system. Through the multi-level linear correlation design of current, displacement, cross-sectional area, resistance, and damping coefficient, the optimal damping coefficient is accurately converted into the actual damping effect, achieving continuous damping adjustment without jerking and improving the smoothness of steering feel.

[0056] The return spring is used to return the piston to its initial position when the electromagnetic coil is de-energized. At this time, the cross-sectional area of ​​the oil passage is at its maximum, and the damping coefficient is maintained at the basic damping coefficient of 0.1 N·s / m. This ensures that the system still has basic steering function after power failure, protects driving safety, and avoids steering function failure due to system malfunction.

[0057] It should be noted that the internal hydraulic oil of the electromagnetic damping regulator needs to be changed regularly to ensure its viscosity and cleanliness, and to prevent oil deterioration or impurities from clogging the oil passages and affecting the damping adjustment effect. The fit clearance between the piston and the inner wall of the housing needs to be strictly controlled and regularly inspected and maintained to prevent excessive clearance from causing oil leakage or a decrease in damping adjustment accuracy. In addition, the electromagnetic coil needs to have good insulation performance and heat dissipation capacity to ensure long-term stable operation and to prevent the actuator adjustment module from malfunctioning due to coil overheating or insulation damage.

[0058] To clearly demonstrate the system's operation in different typical scenarios, the following details the process using three scenarios: low-speed vehicle maneuvering, high-speed cruising, and bumpy road conditions. Under low-speed maneuvering conditions, with vehicle speed ≤ 30 km / h, steering angular velocity = 50° / s, and road vibration acceleration = 0.1g, the working condition perception module's vehicle speed sensor first collects vehicle speed data at 20 km / h and outputs a corresponding pulse signal; the steering angle sensor collects steering angular velocity data at 50° / s and outputs a 0.8V analog signal; and the road surface smoothness sensor collects road vibration acceleration data at 0.1g and outputs a 0.2V analog signal. These three signals are transmitted to the central control unit via the CAN bus, LIN bus, and analog signal line, respectively. After receiving the data, the central control unit calculates the optimal damping coefficient using a multi-parameter coupled damping algorithm. Substituting this into the formula C = 0.08 × 20 + 0.02 × 50 + 1.5 × 0.1 + 0.1, the damping coefficient is found to be 2.85 N·s / m, falling within the range of 0.1 to 2 N·s / m. The optimal damping coefficient is then converted into a PWM signal with a corresponding duty cycle of approximately 27.8% (2.85-0.1) / 0.099). This PWM signal with a 27.8% duty cycle is output to the control module. The electromagnetic coil of the electromagnetic damping regulator is supplied with a current of approximately 0.56A, generating a magnetic field that attracts the piston to move approximately 1.4mm, increasing the cross-sectional area of ​​the hydraulic passage to 6mm². At this point, the driver turns the steering wheel, and the steering linkage moves the piston, allowing the hydraulic fluid to flow through the larger cross-sectional area of ​​the passage. This reduces resistance and lowers the steering effort to approximately 40N, enabling easy maneuvering. The steering resistance is reduced by 40%–60% compared to existing fixed damping systems, solving the problem of high effort at low speeds in existing fixed damping systems.

[0059] Under high-speed cruising conditions, with a vehicle speed ≥ 80 km / h, a steering angular velocity of 10° / s, and a road vibration acceleration of 0.2g, the various sensors in the condition sensing module collect data on vehicle speed at 100 km / h, steering angular velocity at 10° / s, and road vibration acceleration at 0.2g, and transmit this data to the central control unit. The central control unit calculates the optimal damping coefficient using an algorithm, substituting it into the formula C = 0.08 × 100 + 0.02 × 10 + 1.5 × 0.2 + 0.1, resulting in a damping coefficient of 8.6 N·s / m. This damping coefficient falls within the range of 5–10 N·s / m. It is then converted into a PWM signal with a corresponding duty cycle: duty cycle = (8.6 - 0.1) / 0.099 ≈ 85.9%, and outputs a PWM signal with a duty cycle of 85.9% to the execution adjustment module. The electromagnetic coil is supplied with a current of approximately 1.72A, which attracts the piston to move by about 4.3mm, reducing the cross-sectional area of ​​the oil passage to 1.5mm². When the steering linkage moves the piston, the oil flow resistance increases, the steering damping increases, and the steering wheel rotation sensitivity decreases by 30% to 50%. The driver needs to apply about 70N of force to turn the steering wheel, avoiding oversteering caused by accidental hand movements at high speeds, solving the problem of high-speed drifting in the existing system, and improving driving safety.

[0060] Under bumpy road conditions, with a vehicle speed of 60 km / h, a steering angular velocity of 20° / s, and a road vibration acceleration of 2g, the road surface smoothness sensor accurately detects severe road bumps, quickly collects the 2g vibration acceleration data, and transmits it to the central control unit. The central control unit responds rapidly, calculating the optimal damping coefficient in real time using an algorithm, quickly adjusting the duty cycle of the PWM signal, and outputting it to the execution adjustment module. The electromagnetic damping regulator completes current adjustment and piston displacement within 50ms, promptly changing the cross-sectional area of ​​the hydraulic passage, increasing the steering system damping coefficient, stabilizing steering feel, preventing loss of steering control due to road bumps, and ensuring vehicle handling stability under complex road conditions.

[0061] The system's adaptive damping adjustment method achieves real-time and accurate adaptation of the damping coefficient to driving conditions through a closed-loop process of data acquisition, coefficient calculation, damping adjustment, and feedback correction.

[0062] The specific process is as follows: First, the operating condition sensing module acquires multi-dimensional operating condition data in real time, which is received and stored by the central control unit at fixed time intervals to ensure the continuity and integrity of the data. Second, the damping calculation module calls the multi-parameter coupled damping algorithm to calculate the multi-dimensional operating condition data and generate the optimal damping coefficient corresponding to the current operating condition. Then, the central control unit converts the optimal damping coefficient into a PWM signal and transmits it to the execution adjustment module to drive the electromagnetic damping adjuster to adjust the cross-sectional area of ​​the oil passage, thereby achieving damping adjustment. Finally, the central control unit receives the piston displacement data and oil pressure data fed back by the execution adjustment module in real time, and performs linkage verification in conjunction with the latest multi-dimensional operating condition data synchronously collected by the operating condition sensing module. Based on the real-time verification deviation, the weight coefficient of the multi-parameter coupled damping algorithm and the duty cycle of the PWM signal are dynamically corrected to form a complete closed-loop adjustment process. This closed-loop process can continuously optimize the damping coefficient output, ensuring that the damping coefficient of the steering system can quickly adapt to the needs under different driving conditions, taking into account both steering comfort and handling stability. Real-vehicle testing has verified that the closed-loop adjustment process significantly optimizes the real-time and continuous adjustment of the steering system, improves steering feel smoothness by more than 80%, increases driver focus by 25%, and reduces the risk of vehicle steering accidents by 30% compared to existing technologies.

[0063] The fault diagnosis and protection module monitors the working status of each module in the system in real time. When a fault is detected, the protection mechanism is activated in a timely manner to ensure that the vehicle's steering function is not seriously affected and to ensure driving safety.

[0064] It should be noted that steering system failures during vehicle operation may pose safety risks. Therefore, the fault diagnosis and protection module must have the ability to quickly identify faults, accurately determine faults, and provide reliable protection responses to avoid steering failure or severe performance degradation due to module failure.

[0065] The fault diagnosis and protection module's working mechanism includes three stages: status monitoring, fault determination, and protection response. In the status monitoring stage, the operating status of each module is monitored in real time, including the integrity of sensor signals from the condition sensing module, the operational status of the central control unit, and the execution status of the electromagnetic damping regulator. The module continuously collects operating parameters and feedback signals to ensure a comprehensive understanding of the system's operating status.

[0066] In the fault diagnosis stage, the monitoring data is analyzed according to the preset fault diagnosis rules. When a fault is detected, the fault type and severity are automatically determined. Fault types include sensor faults, central control unit operation faults, electromagnetic damping regulator execution faults, etc. The severity is divided into minor faults, general faults, and serious faults. At the same time, the corresponding fault alarm signal is issued, and the fault occurrence time, operating parameters, and fault codes are recorded to provide detailed basis for subsequent maintenance and facilitate rapid fault location and troubleshooting.

[0067] During the protection response phase, the fault protection mode is activated. The central control unit switches to a basic damping coefficient of 0.1 N·s / m based on the fault type. The basic damping coefficient ensures that the vehicle has basic steering function and avoids excessively sensitive or heavy steering due to abnormal damping. This ensures that the driver can control the vehicle to drive safely to the repair location and reduces the safety risks caused by the fault.

[0068] It should be noted that the fault judgment rules of the fault diagnosis and protection module must be formulated based on a large amount of real vehicle test data and fault cases to ensure the accuracy and timeliness of fault identification; fault alarm signals must be clearly displayed to the driver through the vehicle's instrument panel or a dedicated warning device, so that the driver can be aware of the system status in a timely manner and take appropriate measures; in addition, fault record data must be stored in a non-volatile storage unit, so that it will not be lost even if the vehicle is powered off, making it convenient for maintenance personnel to retrieve and analyze, and improving maintenance efficiency.

[0069] refer to Figure 1 This embodiment illustrates the collaborative logic and data flow of each module. The working condition sensing module collects multi-dimensional working condition data and transmits it to the central control unit. The central control unit schedules the damping calculation module to generate the optimal damping coefficient and then transmits the converted control signal to the execution adjustment module to achieve damping adjustment. The feedback data from the execution adjustment module and the latest data from the working condition sensing module are used together for closed-loop correction. The fault diagnosis and protection module monitors the status of each module throughout the process and activates the protection mechanism in case of a fault, forming a closed-loop process of data input, processing, adjustment, feedback, and protection.

[0070] It should be noted that the hardware selection for each module of the system must be strictly adapted to the vehicle's working environment and performance requirements to ensure long-term stable operation. After real-vehicle testing, the system can work stably in various scenarios, including vehicle speeds of 0-120km / h and road surfaces such as paved roads, gravel roads, and speed bumps. The system's software algorithm can be customized and adjusted according to the steering characteristics of different vehicle models to improve the system's versatility and adaptability. In addition, the system supports functional expansion and can add functions such as working condition scene recognition and personalized damping coefficient memory to meet the needs of different users and the trend of automotive intelligence development.

[0071] Based on the same inventive concept, this application also provides a vehicle steering method that can adaptively adjust the damping coefficient according to driving conditions, applied to a vehicle steering system, including the following steps: S1: Real-time acquisition of multi-dimensional operating condition data, which is received and stored by the central control unit at fixed time intervals; S2: The multi-parameter coupled damping algorithm is used to calculate the multi-dimensional working condition data and generate the optimal damping coefficient corresponding to the current working condition. S3: Convert the optimal damping coefficient into a pulse width modulation signal and transmit it to the execution adjustment module to drive the electromagnetic damping regulator to adjust the cross-sectional area of ​​the oil passage; S4: Receives piston displacement and oil pressure data from the execution adjustment module in real time, combines them with the latest multi-dimensional operating condition data synchronously collected by the operating condition sensing module for linkage verification, dynamically corrects the weight coefficients of the multi-parameter coupled damping algorithm and the duty cycle of the pulse width modulation signal, and forms a closed-loop adjustment process.

[0072] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A vehicle steering system capable of adaptively adjusting the damping coefficient according to driving conditions, comprising a central control unit, characterized in that, The central control unit has the following communication connections: The working condition perception module is used to collect multi-dimensional working condition data such as vehicle speed, steering angle, steering angular velocity and road vibration acceleration in real time during vehicle operation. The damping calculation module has a built-in multi-parameter coupled damping algorithm. It takes the multi-dimensional working condition data as input and generates the optimal damping coefficient under the current working condition in real time through a preset formula. The adjustment module, consisting of an electromagnetic damping regulator, receives a control signal from the central control unit corresponding to the optimal damping coefficient. By changing the magnitude of the electromagnetic coil current, it adjusts the cross-sectional area of ​​the oil passage inside the electromagnetic damping regulator in real time, thereby achieving automatic, real-time, and continuous adjustment of the damping coefficient of the vehicle steering system.

2. The automotive steering system according to claim 1, characterized in that, The working condition sensing module includes a Hall-type vehicle speed sensor, a non-contact photoelectric steering angle sensor, and a piezoelectric acceleration sensor. The data acquisition process of the operating condition sensing module includes: The Hall effect vehicle speed sensor detects the rotation of the wheel axle gear ring and outputs a pulse signal proportional to the vehicle speed to obtain real-time vehicle speed data. The rotation of the steering wheel shaft grating disk is detected by a non-contact photoelectric steering angle sensor, which outputs an analog signal and simultaneously collects steering angle and steering angular velocity data. The vertical vibration of the vehicle frame is detected by a piezoelectric accelerometer, and the road surface smoothness is judged based on the magnitude of the vibration acceleration, thus collecting road surface condition data. The data collected by the three types of sensors are transmitted to the central control unit through their respective transmission links.

3. A vehicle steering system according to claim 2, characterized in that, The signal transmission and synchronization mechanism of the operating condition sensing module includes: Hall effect vehicle speed sensors transmit pulse signals via a bus, non-contact photoelectric steering angle sensors transmit analog signals via a dedicated bus, and piezoelectric accelerometers transmit vibration signals via analog signal lines. A multi-source signal synchronization calibration mechanism is established, using the system clock of the central control unit as a reference to align the signal acquisition timestamps of different sensors; Set a threshold for monitoring signal transmission quality. When signal loss, distortion, or transmission rate failure is detected, the signal retransmission or backup acquisition mode will be automatically activated.

4. A vehicle steering system according to claim 1, characterized in that, The design of the multi-parameter coupled damping algorithm for the damping calculation module includes: Using vehicle speed, steering angular velocity, and road vibration acceleration as input variables, the formula C=K1× v +K2× ω +K3× a The computational model is constructed using +C0, where C is the optimal damping coefficient, and K1, K2, and K3 are weighting coefficients. v For vehicle speed, ω For the steering angular velocity, a C0 represents the road surface vibration acceleration, and C0 is the basic damping coefficient. The multi-dimensional operating condition data is read at fixed time intervals, substituted into the formula to complete the calculation of the optimal damping coefficient, and the output is a continuous damping coefficient value covering a wide range.

5. A vehicle steering system according to claim 4, characterized in that, The optimization mechanism of the multi-parameter coupled damping algorithm includes: Establish a working condition data sample library and continuously accumulate multi-dimensional working condition data and corresponding optimal damping coefficient feedback data under different driving scenarios; Machine learning algorithms are used to train and update the data in the working condition data sample library, and the values ​​of weight coefficients and basic damping coefficients are dynamically adjusted. A working condition similarity matching mechanism is introduced. When a new working condition is detected, the optimized parameters of the same working condition in the working condition data sample library are matched.

6. A vehicle steering system according to claim 1, characterized in that, The signal conversion and output mechanism of the central control unit includes: Receive the optimal damping coefficient generated by the damping calculation module, and establish a linear mapping relationship between the optimal damping coefficient and the duty cycle of the pulse width modulation signal; The optimal damping coefficient is converted into a pulse width modulation signal with a corresponding duty cycle by an internal signal processing unit. An anti-interference transmission strategy is adopted to output the pulse width modulation signal to the execution and regulation module, and a signal transmission verification mechanism is established simultaneously to provide real-time feedback on the signal reception status of the execution and regulation module.

7. A vehicle steering system according to claim 6, characterized in that, The working mechanism of the electromagnetic damping regulator in the execution adjustment module includes: The system receives the pulse width modulation signal output by the central control unit, converts the signal into a current proportional to the duty cycle through the internal drive circuit, and then passes it into the electromagnetic coil. The magnetic field strength generated by the current changes dynamically with the magnitude of the current. The magnetic field exerts an axial attraction on the internal piston, driving the piston to make continuous displacement motion along the inner wall of the outer shell. During piston displacement, the effective flow cross-sectional area of ​​the oil passage is changed synchronously. Through the linkage control of magnetic field strength, piston displacement and passage cross-sectional area, the dynamic adaptation of the steering system damping coefficient is achieved.

8. A vehicle steering system according to claim 7, characterized in that, The damping adjustment logic of the electromagnetic damping regulator includes: The piston displacement is positively correlated with the current flowing through the electromagnetic coil. The larger the current, the longer the piston displacement distance and the smaller the cross-sectional area of ​​the oil passage. The cross-sectional area of ​​the oil passage is inversely related to the oil flow resistance. The smaller the cross-sectional area of ​​the passage, the greater the oil flow resistance and the higher the damping coefficient of the steering system. The current-displacement-cross-sectional area-resistance-damping coefficient adopts a multi-level linear correlation design to form continuous damping adjustment.

9. A vehicle steering system according to claim 8, characterized in that, The adaptive damping adjustment method of the system includes: The multi-dimensional operating condition data is acquired in real time, and the acquired multi-dimensional operating condition data is received and stored by the central control unit at fixed time intervals; The optimal damping coefficient corresponding to the current working condition is generated by calculating multi-dimensional working condition data through a multi-parameter coupled damping algorithm. The optimal damping coefficient is converted into a pulse width modulation signal and transmitted to the execution adjustment module to drive the electromagnetic damping regulator to adjust the cross-sectional area of ​​the oil passage; The system receives piston displacement and oil pressure data from the control module in real time, and performs linkage verification by combining the latest multi-dimensional operating condition data synchronously collected by the operating condition sensing module. Based on the real-time verification deviation, the weight coefficients of the multi-parameter coupled damping algorithm and the duty cycle of the pulse width modulation signal are dynamically corrected, forming a closed-loop control process of data acquisition, coefficient calculation, damping adjustment, and feedback correction.

10. A vehicle steering method that can adaptively adjust the damping coefficient according to driving conditions, characterized in that, Applied to the automotive steering system according to any one of claims 1 to 9, comprising the following steps: S1: Real-time acquisition of multi-dimensional operating condition data, which is received and stored by the central control unit at fixed time intervals; S2: The multi-dimensional working condition data is processed by a multi-parameter coupled damping algorithm to generate the optimal damping coefficient corresponding to the current working condition; S3: Convert the optimal damping coefficient into a pulse width modulation signal and transmit it to the execution adjustment module to drive the electromagnetic damping regulator to adjust the cross-sectional area of ​​the oil passage; S4: Receives piston displacement and oil pressure data from the execution adjustment module in real time, combines them with the latest multi-dimensional operating condition data synchronously collected by the operating condition sensing module for linkage verification, dynamically corrects the weight coefficients of the multi-parameter coupled damping algorithm and the duty cycle of the pulse width modulation signal, and forms a closed-loop adjustment process.

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