Method and device for controlling comfort of running vehicle and electronic equipment

Abstract

The embodiment of the invention discloses a driving vehicle comfort control method and device and electronic equipment. The method comprises the steps that vector features corresponding to information of protrusions in front of a vehicle are obtained; in response to the condition that the vector feature meets a preset first control condition, determining a parameter group matched with the vector feature in a preset database based on a Hash algorithm, so as to adjust the opening degree of an electromagnetic valve of the shock absorber based on a damping coefficient in the parameter group; and based on the current speed and the current sprung mass of the vehicle, the damping coefficient is adjusted through a PID control algorithm. In the embodiment of the invention, the existing vehicle-mounted sensors (a wheel speed sensor, a longitudinal acceleration sensor, a motor torque signal and a camera) can be completely reused to construct a sensing network of the preview system, and the effect close to that of an advanced preview system can be achieved without additionally invested hardware cost of a high-precision laser radar and a double-cavity air suspension. And the method can be adapted to middle and low-end vehicles to meet the driving comfort requirements of middle and low-end users.

Description

Technical Field

[0001] The embodiments in this specification belong to the field of vehicle damping control technology, and specifically relate to a method, device and electronic equipment for controlling the comfort of a moving vehicle. Background Technology

[0002] To improve driving comfort, vehicles are generally equipped with a pre-aiming system. This system uses sensors such as cameras and lidar to collect real-time information about the road surface ahead (e.g., potholes, speed bumps), dynamically adjusting suspension damping or vehicle height to reduce bumps. However, current pre-aiming systems heavily rely on high-precision lidar and dual-chamber air suspension, resulting in high hardware costs and a significant increase in overall vehicle price. This makes them unsuitable for mid-to-low-end vehicles and fails to meet the driving comfort needs of mid-to-low-end users. Summary of the Invention

[0003] Embodiments of this disclosure provide a method, apparatus, and electronic device for controlling the comfort of a vehicle, designed to address one or more of the problems described above and other potential problems.

[0004] According to a first aspect of this disclosure, a method for controlling the comfort of a vehicle is provided. The method includes acquiring vector features corresponding to information about a protrusion in front of the vehicle, the protrusion information including height and length information; responding to the vector features satisfying a preset first control condition, determining a parameter set matching the vector features in a preset database based on a hash algorithm, and adjusting the opening of a shock absorber's solenoid valve based on a damping coefficient in the parameter set; and adjusting the damping coefficient using a PID control algorithm based on the vehicle's current speed and current sprung mass, and adjusting the opening of the shock absorber's solenoid valve according to a current parameter corresponding to the adjusted damping coefficient.

[0005] According to a second aspect of this disclosure, a comfort control device for a vehicle is provided. The device includes a feature acquisition module configured to acquire vector features corresponding to information about a protrusion in front of the vehicle, the protrusion information including height and length information; an opening adjustment module configured to, in response to the vector features satisfying a preset first control condition, determine a parameter set matching the vector features in a preset database based on a hash algorithm, and adjust the opening of the solenoid valve of the shock absorber based on the damping coefficient in the parameter set; and a damping adjustment module configured to adjust the damping coefficient based on the vehicle's current speed and current sprung mass using a PID control algorithm, and adjust the opening of the solenoid valve of the shock absorber according to the current parameter corresponding to the adjusted damping coefficient.

[0006] According to a third aspect of this disclosure, an electronic device is provided, including one or more processors and a memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform a method provided according to a first scheme.

[0007] According to a fourth aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method provided according to the first aspect.

[0008] The embodiments provided in this specification, by matching the vector features of protrusion information with parameter sets, controlling the shock absorber with the damping coefficient of the parameter set, and performing PID control of the damping coefficient based on the current speed and current sprung mass, can completely reuse existing on-board sensors (wheel speed sensors, longitudinal acceleration sensors, motor torque signals, cameras) to build the perception network of the pre-aiming system. It can achieve an effect close to that of advanced pre-aiming systems without the need for additional investment in high-precision LiDAR and dual-cavity air suspension hardware costs. It can be adapted to low- and mid-range vehicles to meet the driving comfort needs of low- and mid-range users. Attached Figure Description

[0009] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0010] Figure 1 A flowchart illustrating a method for controlling the comfort of a vehicle according to some embodiments of the present disclosure is shown.

[0011] Figure 2 A schematic diagram of the structure of a comfort control device for a vehicle according to some embodiments of the present disclosure is shown;

[0012] Figure 3 A schematic block diagram of an electronic device according to some embodiments of the present disclosure is shown. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0014] The terms “comprising” and “having”, and any variations thereof, in this specification, claims, and the foregoing drawings are intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. Depending on the context, the word “if” as it applies herein may be interpreted as “when”, “in response to determination”, or “in response to detection”.

[0015] Figure 1 A schematic flowchart of a comfort control method 100 for a vehicle according to some embodiments of this disclosure is shown. Method 100 can, for example, be executed by an onboard MCU controller. Figure 1 As shown, method 100 may include the following steps:

[0016] Step 102: Obtain the vector features corresponding to the protrusions in front of the vehicle. The protrusion information includes height and length information.

[0017] In this embodiment, the controller can receive protrusion information collected from a binocular camera or lidar (high precision is not required). The protrusion information can be infrared image information or pulse information, etc. Protrusions generally refer to objects such as speed bumps and manhole covers. Through the protrusion information, the height and length information of the protrusion can be identified and its features vectorized for easy subsequent processing. The vector features can be a 2D vector including height and length, or a 9D vector including height, length, width, tilt angle, vehicle speed, sprung mass, surface material, temperature, and humidity. The tilt angle, i.e., the slope angle, can be output by the tightly coupled positioning system of Global Navigation Satellite System / Inertial Measurement Unit (GNSS / IMU). Vehicle speed, sprung mass, temperature, and humidity can all be determined by onboard sensors. The width and surface material can also be determined by image recognition of the protrusion information.

[0018] Step 104: In response to the vector feature satisfying the preset first control condition, determine the parameter set that matches the vector feature in the preset database based on the hash algorithm, and adjust the opening of the solenoid valve of the shock absorber based on the damping coefficient in the parameter set.

[0019] In this embodiment, a first control condition can be preset, such as a height greater than or equal to 5 cm and a length greater than or equal to 1.2 m. If the vector features meet this first control condition, it indicates that vehicle comfort control is required to reduce the feeling of bumps. First, experimental simulation tests can be conducted in advance. Several sets of parameter groups are stored in the database. In addition to feature data such as height and length, the parameter groups also include the most suitable damping coefficient determined by the test under the combination of feature data. Using the MinHash algorithm, the vector features and each parameter group in the database can be treated as a set. The hash value of each element in the set is calculated by mapping using a hash function, and the minimum hash value among all elements is used as the fingerprint signature of the set. Finally, by calculating the similarity of the fingerprint signature, the parameter group matching the vector features is determined in the database. Based on the damping coefficient in the parameter group, the mapping relationship between the corresponding damping coefficient and the current parameter can be determined according to the model of the shock absorber. The current parameter is then queried according to the mapping relationship, and the current through the solenoid valve of the shock absorber is adjusted to the corresponding current parameter, thereby adjusting the opening of the solenoid valve of the shock absorber to reduce the impact acceleration of the tire when passing over a protrusion. Among them, the shock absorber can be, for example, an active shock absorber that can actively control the current magnitude to control the opening of the solenoid valve, such as a continuous damping control (CDC) shock absorber.

[0020] Step 106: Based on the vehicle's current speed and current sprung mass, the damping coefficient is adjusted by the PID control algorithm, and the opening of the shock absorber's solenoid valve is adjusted according to the current parameters corresponding to the adjusted damping coefficient.

[0021] In this embodiment, considering that actual driving conditions cannot perfectly match experimental test conditions, a PID control algorithm can be used to dynamically adjust the damping coefficient to further ensure the effect of damping adjustment. During damping adjustment, the vehicle's current speed and current sprung mass are considered to have the greatest impact on damping. Furthermore, considering that the adjustment error cannot be directly determined using the damping coefficient, the error can be calculated based on the current speed and current sprung mass (for example, the weighted sum of their normalized values ​​can be used as the error, or different errors can be preset for the difference between the current value and a preset standard value). This allows for adjustment of the control quantity output by the PID control algorithm, thereby achieving dynamic adjustment of the damping coefficient. In this way, while significantly reducing costs, it covers 90% of user comfort adjustment scenarios, and the balanced performance of comfort adjustment can meet the basic needs of users, achieving a balance between performance and cost.

[0022] The PID control algorithm's process involves using vehicle speed and sprung mass data as input parameters, combined with preset constraints corresponding to comfort and handling targets, to dynamically calculate the damping coefficient. Next, based on the mapping relationship between the damping coefficient and current parameters corresponding to the shock absorber model, the algorithm queries the current parameter corresponding to the calculated damping coefficient. This current parameter is used to generate a current control command, adjusting the current through the solenoid valve to regulate its opening. Furthermore, the deviation between the actual operating current of the solenoid valve and the target value corresponding to the current parameter, or other deviations obtained through custom settings (such as deviations determined based on current speed and current sprung mass), can be used as an error signal to dynamically correct the PID parameters, ensuring damping adjustment accuracy.

[0023] In one possible implementation, the damping coefficient is adjusted by a PID control algorithm based on the vehicle's current speed and current sprung mass, including:

[0024] A composite parameter is constructed by weighting the normalized values ​​of the vehicle's current speed and current sprung mass; and

[0025] The composite parameters are used as the error signal of the PID control algorithm, and the damping coefficient is adjusted by the control quantity output by the PID control algorithm.

[0026] In this embodiment, the vehicle speed v is first mapped to the interval [0, 1] based on the vehicle speed range (e.g., [0, 120] km / h), resulting in the normalized value v_norm = v / 120. The sprung mass m is then mapped to the interval [0, 1] based on the sprung mass range (e.g., [1000, 2500] kg), resulting in the normalized value m_norm = (m-1000) / 1500. Next, by weighting the two values, the composite parameter e(t) can be constructed as follows:

[0027]

[0028] in, ,default , .

[0029] The composite parameter is used as the error signal for the PID control algorithm to adjust the output control quantity u(k), and the damping coefficient is adjusted synchronously according to the adjustment of the control quantity. The damping coefficient can be adjusted directly based on the change in the control quantity, or the relationship between the two can be determined through prior experimental simulation to establish a mapping ratio, and the damping coefficient can be adjusted synchronously based on this mapping ratio. The formula for calculating the control quantity is:

[0030]

[0031] in, The proportional gain can be set to 2.5; The integral gain can be set to 0.8; The differential gain can be set to 1.2; This is the current error; This is the error from the previous test; This represents the cumulative error from the initial time to the current time. The sampling period.

[0032] In one possible implementation, the method further includes:

[0033] In response to the wheel speed sensor detecting a front-to-rear axle speed difference greater than a speed difference threshold and a duration greater than a duration threshold, the vehicle's current acceleration error and road adhesion coefficient are calculated; and

[0034] In response to the acceleration error and road adhesion coefficient meeting the preset second control conditions, the motor output torque corresponding to each tire is compensated based on the slip ratio, vertical load and maximum motor torque of each tire to reduce the braking force of the tire.

[0035] In this embodiment, wheel speed sensors can detect the difference in rotational speed between the front and rear axles. If the difference in rotational speed exceeds a threshold (e.g., greater than or equal to 15%) and lasts for a duration greater than a duration threshold (e.g., greater than or equal to 500 ms), the vehicle is considered to be in a slope condition, requiring appropriate comfort control. Acceleration error can be determined by the difference between the vehicle's longitudinal acceleration (i.e., the actual acceleration generated by the vehicle's movement in the direction of travel) and the theoretical acceleration determined based on the current road conditions. The road adhesion coefficient (i.e., the maximum adhesion rate) can be determined by querying a slip rate-road adhesion coefficient mapping table obtained from pre-tested experiments for the vehicle after determining the tire slip rate. The adhesion rate in the table generally follows a trend of first increasing and then decreasing. The slip rate can be determined by the ratio between the difference between the vehicle's actual speed and the wheel's circumferential speed, and the vehicle's actual speed, or by using a Kalman filter algorithm for state estimation of the slip rate.

[0036] Acceleration error generally does not exceed a fixed range, and the road surface adhesion coefficient is not too low. However, if both conditions meet the second control condition (e.g., acceleration error greater than 0.3g and road surface adhesion coefficient less than 0.4), it indicates that the tires may be excessively slipping, causing significant vehicle deviation during travel. Motor torque compensation is needed to improve vehicle stability. Specifically, the motor output torque can be dynamically adjusted based on slip ratio, vertical load, and maximum motor torque to reduce tire braking force, prevent wheel lock-up, and avoid excessive tire slippage. A specific calculation formula could be:

[0037]

[0038] in, To compensate for the adjusted motor output torque, For the motor output torque, The road surface adhesion coefficient, For vertical loads, This represents the maximum torque of the motor.

[0039] In one possible implementation, calculating the vehicle's current acceleration error and road adhesion coefficient includes:

[0040] Based on the trained tire-road coupling model, the theoretical acceleration under the current road conditions is determined.

[0041] The current acceleration error of the vehicle is determined based on the absolute difference between the vehicle's longitudinal acceleration and the theoretical acceleration; and

[0042] The tire slip ratio is estimated based on the extended Kalman filter algorithm, and the road adhesion coefficient is queried based on the slip ratio.

[0043] In this embodiment, torque sensors (such as hub-type torque sensors) and a six-component force testing system can be pre-installed on a real vehicle or test bench in an experimental environment to synchronously collect tire longitudinal force, lateral force, and slip ratio data. A multi-dimensional test matrix is ​​constructed using different road surface combinations (dry / wet asphalt, ice and snow, gravel, etc.), slopes (-15° to +15°), and load conditions (no load / full load). Then, the CAN FD bus time synchronization mechanism (such as SYNC frames) is used to align torque signals (signal transmission frequency can be 1kHz), slope angles (signal transmission frequency can be 100Hz), and vehicle status data (signal transmission frequency can be 50Hz). This allows the construction of a tire-road coupling model, which can be used to simulate and determine the theoretical acceleration under the current road conditions. Next, based on the onboard sensors, the vehicle's current longitudinal acceleration can be determined, and the absolute difference between the two can be calculated to obtain the acceleration error. The acceleration error is larger on slopes than on flat surfaces, thus allowing the determination of whether the vehicle is on a slope.

[0044] Furthermore, based on the extended Kalman filter algorithm, the state vector can be defined as:

[0045]

[0046] in, For slip ratio, It is the rate of change of the slip ratio (i.e., the derivative of the slip ratio with respect to time).

[0047] Next, the equations of motion are constructed to describe the state vector from time t. arrive Evolutionary patterns:

[0048]

[0049] in, Due to the rotational inertia of the wheels, The effective rolling radius of the tire. Input torque to the wheels, For longitudinal ground reaction force, For process noise, This represents the discretization time step.

[0050] Construct observation equations to describe the relationship between measurable physical quantities and state variables:

[0051]

[0052] in, For the longitudinal speed of the vehicle, For wheel speed, To observe noise.

[0053] The observation equation directly provides the measured value of the slip ratio; therefore, the slip ratio is defined as:

[0054]

[0055] The slip ratio can be estimated using the above method, and the estimate can be continuously revised by comparing the predicted value with the actual measured value. The road surface adhesion coefficient can then be obtained from the estimated slip ratio.

[0056] In one possible implementation, after responding to the wheel speed sensor detecting that the front and rear axle speed difference is greater than a speed difference threshold and the duration is greater than a duration threshold, the method further includes:

[0057] In response to a slope angle greater than an angle threshold, a gain coefficient is determined based on the slope angle to compensate for the motor output torque. The gain coefficient increases linearly with the slope angle when the slope angle is in the first angle range, and is a fixed value when the slope angle is in the second angle range. The maximum value in the first angle range is less than the minimum value in the second angle range.

[0058] In this embodiment, if the slope angle is greater than an angle threshold (e.g., greater than 8°), a gain coefficient is determined to provide additional compensation for the motor output torque, slightly increasing it and preventing slippage. Specifically, different slope angles can determine different gain coefficients. For example, when the slope angle is between 8° and 15°, the gain coefficient can be set between 1.5 and 2.0 using linear interpolation. When the slope angle is greater than 15°, it can be fixed at 2.0 to prevent sudden torque changes. An exemplary compensation formula could be:

[0059]

[0060] in, This is the motor output torque after gain factor correction. This represents the motor output torque, and 1.5 is the gain coefficient (initially set to 1.5, but the specific value will be determined later according to the aforementioned method). The slope angle is denoted by .

[0061] In one possible implementation, the method further includes:

[0062] Based on the motor output torque after gain coefficient compensation, the parameter combination corresponding to the high-efficiency zone is queried in the motor efficiency MAP, so as to adjust the real-time parameters of the vehicle according to the parameter combination.

[0063] In this embodiment, the motor is equipped with a motor efficiency MAP stored in a three-dimensional table format (X-axis: speed, Y-axis: torque, Z-axis: efficiency). This MAP can be obtained through calibration on an experimental bench and covers the entire operating range. After determining the motor output torque after gain coefficient compensation, the motor efficiency MAP is used to determine the parameter combination (torque-speed combination) corresponding to the high-efficiency zone (e.g., efficiency greater than or equal to 85%). This is used to adjust the corresponding real-time parameters of the vehicle (i.e., real-time torque and real-time speed) to ensure motor efficiency. The specific parameter combination selected within the high-efficiency zone can be chosen based on actual needs. For example, in the State of Charge (SOC) state, the most efficient parameter combination can be prioritized, while in the low-charge state, peak torque output can be limited to select a parameter combination that just reaches the high-efficiency zone. The threshold for dividing the high-charge and low-charge states can be adjusted and set according to actual requirements.

[0064] In one possible implementation, after responding to the wheel speed sensor detecting that the front and rear axle speed difference is greater than a speed difference threshold and the duration is greater than a duration threshold, the method further includes:

[0065] A parametric curve is generated based on the longitudinal projection of lane line features along the lane line.

[0066] After performing piecewise cubic Hermite interpolation on the parametric curve, the radius of curvature of the lane lines is calculated; and

[0067] In response to the curvature radius satisfying the preset third control condition, a control command is generated, which is used to control the damper to increase stiffness.

[0068] In this embodiment, the binocular vision camera can also extract features from the road lane lines. During feature extraction, a Difference of Gaussian Pyramid (DoG) can be used to detect key points, and unstable points can be filtered out using a contrast threshold (e.g., 0.03) and edge response (e.g., Hessian matrix, threshold of 10). Next, prior knowledge of the lane lines can be introduced based on the gradient orientation histogram (e.g., a 16x8 window) to forcibly retain feature points within a horizontal range of ±15°. When performing lane line feature matching on the detected features, a nearest neighbor search can be performed using a KD-tree with a distance threshold of 0.6 for coarse matching. Alternatively, the lane line continuity constraint can be utilized, and the RANSAC algorithm can be used to eliminate mismatches (with 100 iterations and an interior point threshold of 5 pixels) for fine matching. After completing the above process of acquiring lane line features, a parameterized curve with arc length parameterization can be generated based on the longitudinal projection of the lane line features. Then, piecewise cubic Hermite interpolation is used to perform cubic spline interpolation fitting to ensure the continuity of the first derivative and avoid abrupt changes in curvature. The radius of curvature is then calculated using the following formula:

[0069]

[0070] in, For arc length parameters, The horizontal axis is denoted as .

[0071] When the radius of curvature meets the third control condition (e.g., the radius of curvature R(s) is less than 50ms for 5 consecutive frames (83ms) and the fitting error is less than 2%), the vehicle is considered to be on a mountain road and is identified as a low-traction condition. At this time, the vehicle will switch to "mountain road mode". The stiffness can be increased by 30% through the CDC shock absorber to suppress vehicle roll and ensure a smooth and comfortable ride on mountain roads. In addition, the yaw rate can be PID controlled based on the vehicle's ESP (Electronic Stability Program) system to adjust the braking force distribution so that the roll angle is less than a certain angle.

[0072] In other possible implementations, in the "mountain road mode," the EPS (Electric Power Steering) system can also be compensated for corner gain based on the slope angle to optimize the EPS response. The calculation formula is as follows:

[0073]

[0074] in, This is the steering gain after corner gain compensation. The default steering gain. The slope angle is denoted by .

[0075] Figure 2 This diagram illustrates the structure of a comfort control device 200 for a vehicle according to some embodiments of the present disclosure. The various embodiments in this specification are described in a progressive manner; similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments. Figure 2 As shown, the device 200 includes a feature acquisition module 201, configured to acquire vector features corresponding to information about protrusions in front of the vehicle, the protrusion information including height and length information; an opening adjustment module 202, configured to, in response to the vector features satisfying a preset first control condition, determine a parameter set matching the vector features in a preset database based on a hash algorithm, and adjust the opening of the shock absorber's solenoid valve based on the damping coefficient in the parameter set; and a damping adjustment module 203, configured to, based on the vehicle's current speed and current sprung mass, adjust the damping coefficient using a PID control algorithm, and adjust the opening of the shock absorber's solenoid valve according to the current parameter corresponding to the adjusted damping coefficient.

[0076] In one possible implementation, the damping adjustment module 203 is further configured to construct a composite parameter based on a weighted average of the vehicle’s current speed and current sprung mass; and to use the composite parameter as an error signal for a PID control algorithm to adjust the damping coefficient using the control quantity output by the PID control algorithm.

[0077] In one possible implementation, the device further includes: a ramp control module configured to calculate the current acceleration error and road surface adhesion coefficient of the vehicle in response to a wheel speed sensor detecting a front-to-rear axle speed difference greater than a speed difference threshold and a duration greater than a duration threshold; and to compensate for the motor output torque corresponding to each tire based on the slip ratio, vertical load, and maximum motor torque of each tire in response to a preset second control condition, so as to reduce the braking force of the tire.

[0078] In one possible implementation, the ramp control module is further configured to determine the theoretical acceleration under the current road conditions based on a trained tire-road coupling model; determine the current acceleration error of the vehicle based on the absolute difference between the vehicle's longitudinal acceleration and the theoretical acceleration; and estimate the tire slip ratio based on an extended Kalman filter algorithm to query the road adhesion coefficient based on the slip ratio.

[0079] In one possible implementation, the ramp control module is further configured to determine a gain coefficient based on the ramp angle in response to a ramp angle greater than an angle threshold, so as to compensate the motor output torque according to the gain coefficient. The gain coefficient increases linearly with the ramp angle when the ramp angle is in a first angle range, and the gain coefficient is a fixed value when the ramp angle is in a second angle range. The maximum value of the first angle range is less than the minimum value of the second angle range.

[0080] In one possible implementation, the ramp control module is also configured to query the parameter combination corresponding to the high-efficiency zone in the motor efficiency MAP based on the motor output torque after gain coefficient compensation, so as to adjust the real-time parameters of the vehicle according to the parameter combination.

[0081] In one possible implementation, the ramp control module is further configured to generate a parametric curve based on the longitudinal projection of the lane line features along the lane line; calculate the radius of curvature of the lane line after performing piecewise cubic Hermite interpolation on the parametric curve; and generate a control command in response to the radius of curvature satisfying a preset third control condition, the control command being used to control the shock absorber to increase stiffness.

[0082] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this specification is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0083] Figure 3 A block diagram of an electronic device 300 that can implement various embodiments of the present disclosure is shown. For example... Figure 3 As shown, the electronic device 300 includes a processor 310, a disk drive 320, an input / output interface 330, a network interface 340, and a memory 350. The processor 310, disk drive 320, input / output interface 330, network interface 340, and memory 350 can communicate with each other via a communication bus 360.

[0084] The processor 310 can be implemented using a general-purpose CPU, microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits to execute relevant programs in order to implement the technical solution provided in this application.

[0085] The memory 350 can be implemented in the form of ROM (Read Only Memory), RAM (Read Access Memory), static memory, dynamic storage devices, etc. The memory 350 can store the operating system 351 used to control the operation of the electronic device 300, and the basic input / output system (BIOS) 352 used to control the low-level operations of the electronic device 300. Additionally, it can store a web browser 353, a data storage management system 354, etc. In summary, when the technical solution provided in this application is implemented through software or firmware, the relevant program code is stored in the memory 350 and is called and executed by the processor 310.

[0086] Input / output interface 330 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0087] Network interface 340 is used to connect a communication module (not shown in the figure) to enable communication and interaction between the device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0088] Bus 360 includes a pathway for transmitting information between various components of the device, such as processor 310, disk drive 320, input / input interface 330, network interface 340, and memory 350.

[0089] It should be noted that although the above-described device only shows the processor 310, disk drive 320, input / output interface 330, network interface 340, memory 350, bus 360, etc., in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the method of this application, and does not necessarily include all the components shown in the figures.

[0090] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0091] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. Furthermore, although operations are depicted in a specific order, this should be understood as requiring that such operations be performed in the specific order shown or in sequential order, or requiring that all illustrated operations be performed to achieve the desired result. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations.

[0092] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for controlling the comfort of a moving vehicle, characterized in that, The method includes: Obtain vector features corresponding to information about protrusions in front of the vehicle, wherein the protrusion information includes height information and length information; In response to the vector feature satisfying a preset first control condition, a parameter set matching the vector feature is determined in a preset database based on a hash algorithm, and the opening of the solenoid valve of the shock absorber is adjusted based on the damping coefficient in the parameter set; and Based on the vehicle's current speed and current sprung mass, the damping coefficient is adjusted by a PID control algorithm, and the opening of the shock absorber's solenoid valve is adjusted according to the current parameter corresponding to the adjusted damping coefficient.

2. The method for controlling the comfort of a vehicle according to claim 1, characterized in that, The adjustment of the damping coefficient by the PID control algorithm based on the vehicle's current speed and current sprung mass includes: A composite parameter is constructed by weighting the normalized values ​​of the vehicle's current speed and current sprung mass; and The composite parameters are used as error signals for the PID control algorithm, and the damping coefficient is adjusted by the control quantity output by the PID control algorithm.

3. The method for controlling the comfort of a moving vehicle according to claim 1, characterized in that, The method further includes: In response to the wheel speed sensor detecting a front-to-rear axle speed difference greater than a speed difference threshold and a duration greater than a duration threshold, the vehicle's current acceleration error and road adhesion coefficient are calculated; and In response to the acceleration error and road adhesion coefficient satisfying the preset second control condition, the motor output torque corresponding to each tire is compensated based on the slip ratio, vertical load and maximum motor torque of each tire, so as to reduce the braking force of the tire.

4. The method for controlling the comfort of a vehicle according to claim 3, characterized in that, The calculation of the vehicle's current acceleration error and road adhesion coefficient includes: Based on the trained tire-road coupling model, the theoretical acceleration under the current road conditions is determined. Based on the absolute difference between the vehicle's longitudinal acceleration and the theoretical acceleration, the current acceleration error of the vehicle is determined; and The tire slip ratio is estimated based on the extended Kalman filter algorithm, and the road adhesion coefficient is queried based on the slip ratio.

5. The method for controlling the comfort of a moving vehicle according to claim 3, characterized in that, The response to the wheel speed sensor detecting a front-to-rear axle speed difference greater than a speed difference threshold and a duration greater than a duration threshold further includes: In response to a slope angle greater than an angle threshold, a gain coefficient is determined based on the slope angle to compensate for the motor output torque according to the gain coefficient. The gain coefficient increases linearly with the slope angle when the slope angle is in a first angle range, and the gain coefficient is a fixed value when the slope angle is in a second angle range. The maximum value of the first angle range is less than the minimum value of the second angle range.

6. The method for controlling the comfort of a vehicle according to claim 5, characterized in that, The method further includes: Based on the motor output torque after gain coefficient compensation, the parameter combination corresponding to the high-efficiency zone is queried in the motor efficiency MAP, so as to adjust the real-time parameters of the vehicle according to the parameter combination.

7. The method for controlling the comfort of a vehicle according to claim 3, characterized in that, The response to the wheel speed sensor detecting a front-to-rear axle speed difference greater than a speed difference threshold and a duration greater than a duration threshold further includes: A parametric curve is generated based on the longitudinal projection of lane line features along the lane line. After performing piecewise cubic Hermite interpolation on the parameterized curve, the radius of curvature of the lane line is calculated; and In response to the curvature radius satisfying a preset third control condition, a control command is generated to control the shock absorber to increase its stiffness.

8. A comfort control device for a vehicle, characterized in that, The device includes: The feature acquisition module is configured to acquire vector features corresponding to information about protrusions in front of the vehicle, wherein the protrusion information includes height information and length information. The opening adjustment module is configured to, in response to the vector feature satisfying a preset first control condition, determine a parameter set matching the vector feature in a preset database based on a hash algorithm, and adjust the opening of the solenoid valve of the shock absorber based on the damping coefficient in the parameter set; and The damping adjustment module is configured to adjust the damping coefficient based on the vehicle's current speed and current sprung mass using a PID control algorithm, thereby adjusting the opening of the shock absorber's solenoid valve according to the current parameters corresponding to the adjusted damping coefficient.

9. An electronic device, comprising: One or more processors, and A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of a comfort control method for a vehicle according to any one of claims 1-7.

10. A computer program product comprising a computer program that, when executed by a processor, implements a method for comfort control of a vehicle according to any one of claims 1-7.

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