Magnetorheological suspension semi-active feedback control system based on laser radar and multi-sensor fusion

Abstract

The invention discloses a magneto-rheological suspension semi-active feedback control system based on laser radar and multi-sensor fusion. The magneto-rheological suspension semi-active feedback control system comprises a radar assembly, a sensor assembly and a feedback control assembly which are integrally installed on a vehicle body. Related road surface and vehicle driving data are obtained through the laser radar, the vehicle attitude sensor and the vehicle speed sensor, the collected data are analyzed and processed through the data processing unit, and real-time road condition scores and vehicle driving parameters are obtained; generating a suspension control signal according to the real-time road condition score and the vehicle driving parameters, and transmitting the suspension control signal to a suspension controller; the suspension controller transmits current to the magnetorheological dampers, and therefore the magnetorheological dampers are controlled to output damping force to the corresponding wheels. The response speed of the magneto-rheological suspension can be remarkably increased, the adaptability of the magneto-rheological suspension to complex road conditions is enhanced, and therefore the driving stability, controllability and riding comfort of a vehicle are remarkably improved.

Description

Technical Field

[0001] The present invention relates to a semi - active suspension system, specifically a semi - active feedback control system for a magnetorheological suspension based on lidar and multi - sensor fusion, belonging to the technical field of automotive or vehicle suspension systems. Background Art

[0002] Currently, automotive suspension systems are mainly divided into passive suspensions, semi - active suspensions, and active suspensions. Among them, passive suspensions have fixed stiffness and damping characteristics and cannot adapt to complex and changeable road conditions. Although active suspensions have excellent adaptability, they are costly, have complex structures, and high energy consumption, so they have not been widely applied yet. In contrast, semi - active suspensions have obvious advantages in balancing comfort, handling, and cost. Magnetorheological suspensions have become a research hotspot in the development of current intelligent suspensions due to their adjustable damping, fast response speed, and low energy consumption. The core of a magnetorheological suspension is a magnetorheological damper, which is filled with magnetorheological fluid inside and can rapidly change its viscosity under the action of an external magnetic field, thereby adjusting the damping characteristics of the suspension.

[0003] In the prior art, such as the controllable - damping external magnetorheological intelligent suspension system, control method, and vehicle disclosed in the publication number CN114953880A, which includes a suspension cylinder, a connecting pipe, a magnetorheological control unit, and an accumulator; the magnetorheological control unit is located between the suspension cylinder and the accumulator, and the three are connected through the connecting pipe; there is magnetorheological fluid between the suspension cylinder, the magnetorheological control unit, and the accumulator; when the suspension cylinder compresses and extends, it conducts the magnetorheological fluid to flow back and forth together with the accumulator. When an external current is applied to the magnetorheological control unit, the electromagnetic field in the magnetorheological control unit causes the magnetorheological fluid to "solidify", thereby affecting the flow rate of the magnetorheological fluid and the magnitude of the damping of the suspension system; by increasing and decreasing the external current, the electromagnetic field intensity is increased and decreased to adjust the system damping. However, the existing magnetorheological suspension systems still have certain limitations. On the one hand, most traditional magnetorheological suspensions adopt single - feedback control, mainly relying on sensors such as vehicle body acceleration and wheel speed for closed - loop adjustment. However, when encountering sudden bumps or potholes, there is a certain delay in the system response, which affects the adjustment effect of the suspension. On the other hand, there is a lack of feed - forward control and it is unable to sense the road conditions ahead in advance, resulting in the inability of the magnetorheological shock absorber to adjust the damping force in advance when passing through a speed bump or pothole. In addition, the utilization rate of sensor information in the existing system is low, mainly relying on vehicle speed sensors or vehicle attitude sensors, and new environment - sensing devices such as lidar or cameras are not fully utilized. Summary of the Invention

[0004] The purpose of the present invention is to provide a semi - active feedback control system for a magnetorheological suspension based on lidar and multi - sensor fusion to solve at least one of the above - mentioned technical problems.

[0005] The present invention achieves the above object through the following technical solutions: A semi-active feedback control system for a magnetorheological suspension based on the fusion of lidar and multi-sensors, comprising a radar component, a sensor component, and a feedback control component integrally installed on the vehicle body. The radar component and the sensor component are both connected to the feedback control component for signal transmission. The radar component includes a lidar and a stable pan-tilt head. The sensor component includes a vehicle attitude sensor and a vehicle speed sensor. The feedback control component includes a data processing unit, a suspension controller, and a magnetorheological damper;

[0006] The stable pan-tilt head is fixedly connected to the vehicle body, and the lidar is installed on the stable pan-tilt head. The lidar scans the road surface ahead in real time, obtains road surface shape, obstacles, and road condition information, and transmits the collected lidar point cloud data to the data processing unit;

[0007] The vehicle attitude sensor obtains body attitude data such as the tilt angle of the vehicle body and the centripetal acceleration when the vehicle turns, and transmits it to the data processing unit. The vehicle speed sensor obtains the vehicle speed data of the vehicle and transmits it to the data processing unit;

[0008] The suspension controller is used to receive signals from the data processing unit and control the working state of the magnetorheological damper. The magnetorheological damper is equipped with magnetorheological fluid and an electromagnetic coil. The magnetorheological damper changes the current passing through the electromagnetic coil according to the suspension adjustment signal, generates a magnetic field acting on the magnetorheological fluid, and the data processing unit is equipped with a data fusion processing algorithm.

[0009] As a further aspect of the present invention: The data fusion processing algorithm analyzes and processes the lidar point cloud data collected by the lidar, the body attitude data collected by the vehicle attitude sensor, and the driving speed of the vehicle collected by the vehicle speed sensor to obtain a real-time road condition score; and after the data fusion processing algorithm receives the data from the vehicle attitude sensor and the vehicle speed sensor, the data processing unit processes these data to obtain vehicle driving parameters.

[0010] As a further aspect of the present invention: The data processing unit stores a set of control signals for vehicle models and magnetorheological damper models under different real-time road condition scores and vehicle driving parameters; and the data processing unit determines the corresponding control signal and transmits the control signal to the suspension controller.

[0011] As a further aspect of the present invention: The vehicle driving parameters include, but are not limited to, accelerations, decelerations, and centripetal accelerations corresponding to driving condition types such as emergency start, emergency braking, and emergency turning.

[0012] As a further aspect of the present invention: Each magnetorheological damper has a corresponding suspension controller. The data fusion processing algorithm is used to perform point cloud denoising on the lidar point cloud data collected by the lidar, including the following steps:

[0013] 1) Remove outliers using the RANSAC algorithm;

[0014] 2) Remove small isolated point clusters using the DBSCAN clustering method.

[0015] As a further aspect of the present invention: The data fusion processing algorithm analyzes and scores the slope of the vehicle driving road surface, including the following steps:

[0016] 1) Select ground points within a certain range, fit a local plane based on the least squares method, and calculate the slope;

[0017] 2) Set a slope threshold;

[0018] 3) Read the vehicle driving speed;

[0019] 4) The slope scoring formula is:

[0020]

[0021] In the formula, k s is the slope influence coefficient, θ is the slope angle, indicating that the slope has a greater impact during high-speed driving.

[0022] As a further aspect of the present invention: The data fusion processing algorithm analyzes and scores the flatness of the vehicle driving road surface, including the following steps:

[0023] 1) Adopt height change statistics;

[0024] 2) Calculate the standard deviation of the point cloud height within the local area;

[0025] 3) Analyze the lateral / longitudinal slope change of the road surface;

[0026] 4) Measure using the International Roughness Index (IRI);

[0027] 5) The road surface flatness scoring formula is:

[0028]

[0029] In the formula, IRI is the flatness index of the current road, IRI max is the set maximum tolerable flatness, k v is the speed influence coefficient, v is the current vehicle speed, v max is the set maximum safe speed.

[0030] As a further aspect of the present invention: The data fusion processing algorithm analyzes and scores the obstacles on the vehicle driving road surface, including the following steps:

[0031] 1) Extract obstacles using DBSCAN or Euclidean clustering;

[0032] 2) Calculate the total number of obstacles;

[0033] 3) Calculate the horizontal distance of the obstacle from the vehicle center line;

[0034] 4) Calculate the volume of the obstacle;

[0035] 5) The obstacle scoring formula is:

[0036]

[0037] In the formula, N obs is the total number of obstacles, d is the horizontal distance of the obstacle from the vehicle center line, and Vi is the volume of the obstacle.

[0038] As a further solution of the present invention: The data fusion processing algorithm scores the real-time road conditions, including the following steps:

[0039] 1) Integrate the analysis results of the slope, road surface flatness, and obstacles by the data fusion processing algorithm;

[0040] 2) Assign weights to the slope, road surface flatness, and obstacles, perform comprehensive calculations, and perform normalization processing to obtain the real-time road condition score.

[0041] As a further solution of the present invention: The suspension controller controls the damping force change of the magnetorheological damper, including the following steps:

[0042] 1) The suspension controller outputs current according to the signal of the data processing unit;

[0043] 2) The current passes through the electromagnetic coil in the magnetorheological damper to generate a magnetic field;

[0044] 3) The magnetic field acts on the magnetorheological fluid in the magnetorheological damper to adjust its viscosity;

[0045] 4) The change in the viscosity of the magnetorheological fluid causes a change in the damping force.

[0046] The suspension controller transmits control signals to each magnetorheological damper according to the received suspension control signals, so as to control each magnetorheological damper to make a response and output damping force to the corresponding wheel.

[0047] The beneficial effects of the present invention are:

[0048] 1) Predict road surface changes in advance and improve the response speed. The magnetorheological damper combines lidar and multi-sensor data. By predicting changes in the road conditions ahead, the damping force is quickly adjusted to ensure that the suspension system can respond in a timely manner without relying on the body vibration signal;

[0049] 2) Improve comfort and safety. The magnetorheological damper can intelligently adjust the damping force to optimize the suspension response, thus providing a smoother driving experience. Even under different road conditions, the system can still effectively adjust the damping force to ensure stable vehicle handling and comfortable riding.

[0050] 3) Optimize energy consumption and improve efficiency. While providing high dynamic adaptability, the magnetorheological suspension has higher energy efficiency and lower energy consumption compared to fully active suspensions. The precise adjustment of the magnetorheological fluid ensures efficient energy utilization.

[0051] 4) Enhance the adaptability to complex working conditions. The magnetorheological damper can quickly adjust the damping force to adapt to complex road conditions such as rough, gravel, potholed roads, as well as dynamic conditions such as high-speed driving and emergency obstacle avoidance, effectively suppressing vibrations and improving vehicle stability and safety.

[0052] 5) Cost-effectiveness. The system uses magnetorheological technology and lidar for forward road condition prediction, optimizes the suspension control strategy, and provides lower costs and higher dynamic adaptability compared to fully active suspensions.

[0053] 6) The system scans the road information ahead through lidar, combines vehicle speed and attitude data, predicts upcoming road surface changes in advance, and optimizes the adjustment strategy of the magnetorheological damper. By adjusting the damping force in real time, the magnetorheological damper improves the suspension control accuracy and response speed while ensuring energy efficiency, comfort, and safety, enabling the vehicle to adapt to various complex road conditions and improve the overall driving performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic structural diagram of the semi-active feedback control system of the present invention;

[0055] Figure 2 It is a working principle diagram of the lidar scanning the road surface of the present invention;

[0056] Figure 3 It is a working principle diagram of the suspension controller controlling the change of the damping force of the magnetorheological damper of the present invention;

[0057] Figure 4 It is a flow chart for calculating the slope score of the present invention;

[0058] Figure 5 It is a flow chart for calculating the road surface flatness score of the present invention;

[0059] Figure 6 It is a flow chart for calculating the obstacle score of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0060] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0061] Embodiment 1, as Figures 1 to 6 shown, a semi-active feedback control system for a magnetorheological suspension based on the fusion of lidar and multi-sensors includes a radar component, a sensor component, and a feedback control component integrally installed on the vehicle body. The radar component and the sensor component are both signal-transmission connected to the feedback control component. The radar component includes a lidar and a stable pan-tilt head. The sensor component includes a vehicle attitude sensor and a vehicle speed sensor. The feedback control component includes a data processing unit, a suspension controller, and a magnetorheological damper;

[0062] The stable pan-tilt head is fixedly connected to the vehicle body, and the lidar is installed on the stable pan-tilt head. The stable pan-tilt head is provided for stably installing the lidar. The lidar scans the road surface ahead in real time, obtains road surface shape, obstacles, and road condition information, and transmits the collected lidar point cloud data to the data processing unit;

[0063] The vehicle attitude sensor obtains vehicle body attitude data such as the tilt angle of the vehicle body and the centripetal acceleration when the vehicle turns, and transmits it to the data processing unit. The vehicle speed sensor obtains the vehicle speed data of the vehicle and transmits it to the data processing unit;

[0064] The suspension controller is used to receive the signal from the data processing unit and control the working state of the magnetorheological damper. The magnetorheological damper is equipped with magnetorheological fluid and an electromagnetic coil. The magnetorheological damper changes the current passing through the electromagnetic coil according to the suspension adjustment signal, generates a magnetic field acting on the magnetorheological fluid, adjusts its viscosity, and changes the damping force. The data processing unit is equipped with a data fusion processing algorithm.

[0065] Embodiment 2, in addition to including all the technical features in Embodiment 1, this embodiment further includes: The data fusion processing algorithm analyzes and processes the lidar point cloud data collected by the lidar, the vehicle body attitude data collected by the vehicle attitude sensor, and the driving speed of the vehicle collected by the vehicle speed sensor to obtain a real-time road condition score; and after the data fusion processing algorithm receives the data from the vehicle attitude sensor and the vehicle speed sensor, the data processing unit processes these data to obtain vehicle driving parameters.

[0066] Further, the data processing unit stores a set of control signals for vehicle models and magnetorheological damper models under different real-time road condition scores and vehicle driving parameters; and the data processing unit determines the corresponding control signals and transmits the control signals to the suspension controller.

[0067] Further, the vehicle driving parameters include, but are not limited to, accelerations, decelerations, and centripetal accelerations corresponding to driving condition types such as emergency start, emergency braking, and emergency turning.

[0068] Further, each magnetorheological damper has a corresponding suspension controller, and uses a data fusion processing algorithm to perform point cloud denoising on the lidar point cloud data collected by the lidar, including the following steps:

[0069] 1) Using the RANSAC algorithm to remove outliers;

[0070] 2) Using the DBSCAN clustering method to remove small isolated point clusters.

[0071] Embodiment 3, in this embodiment, in addition to including all the technical features in Embodiment 1, it further includes:

[0072] The data fusion processing algorithm analyzes and scores the slope of the vehicle driving road surface, including the following steps:

[0073] 1) Selecting ground points within a certain range, fitting a local plane based on the least squares method, and calculating the slope;

[0074] 2) Setting a slope threshold;

[0075] 3) Reading the vehicle driving speed;

[0076] 4) The slope scoring formula is:

[0077]

[0078] In the formula, k s is the slope influence coefficient, θ is the slope angle, indicating that the slope has a greater impact during high-speed driving.

[0079] Further, the data fusion processing algorithm analyzes and scores the flatness of the vehicle driving road surface, including the following steps:

[0080] 1) Using height change statistics;

[0081] 2) Calculating the standard deviation of the point cloud height within a local area;

[0082] 3) Analyzing the lateral / longitudinal slope change of the road surface;

[0083] 4) Using the International Roughness Index (IRI) for measurement;

[0084] 5) The road surface evenness scoring formula is as follows:

[0085]

[0086] Where IRI is the evenness index of the current road, and IRI max is the set maximum tolerable evenness, k v is the speed influence coefficient, v is the current vehicle speed, and v max is the set maximum safe speed.

[0087] Furthermore, the data fusion processing algorithm analyzes and scores the obstacles on the road surface where the vehicle is traveling, including the following steps:

[0088] 1) Use DBSCAN or Euclidean clustering to extract obstacles;

[0089] 2) Calculate the total number of obstacles;

[0090] 3) Calculate the horizontal distance of the obstacle from the vehicle center line;

[0091] 4) Calculate the volume of the obstacle;

[0092] 5) The obstacle scoring formula is as follows:

[0093]

[0094] Where N obs is the total number of obstacles, d is the horizontal distance of the obstacle from the vehicle center line, and Vi is the volume of the obstacle.

[0095] Furthermore, the data fusion processing algorithm scores the real-time road conditions, including the following steps:

[0096] 1) Integrate the analysis results of the slope, road surface evenness, and obstacles by the data fusion processing algorithm;

[0097] 2) Assign weights to the slope, road surface evenness, and obstacles, and perform normalization processing to obtain the real-time road condition score.

[0098] Furthermore, the suspension controller controls the damping force change of the magnetorheological damper, including the following steps:

[0099] 1) The suspension controller outputs a current according to the signal of the data processing unit;

[0100] 2) The current passes through the electromagnetic coil in the magnetorheological damper to generate a magnetic field;

[0101] 3) The magnetic field acts on the magnetorheological fluid in the magnetorheological damper to adjust its viscosity;

[0102] 4) The change in the viscosity of the magnetorheological fluid causes a change in the damping force.

[0103] The suspension controller transmits control signals to each magnetorheological damper according to the received suspension control signals, thereby controlling each magnetorheological damper to respond and output damping force to the corresponding wheel.

[0104] Relevant road surface and vehicle driving data are obtained through lidar, vehicle attitude sensors, and vehicle speed sensors; the collected data is analyzed and processed by a data processing unit to obtain real-time road condition scores and vehicle driving parameters; suspension control signals are generated according to the real-time road condition scores and vehicle driving parameters and transmitted to the suspension controller; the suspension controller transmits currents to each magnetorheological damper respectively, thereby controlling each magnetorheological damper to output damping force to the corresponding wheel.

[0105] The system scans the road information ahead through lidar, combines vehicle speed and attitude data, predicts upcoming road surface changes in advance, and optimizes the adjustment strategy of the magnetorheological damper. By adjusting the damping force in real time, the magnetorheological damper improves the suspension control accuracy and response speed while ensuring energy efficiency, comfort, and safety, enabling the vehicle to adapt to various complex road conditions and improve the overall driving performance.

[0106] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

[0107] In addition, it should be understood that although this specification is described according to embodiments, not every embodiment only contains an independent technical solution. This narrative way of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A magnetorheological suspension semi-active feedback control system based on laser radar and multi-sensor fusion, comprising a radar component, a sensor component and a feedback control component integrated and installed on the vehicle body, characterized in that: The radar assembly and the sensor assembly are both connected to the feedback control assembly for signal transmission, the radar assembly includes a laser radar and a stabilizing gimbal, the sensor assembly includes a vehicle posture sensor and a vehicle speed sensor, and the feedback control assembly includes a data processing unit, a suspension controller and a magnetorheological damper; The stabilized gimbal is fixedly connected to the vehicle body, and the laser radar is installed on the stabilized gimbal. The laser radar scans the road ahead in real time to obtain road shape, obstacles and road condition information, and transmits the collected laser radar point cloud data to the data processing unit; The vehicle attitude sensor acquires the vehicle body attitude data such as the tilt angle of the vehicle body and the centripetal acceleration when the vehicle turns, and transmits the data to the data processing unit; the vehicle speed sensor acquires the vehicle speed data of the vehicle, and transmits the data to the data processing unit; The suspension controller is used to receive signals from a data processing unit and control the working state of a magnetorheological damper. The magnetorheological damper is equipped with a magnetorheological fluid and an electromagnetic coil. The magnetorheological damper changes the current passing through the electromagnetic coil according to a suspension adjustment signal to generate a magnetic field acting on the magnetorheological fluid. The data processing unit is equipped with a data fusion processing algorithm.

2. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The data fusion processing algorithm analyzes and processes the laser radar point cloud data collected by the laser radar, the vehicle body posture data collected by the vehicle posture sensor, and the vehicle driving speed collected by the vehicle speed sensor to obtain a real-time road condition score; and after the data fusion processing algorithm receives the data from the vehicle posture sensor and the vehicle speed sensor, the data processing unit processes these data to obtain vehicle driving parameters.

3. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The data processing unit stores a control signal set of the vehicle model and the magnetorheological damper model under different real-time road condition scores and vehicle driving parameters; and the data processing unit determines the corresponding control signal and transmits the control signal to the suspension controller.

4. The magnetorheological suspension semi-active feedback control system according to claim 3 is characterized in that: The vehicle driving parameters include, but are not limited to, acceleration, deceleration, and centripetal acceleration corresponding to emergency start, emergency braking, and emergency turning driving conditions.

5. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: Each of the magnetorheological dampers has a corresponding suspension controller, and the laser radar point cloud data collected by the laser radar is subjected to point cloud denoising using the data fusion processing algorithm, including the following steps: 1) Use the RANSAC algorithm to remove outliers; 2) Use DBSCAN clustering method to remove small isolated point clusters.

6. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The data fusion processing algorithm analyzes and scores the slope of the road on which the vehicle is traveling, including the following steps: 1) Select ground points within a certain range, fit the local plane based on the least squares method, and calculate the slope; 2) Setting the slope threshold; 3) Read the vehicle speed; 4) The slope scoring formula is: In the formula, k s is the slope influence coefficient, θ is the slope angle, This means that the slope has a greater impact when driving at high speeds.

7. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The data fusion processing algorithm analyzes and scores the smoothness of the road surface on which the vehicle is traveling, and includes the following steps: 1) Using height change statistics; 2) Calculate the standard deviation of the point cloud height in the local area; 3) Analyze the changes in the transverse / longitudinal slope of the road surface; 4) Use the International Road Roughness Index for measurement; 5) The scoring formula for road surface smoothness is: Where IRI is the current road roughness index, IRI max is the maximum tolerance flatness, k v is the speed influence coefficient, v is the current vehicle speed, v max The maximum safe speed is set.

8. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The data fusion processing algorithm analyzes and scores obstacles on the road surface where the vehicle is traveling, including the following steps: 1) Use DBSCAN or Euclidean clustering to extract obstacles; 2) Calculate the total number of obstacles; 3) Calculate the horizontal distance between the obstacle and the center line of the vehicle; 4) Calculate the volume of obstacles; 5) The obstacle scoring formula is: Where N obs is the total number of obstacles, d is the horizontal distance between the obstacle and the center line of the vehicle, and Vi is the volume of the obstacle.

9. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The data fusion processing algorithm scores the real-time traffic conditions, including the following steps: 1) Comprehensive analysis results of the data fusion processing algorithm on slope, road surface flatness and obstacles; 2) Weights are assigned to the slope, the road surface flatness and the obstacles, and normalized to obtain a real-time road condition score.

10. The magnetorheological suspension semi-active feedback control system according to claim 1, characterized in that: The suspension controller controls the change of the damping force of the magnetorheological damper, comprising the following steps: 1) The suspension controller outputs current according to the signal of the data processing unit; 2) The current passes through the electromagnetic coil in the magnetorheological damper to generate a magnetic field; 3) The magnetic field acts on the magnetorheological fluid in the magnetorheological damper to adjust its viscosity; 4) The change in viscosity of the magnetorheological fluid causes the change in damping force.

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