Suspension adjusting device for self-driving automobile

Abstract

The invention belongs to the technical field of automobile control, and particularly relates to a suspension adjusting device for an automatic driving automobile, which comprises a sensor module, a central control module, an actuator module, a management module and a communication and power supply module, and is characterized in that the sensor module comprises a road surface sensing unit, a vehicle state unit and an environment sensing unit; a plurality of sensors are used in cooperation to form a dynamic sensing network, various road condition information such as road surface evenness, bumping degree and gradient change in the vehicle driving process can be sensed in real time, vehicle driving states such as vehicle speed, acceleration and steering angle information can be sensed in real time, and according to the sensed data, real-time monitoring of the vehicle driving state can be realized. The hardness and damping of the suspension and the height of a chassis are automatically adjusted, self-adaptive adjustment of the suspension system is achieved, a user can conveniently use the suspension system, more comfortable driving and riding experience is provided for the user, and meanwhile the control stability of a vehicle is improved.

Description

Technical Field

[0001] The present invention belongs to the field of automobile control technology, and in particular relates to a suspension adjustment device for an autonomous driving vehicle. Background Art

[0002] The suspension system of an autonomous vehicle refers to the device that connects the vehicle's body and wheels. It is designed to absorb the impact and vibration caused by uneven roads, maintain wheel contact with the ground, and ensure the vehicle's comfort, stability, and handling. The suspension can usually adjust its stiffness and damping to ensure that the suspension is always in an optimal vibration reduction state, providing a better riding experience for the driver and passengers. However, when adjusting the stiffness and damping characteristics of the suspension of an autonomous vehicle according to road conditions, the road conditions are first determined based on the road the vehicle has traveled, and then adjusted accordingly. Therefore, the vehicle will only adjust to road conditions after driving on the road, making the adjustment method relatively passive, the adjustment effect is poor, and the user experience is poor. In order to solve the above problems, this application proposes a suspension adjustment device for an autonomous vehicle. Summary of the Invention

[0003] In order to solve the problems raised in the above background technology, the present invention provides a suspension adjustment device for an autonomous vehicle, which has the characteristic of being able to automatically adjust the suspension in advance according to road conditions.

[0004] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: A suspension adjustment device for an autonomous vehicle, comprising an adjustment mechanism, the adjustment mechanism comprising a first spring of the suspension, a first mounting seat, a second spring, a second mounting seat fixedly connected to the vehicle body, an adjustment shaft, a motor, and a hydraulic support rod, wherein one end of the first spring of the suspension is fixedly connected to the first mounting seat, the upper end of the first mounting seat is fixedly connected to the second spring, the second mounting seat is arranged above the first mounting seat, a mounting hole is formed in the second mounting seat, an adjustment shaft is connected through the surface of the second mounting seat, the adjustment shaft is connected to the top end of the second spring, the motor is fixedly mounted on the top surface of the second mounting seat, the hydraulic support rod is fixedly mounted on the top surface of the first mounting seat, and the sensor body is fixedly mounted on the top surface of the second mounting seat; The sensor body includes a sensor module, a central control module, an actuator module, a management module and a communication and power supply module; The motor and the adjustment shaft are engaged through gears, and the hydraulic support rod is symmetrically installed between the first mounting seat and the second mounting seat; The sensor module includes a road surface sensing unit, a vehicle state unit, and an environment sensing unit. The sensor module uses a variety of sensors to detect road surface conditions, vehicle dynamic conditions, and driving environment information in real time, providing data input for suspension adjustment. The central control module includes a data processing unit, an algorithm unit, and an adjustment control unit. The central control module integrates and processes the data information collected by the sensor module, calculates the optimal suspension parameters in real time through MPC and reinforcement learning algorithms, and issues adjustment instructions to control the suspension according to the calculated optimal suspension parameters; The actuator module includes a damping adjustment unit, a stiffness adjustment unit, and a height adjustment unit. The actuator module realizes stepless adjustment of damping, stiffness, and height through magnetorheological shock absorbers, air springs, and electric lifts according to the adjustment instructions of the central control module, thereby realizing suspension adjustment. The management module includes a mode selection unit, a parameter configuration unit, and a dynamic adaptation unit. The management module supports manual and automatic mode switching for suspension adjustment, and has a preset strategy library and user-defined parameter storage. It manually and automatically adjusts the suspension to comfort mode, sport mode, off-road mode, and custom mode, and performs real-time suspension fine-tuning based on the optimal suspension parameters in the central control module combined with vehicle load and map prediction. The communication and power supply module includes an on-board communication unit and a power management unit. The communication and power supply module is linked with the vehicle system through CAN / Ethernet to realize data interaction between the regulating device and the autonomous driving vehicle, and through the redundant power supply design, it ensures continuous power supply under extreme working conditions.

[0005] As a preferred suspension adjustment device for an autonomous vehicle of the present invention, the road surface sensing unit includes a laser radar and an acceleration sensor. The laser radar accurately detects the three-dimensional contour of the road ahead by emitting lasers and quantifies the road surface flatness. The acceleration sensor can measure the vertical acceleration of the vehicle body, calculate the frequency and amplitude of the bumps, and monitor the roll risk for the lateral acceleration.

[0006] As a preferred suspension adjustment device for an autonomous vehicle of the present invention, the vehicle state unit includes an IMU sensor, a height sensor and a tire pressure sensor. The IMU sensor monitors the three-dimensional motion state of the vehicle through a gyroscope and an accelerometer, and is used to predict changes in the vehicle body posture. The height sensor measures the relative displacement between the wheels and the vehicle body in real time to determine the compression and rebound state of the suspension. The tire pressure sensor monitors the tire pressure changes of the autonomous vehicle and calculates the vehicle center of gravity position in combination with the load distribution algorithm of the algorithm unit.

[0007] As a preferred suspension adjustment device for an autonomous vehicle of the present invention, the environmental perception unit includes a GPS and a meteorological sensor. The GPS ensures real-time update of map data through 5G-V2X communication, pre-reads the slope, curve curvature radius and road material within 200 meters ahead, and supports predictive adjustment of the suspension. The meteorological sensor detects temperature, humidity, and precipitation intensity, so that the algorithm unit can dynamically adjust the suspension strategy according to the environmental conditions of the autonomous vehicle.

[0008] As a preferred suspension adjustment device for an autonomous driving vehicle of the present invention, the data processing unit adopts Kalman filtering and deep learning models to eliminate sensor noise and generate a high-confidence comprehensive road condition assessment result. The algorithm unit is based on the vehicle dynamics model, learns driver preferences and special road conditions over a long period of time, and autonomously optimizes the control strategy library. The adjustment control unit parses the mode instructions from the driver and the autonomous driving system and issues suspension adjustment control instructions based on the calculation results of the algorithm unit.

[0009] As a preferred suspension adjustment device for an autonomous vehicle of the present invention, the damping adjustment unit adjusts the viscosity of the damping fluid by changing the magnetic field strength to adjust the suspension damping force. The stiffness adjustment unit adjusts the suspension stiffness by dynamically adjusting the airbag pressure through the air spring system and the air pump controlled by the ECU. The height adjustment unit increases the ground clearance of the chassis by using a ball screw and a brushless motor.

[0010] As a preferred suspension adjustment device for an autonomous vehicle of the present invention, the mode selection unit supports the driver to manually select the suspension mode through voice commands and touch screen sliding operations, the parameter configuration unit stores the basic parameters calibrated for the autonomous vehicle through a preset mode database, and the user can save personalized settings, and the dynamic adaptation unit uses a load compensation algorithm to correct the suspension parameters in real time according to the seat pressure sensor data.

[0011] As a preferred suspension adjustment device for an autonomous vehicle of the present invention, the on-board communication unit shares data with the ESP via the CAN / Ethernet bus to achieve collaborative control, and the power management unit adopts a redundant power supply design with a main battery and a large capacitor backup. When the main battery fails, the large capacitor provides emergency power.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention forms a dynamic perception network through the coordinated use of multiple sensors, which can perceive in real time various road condition information during vehicle driving, such as road surface flatness, bumpiness, slope changes and other information, as well as vehicle driving status, such as vehicle speed, acceleration, steering angle and other information, and can automatically adjust the hardness, damping and chassis height of the suspension according to the perceived data, to achieve adaptive adjustment of the suspension system, convenient for users to use, and provide users with a more comfortable driving and riding experience, while improving the vehicle's handling stability, and by setting a management module, it can realize multi-mode switching function, allowing users to select a suitable suspension mode from the preset mode database of the parameter configuration unit. Under different driving modes, the suspension adjustment device will be adjusted according to the preset parameters to meet the needs of different driving scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a schematic diagram of the overall structure of the present invention; Figure 2 It is a structural schematic diagram of the present invention; Figure 3 Schematic diagram of the structure of the sensor module in the present invention; Figure 4 This is a schematic diagram of the structure of the central control module in the present invention; Figure 5 Schematic diagram of the structure of the actuator module in the present invention; Figure 6 Schematic diagram of the structure of the management module in the present invention; Figure 7 This is a schematic diagram of the structure of the communication and power supply module in the present invention; Figure 8 Schematic diagram of the structure of the road surface sensing unit in the present invention; Figure 9 Schematic diagram of the structure of the vehicle status unit in the present invention; Figure 10 Schematic diagram of the structure of the environment perception unit in the present invention; In the picture: 1. Sensor module; 11. Road surface perception unit; 111. LiDAR; 112. Acceleration sensor; 12. Vehicle status unit; 121. IMU sensor; 122. Height sensor; 123. Tire pressure sensor; 13. Environmental perception unit; 131. GPS; 132. Weather sensor; 2. Central control module; 21. Data processing unit; 22. Algorithm unit; 23. Adjustment control unit; 3. Actuator module; 31. Damping adjustment unit; 32. Stiffness adjustment unit; 33. Height adjustment unit; 4. Management module; 41. Mode selection unit; 42. Parameter configuration unit; 43. Dynamic adaptation unit; 5. Communication and power module; 51. On-board communication unit; 52. Power management unit; 6. Adjustment mechanism; 61. First spring; 62. First mounting seat; 63. Second spring; 64. Second mounting seat; 65. Adjustment shaft; 66. Motor; 67. Hydraulic support rod; 7. Sensor body. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0015] Example 1 like Figures 1 to 9 As shown; In order to achieve automatic adjustment of the suspension in advance according to road conditions, this suspension adjustment device for an autonomous vehicle includes an adjustment mechanism 6, which includes a first spring 61 of the suspension, a first mounting seat 62, a second spring 63, a second mounting seat 64 fixedly connected to the vehicle body, an adjustment shaft 65, a motor 66 and a hydraulic support rod 67. One end of the first spring 61 of the suspension is fixedly connected to the first mounting seat 62, the upper end of the first mounting seat 62 is fixedly connected to the second spring 63, the second mounting seat 64 is arranged above the first mounting seat 62, and a mounting hole is opened on the second mounting seat 64. The surface of the second mounting seat 64 is connected with the adjustment shaft 65, and the adjustment shaft 65 is connected to the top of the second spring 63. The top surface of the second mounting seat 64 is fixedly installed with the motor 66, the top surface of the first mounting seat 62 is fixedly installed with the hydraulic support rod 67, and the top surface of the second mounting seat 64 is fixedly installed with the sensor body 7; The sensor body 7 includes a sensor module 1, a central control module 2, an actuator module 3, a management module 4 and a communication and power module 5; The sensor module 1 includes a road surface sensing unit 11, a vehicle state unit 12, and an environment sensing unit 13. The sensor module 1 uses a variety of sensors to detect road surface conditions, vehicle dynamic conditions, and driving environment information in real time, providing data input for suspension adjustment. The central control module 2 includes a data processing unit 21, an algorithm unit 22, and an adjustment control unit 23. The central control module 2 integrates and processes the data information collected by the sensor module 1, calculates the optimal suspension parameters in real time through the MPC and reinforcement learning algorithms, and issues adjustment instructions based on the calculated optimal suspension parameters to control the suspension. The actuator module 3 includes a damping adjustment unit 31, a stiffness adjustment unit 32, and a height adjustment unit 33. The actuator module 3 implements stepless adjustment of damping, stiffness, and height through magnetorheological shock absorbers, air springs, and electric lifts according to the adjustment instructions of the central control module 2, thereby achieving suspension adjustment. The management module 4 includes a mode selection unit 41, a parameter configuration unit 42, and a dynamic adaptation unit 43. The management module 4 supports manual and automatic mode switching for suspension adjustment, and has a preset strategy library and user-defined parameter storage. It manually and automatically adjusts the suspension to comfort mode, sport mode, off-road mode, and a custom mode. It also performs real-time suspension fine-tuning based on the optimal suspension parameters in the central control module 2, combined with vehicle load and map prediction. The communication and power supply module 5 includes an on-board communication unit 51 and a power management unit 52. The communication and power supply module 5 is linked to the vehicle system through CAN / Ethernet to realize data interaction between the regulating device and the autonomous driving vehicle, and through the redundant power supply design, it ensures continuous power supply under extreme working conditions.

[0016] In this embodiment: When in use, the user can use the mode selection unit 41 to issue suspension adjustment instructions through voice commands and touch screen sliding operations, and select the appropriate suspension mode from the preset mode database of the parameter configuration unit 42. When the driver selects the automatic suspension adjustment mode, the sensor module 1 will collect the internal and external environmental data of the self-driving car to form a dynamic perception network. The laser radar 111 scans the road surface 5-10 meters ahead to detect the depth of potholes and the frequency of continuous bumps. The acceleration sensor 112 captures the vibration spectrum of the vehicle body at a sampling rate to distinguish features such as speed bumps and gravel roads. The IMU sensor 121 outputs six-axis data in real time to calculate the roll angle of the vehicle body. The height sensor 122 measures the relative displacement of the wheel and the vehicle body in real time to determine the compression and rebound state of the suspension. The GPS 131 provides the slope of the 200 meters ahead, the curvature radius of the curve and the road material, and preloads the suspension lifting strategy. The data collected by the sensor module 1 will be transmitted to the central control module 2, and the Kalman filter will eliminate sensor noise and generate a comprehensive road condition assessment result. The algorithm unit 22 will autonomously optimize the control strategy library based on the vehicle dynamics model, driver preferences and special road conditions. The adjustment control unit 23 will parse the mode instructions from the driver and the automatic driving system and issue suspension adjustment control instructions based on the calculation results of the algorithm unit 22. When the actuator module 3 receives the suspension adjustment instruction, it will adjust the suspension through the damping adjustment unit 31, the stiffness adjustment unit 32 and the height adjustment unit 33, thereby realizing automatic adjustment of the suspension. In addition, through the coordinated use of multiple sensors, the suspension can be automatically adjusted according to the road conditions ahead before the autonomous driving car travels on the road section that needs adjustment, which is convenient for users to use and provides users with a more comfortable driving and riding experience.

[0017] Going further: like Figure 1 As shown; Combining the above: In an optional example, the motor 66 and the adjustment shaft 65 are engaged through gears, and the hydraulic support rod 67 is symmetrically installed between the first mounting seat 62 and the second mounting seat 64 .

[0018] Going further: like Figure 2 and Figure 7 As shown; Combining the above: In an optional embodiment, the road surface sensing unit 11 includes a laser radar 111 and an acceleration sensor 112. The laser radar 111 accurately detects the three-dimensional contour of the road ahead and quantifies the road surface flatness by emitting lasers. The acceleration sensor 112 can measure the vertical acceleration of the vehicle body, calculate the frequency and amplitude of the bumps, and monitor the roll risk for the lateral acceleration.

[0019] Going further: like Figure 2 and Figure 8 As shown; Combining the above: In an optional embodiment, the vehicle status unit 12 includes an IMU sensor 121, a height sensor 122 and a tire pressure sensor 123. The IMU sensor 121 monitors the three-dimensional motion state of the vehicle through a gyroscope and an accelerometer to predict changes in the vehicle body posture. The height sensor 122 measures the relative displacement between the wheel and the vehicle body in real time to determine the compression and rebound state of the suspension. The tire pressure sensor 123 monitors the tire pressure changes of the autonomous vehicle and calculates the center of gravity position of the vehicle in combination with the load distribution algorithm of the algorithm unit 22.

[0020] Going further: like Figure 2 and Figure 9 As shown; Combining the above: In an optional embodiment, the environmental perception unit 13 includes GPS 131 and a meteorological sensor 132. GPS 131 ensures real-time update of map data through 5G-V2X communication, pre-reads the slope, curve curvature radius and road material within 200 meters ahead, and supports predictive adjustment of the suspension. The meteorological sensor 132 detects temperature, humidity, and precipitation intensity, enabling the algorithm unit 22 to dynamically adjust the suspension strategy according to the environmental conditions of the autonomous driving vehicle.

[0021] Going further: like Figure 3 As shown; Combining the above: In an optional embodiment, the data processing unit 21 uses Kalman filtering and deep learning models to eliminate sensor noise and generate a high-confidence comprehensive road condition assessment result. The algorithm unit 22 is based on the vehicle dynamics model, learns driver preferences and special road conditions over a long period of time, and autonomously optimizes the control strategy library. The adjustment control unit 23 parses the mode instructions from the driver and the automatic driving system and issues suspension adjustment control instructions based on the calculation results of the algorithm unit 22.

[0022] Going further: like Figure 4 As shown; Combining the above: In an optional embodiment, the damping adjustment unit 31 adjusts the viscosity of the damping fluid by changing the magnetic field strength to adjust the suspension damping force. The stiffness adjustment unit 32 adjusts the suspension stiffness by dynamically adjusting the airbag pressure through the air spring system and the air pump controlled by the ECU. The height adjustment unit 33 increases the ground clearance of the chassis by using a ball screw and a brushless motor.

[0023] Going further: like Figure 5 As shown; Combining the above: In an optional embodiment, the mode selection unit 41 supports the driver to manually select the suspension mode through voice commands and touch screen sliding operations. The parameter configuration unit 42 stores the basic parameters of the automatic driving vehicle calibration through a preset mode database, and the user can save personalized settings. The dynamic adaptation unit 43 uses a load compensation algorithm to correct the suspension parameters in real time according to the seat pressure sensor data.

[0024] Going further: like Figure 6 As shown; Combining the above: In an optional embodiment, the on-board communication unit 51 shares data with the ESP via the CAN / Ethernet bus to achieve collaborative control. The power management unit 52 uses a redundant power supply design with a main battery and a large capacitor backup. When the main battery fails, the large capacitor provides emergency power.

[0025] The working principle and usage process of the present invention are as follows: When in use, the user can use the mode selection unit 41 to issue suspension adjustment instructions through voice commands and touch screen sliding operations, and select the appropriate suspension mode from the preset mode database of the parameter configuration unit 42. When the driver selects the automatic suspension adjustment mode, the sensor module 1 will collect the internal and external environmental data of the self-driving car to form a dynamic perception network. The laser radar 111 scans the road surface 5-10 meters ahead to detect the depth of potholes and the frequency of continuous bumps. The acceleration sensor 112 captures the vibration spectrum of the vehicle body at a sampling rate to distinguish features such as speed bumps and gravel roads. The IMU sensor 121 outputs six-axis data in real time to calculate the roll angle of the vehicle body. The height sensor 122 measures the relative displacement of the wheel and the vehicle body in real time to judge the compression and rebound state of the suspension. The GPS131 provides the slope of the 200 meters ahead, the curvature radius of the curve and the road material to preload the suspension lift. The data collected by the sensor module 1 will be transmitted to the central control module 2, and the Kalman filter will eliminate the sensor noise and generate a comprehensive road condition assessment result. The algorithm unit 22 will autonomously optimize the control strategy library based on the vehicle dynamics model, driver preferences and special road conditions. The adjustment control unit 23 will parse the mode instructions from the driver and the automatic driving system and issue a suspension adjustment control instruction according to the calculation result of the algorithm unit 22. When the actuator module 3 receives the suspension adjustment instruction, it will adjust the suspension through the damping adjustment unit 31, the stiffness adjustment unit 32 and the height adjustment unit 33, thereby realizing automatic adjustment of the suspension. Moreover, through the coordinated use of multiple sensors, the suspension can be automatically adjusted according to the road conditions ahead before the autonomous driving car travels on the road section that needs adjustment, which is convenient for users to use and provides users with a more comfortable driving and riding experience.

[0026] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A suspension adjustment device for an autonomous vehicle, characterized in that: The invention comprises an adjusting mechanism (6), wherein the adjusting mechanism (6) comprises a first spring (61) of the suspension, a first mounting seat (62), a second spring (63), a second mounting seat (64) fixedly connected to the vehicle body, an adjusting shaft (65), a motor (66) and a hydraulic support rod (67), one end of the first spring (61) of the suspension is fixedly connected to the first mounting seat (62), the upper end of the first mounting seat (62) is fixedly connected to the second spring (63), the second mounting seat (64) is arranged above the first mounting seat (62), a mounting hole is provided on the second mounting seat (64), the surface of the second mounting seat (64) is connected with the adjusting shaft (65), the adjusting shaft (65) is connected to the top end of the second spring (63), the top surface of the second mounting seat (64) is fixedly mounted with the motor (66), the top surface of the first mounting seat (62) is fixedly mounted with the hydraulic support rod (67), and the top surface of the second mounting seat (64) is fixedly mounted with the sensor body (7); The sensor body (7) comprises a sensor module (1), a central control module (2), an actuator module (3), a management module (4) and a communication and power supply module (5); The sensor module (1) comprises a road surface sensing unit (11), a vehicle state unit (12) and an environment sensing unit (13). The sensor module (1) detects road surface state, vehicle dynamic state and driving environment information in real time through the coordinated use of multiple sensors, thereby providing data input for suspension adjustment. The central control module (2) includes a data processing unit (21), an algorithm unit (22) and an adjustment control unit (23). The central control module (2) integrates and processes the data information collected by the sensor module (1), calculates the optimal suspension parameters in real time through the MPC and reinforcement learning algorithms, and issues adjustment instructions to control the suspension to adjust according to the calculated optimal suspension parameters; The actuator module (3) includes a damping adjustment unit (31), a stiffness adjustment unit (32) and a height adjustment unit (33). The actuator module (3) realizes stepless adjustment of damping, stiffness and height through magnetorheological shock absorbers, air springs and electric lifting according to the adjustment instructions of the central control module (2), thereby realizing suspension adjustment. The management module (4) includes a mode selection unit (41), a parameter configuration unit (42) and a dynamic adaptation unit (43). The management module (4) provides support for manual mode switching and automatic mode switching for suspension adjustment, and presets a strategy library and user-defined parameter storage, adjusts the suspension to a comfort mode, a sports mode, an off-road mode and a custom mode in a manual and automatic manner, and performs real-time fine-tuning of the suspension based on the optimal suspension parameters in the central control module (2) combined with vehicle load and map prediction; The communication and power supply module (5) includes an on-board communication unit (51) and a power management unit (52). The communication and power supply module (5) is linked with the vehicle system via CAN / Ethernet to achieve data interaction between the regulating device and the autonomous driving vehicle, and ensures continuous power supply under extreme working conditions through redundant power supply design.

2. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The motor (66) and the adjustment shaft (65) are engaged via gears, and the hydraulic support rod (67) is symmetrically mounted between the first mounting seat (62) and the second mounting seat (64).

3. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The road surface sensing unit (11) includes a laser radar (111) and an acceleration sensor (112). The laser radar (111) accurately detects the three-dimensional profile of the road ahead by emitting laser light and quantifies the road surface smoothness. The acceleration sensor (112) can measure the vertical acceleration of the vehicle body, calculate the frequency and amplitude of the bumps, and monitor the roll risk for the lateral acceleration.

4. The suspension adjustment device for an autonomous vehicle according to claim 1, wherein: The vehicle state unit (12) includes an IMU sensor (121), a height sensor (122), and a tire pressure sensor (123). The IMU sensor (121) monitors the three-dimensional motion state of the vehicle through a gyroscope and an accelerometer, and is used to predict changes in the vehicle body posture. The height sensor (122) measures the relative displacement between the wheel and the vehicle body in real time to determine the compression and rebound state of the suspension. The tire pressure sensor (123) monitors the tire pressure changes of the autonomous vehicle and calculates the center of gravity position of the vehicle in combination with the load distribution algorithm of the algorithm unit (22).

5. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The environmental perception unit (13) includes a GPS (131) and a meteorological sensor (132). The GPS (131) ensures real-time update of map data through 5G-V2X communication, pre-reads the slope, curve radius and road material within 200 meters ahead, and supports predictive adjustment of the suspension. The meteorological sensor (132) detects temperature, humidity and precipitation intensity, so that the algorithm unit (22) can dynamically adjust the suspension strategy according to the environmental conditions of the autonomous vehicle.

6. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The data processing unit (21) uses Kalman filtering and a deep learning model to eliminate sensor noise and generate a high-confidence comprehensive road condition assessment result. The algorithm unit (22) is based on a vehicle dynamics model, learns driver preferences and special road conditions over a long period of time, and autonomously optimizes the control strategy library. The adjustment control unit (23) parses mode instructions from the driver and the automatic driving system and issues suspension adjustment control instructions based on the calculation results of the algorithm unit (22).

7. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The damping adjustment unit (31) adjusts the viscosity of the damping fluid by changing the magnetic field strength to adjust the suspension damping force. The stiffness adjustment unit (32) adjusts the suspension stiffness by dynamically adjusting the airbag pressure through the air spring system controlled by the ECU. The height adjustment unit (33) adjusts the increase in the chassis ground clearance by using a ball screw and a brushless motor.

8. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The mode selection unit (41) supports the driver to manually select the suspension mode through voice commands and touch screen sliding operations. The parameter configuration unit (42) stores the basic parameters calibrated by the autonomous driving vehicle through a preset mode database, and can be saved by the user for personalized settings. The dynamic adaptation unit (43) uses a load compensation algorithm to correct the suspension parameters in real time according to the seat pressure sensor data.

9. The suspension adjustment device for an autonomous vehicle according to claim 1, characterized in that: The vehicle-mounted communication unit (51) shares data with the ESP via a CAN / Ethernet bus to achieve collaborative control. The power management unit (52) utilizes a redundant power supply design with a main battery and a large capacitor backup. When the main battery fails, the large capacitor provides emergency power.

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