An intelligent automobile tailboard hydraulic control system and method based on an internet of things

Abstract

The application provides a kind of based on Internet of Things Intelligent automobile tailgate hydraulic control system and method, it is related to Internet of Things technical field, in system: multiple sensor module includes pressure sensor, displacement sensor and inclination sensor, for real-time acquisition automobile tailgate's load state and environmental parameter;PLC control module is connected with multiple sensor module and Internet of Things communication module signal, for receiving automobile tailgate's load state and environmental parameter and according to intelligent control algorithm generates control instruction;Hydraulic execution module is connected with PLC control module signal, for receiving control instruction to drive tailgate to execute lifting and angle adjustment action;Intelligent control algorithm includes one-key automatic leveling algorithm and anti-collision protection algorithm, for according to the feedback signal of multiple sensor module dynamically adjusts hydraulic output.Remote monitoring and management are realized by Internet of Things technology, provide efficient, reliable technical support for modern intelligent logistics system.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) technology, and in particular to an IoT-based intelligent automotive tailgate hydraulic control system and method. Background Technology

[0002] With the rapid development of the logistics industry, vehicle tailgates, as important equipment for loading and unloading goods, directly affect logistics efficiency and safety in terms of their level of intelligence and automation.

[0003] Traditional automotive tailgate hydraulic control systems rely primarily on manual operation or simple mechanical control, resulting in slow response, low precision, and a lack of environmental adaptability. Especially under complex conditions, such as uneven ground or heavy loads, improper manual adjustments can easily lead to tailgate tilting, uneven load distribution, or even equipment damage. Furthermore, traditional systems lack real-time monitoring and data interaction capabilities, hindering remote management and dynamic optimization, thus limiting their application in modern intelligent logistics systems. In recent years, the rise of IoT technology has provided new opportunities for equipment intelligence. Through multi-sensor fusion and remote communication, real-time monitoring and precise control of equipment status can be achieved. However, current intelligent solutions for automotive tailgate hydraulic systems remain relatively simplistic, lacking integrated sensor data processing and intelligent algorithm optimization, particularly in adaptive control for dynamic load changes and complex environments.

[0004] Therefore, developing an IoT-based intelligent automotive tailgate hydraulic control system that integrates multi-sensor modules, a PLC control module, an IoT communication module, and a hydraulic actuator module, and uses intelligent algorithms to achieve one-click automatic leveling and collision avoidance protection, has become an important direction for solving the aforementioned problems. This system aims to improve the automation level, safety, and adaptability of tailgate operation through real-time data acquisition and intelligent control algorithms, meeting the demands of modern logistics for efficient, safe, and intelligent equipment. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent automotive tailgate hydraulic control system and method based on the Internet of Things, in order to solve the problems pointed out in the background art.

[0006] In a first aspect, embodiments of the present invention provide an intelligent automotive tailgate hydraulic control system based on the Internet of Things (IoT), comprising a PLC control module, a multi-sensor module, an IoT communication module, and a hydraulic actuation module; the multi-sensor module includes a pressure sensor, a displacement sensor, and a tilt sensor, used to collect the load status and environmental parameters of the automotive tailgate in real time; the PLC control module is signal-connected to the multi-sensor module and the IoT communication module, used to receive the load status and environmental parameters of the automotive tailgate and generate control commands according to an intelligent control algorithm; the hydraulic actuation module is signal-connected to the PLC control module, used to receive the control commands to drive the tailgate to perform lifting and angle adjustment actions;

[0007] The intelligent control algorithm includes a one-click automatic leveling algorithm and an anti-collision protection algorithm, which are used to dynamically adjust the hydraulic output based on the feedback signals from the multi-sensor module.

[0008] Optionally, the system further includes a safety protection module connected to the PLC control module via signals. The safety protection module includes an overload alarm unit, an emergency braking unit, and a fault self-diagnosis unit.

[0009] Optionally, the system further includes an emergency manual operation device, which is mechanically or hydraulically connected to the hydraulic actuator module and is used to manually control the tailgate in the event of a power outage or malfunction.

[0010] Optionally, the hydraulic actuator module includes a hydraulic pump, a hydraulic cylinder, and a control valve group controlled by the PLC control module.

[0011] Optionally, the PLC control module is configured to receive feedback signals from the displacement sensor and tilt sensor, and adjust the control commands output to the hydraulic actuator in real time through a closed-loop control algorithm to achieve precise positioning of the tailplate movement.

[0012] Optionally, the IoT communication module is used to upload system status data, fault codes and sensor data to the remote monitoring platform, and to receive instructions from the remote monitoring platform.

[0013] Optionally, the multi-sensor module further includes a terrain scanning unit; the PLC control module is further configured to: receive terrain data from the terrain scanning unit and assess ground bearing capacity before the tailplate is deployed; if soft ground is detected, automatically trigger the anti-sinking mode; wherein, in the anti-sinking mode, the PLC control module controls the hydraulic actuator to reduce the impact force when the tailplate contacts the ground and dynamically maintain a safe grounding pressure.

[0014] Optionally, the system further includes a precise positioning unit; the Internet of Things communication module is configured to: communicate and network with the intelligent vehicle tailgate hydraulic control system of a neighboring vehicle, and based on the data from the precise positioning unit, enable the tailgate of this vehicle and the tailgate of the neighboring vehicle to coordinately adjust their height and angle to form a continuous collaborative loading and unloading operation surface.

[0015] Optionally, the multi-sensor module further includes an inertial measurement unit for acquiring high-frequency inertial measurement data of the vehicle;

[0016] The PLC control module is further configured as follows:

[0017] After the tailplate operation command is issued, high-frequency inertial measurement data from the inertial measurement unit within the time window prior to the issuance of the operation command is acquired.

[0018] Based on the inertial measurement data, the dominant vibration modes of the cargo inside the vehicle are estimated;

[0019] A control signal is generated, the spectral characteristics of which are configured to actively suppress the dominant vibration mode;

[0020] The hydraulic actuator is controlled to perform the main lifting action while applying high-frequency micro-motion to the tail plate platform according to the control signal, so as to counteract the residual vibration inside the cargo.

[0021] Secondly, an embodiment of the present invention provides an intelligent vehicle tailgate hydraulic control method based on the Internet of Things, comprising:

[0022] The load status and environmental parameters of the vehicle's tailgate are collected in real time through a multi-sensor module, which includes a pressure sensor, a displacement sensor, and a tilt sensor.

[0023] The load status and environmental parameters are received by the PLC control module, and control commands are generated according to the intelligent control algorithm. The intelligent control algorithm includes a one-key automatic leveling algorithm and an anti-collision protection algorithm, which are used to dynamically adjust the hydraulic output according to the feedback signals of the multi-sensor module.

[0024] Remote data transmission and monitoring are achieved through an IoT communication module;

[0025] The control command is received by the hydraulic actuator module, which then drives the tailgate to perform lifting and angle adjustment actions.

[0026] The present invention has achieved the following beneficial effects:

[0027] This invention provides an IoT-based intelligent automotive tailgate hydraulic control system. By integrating a multi-sensor module, a PLC control module, an IoT communication module, and a hydraulic actuation module, combined with a one-click automatic leveling algorithm and a collision avoidance protection algorithm, the system achieves intelligent and automated tailgate operation. The system can collect load status and environmental parameters in real time, dynamically adjust hydraulic output, ensure the stability and safety of the tailgate under complex working conditions, significantly improve operational efficiency, reduce the need for manual intervention and operational risks, and simultaneously achieve remote monitoring and management through IoT technology, providing efficient and reliable technical support for modern intelligent logistics systems.

[0028] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0029] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0030] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0031] Figure 1 This is a schematic diagram of an IoT-based intelligent vehicle tailgate hydraulic control system according to an embodiment of the present invention;

[0032] Figure 2 This is a flowchart of an intelligent vehicle tailgate hydraulic control method based on the Internet of Things in an embodiment of the present invention. Detailed Implementation

[0033] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0034] Example 1:

[0035] The core of this research and development approach is to enhance the intelligence and adaptability of the hydraulic control system for automotive tailgates. Addressing the shortcomings of traditional systems under complex operating conditions, it proposes an integrated solution based on the Internet of Things (IoT). First, a multi-sensor module, including pressure, displacement, and tilt sensors, is designed to collect real-time load status and environmental parameters, providing a data foundation for precise control. Second, a PLC control module is developed, incorporating intelligent control algorithms (such as one-click automatic leveling and collision avoidance algorithms) to analyze and process sensor data in real time, generating dynamic control commands to adapt to tailgate adjustment needs under different operating conditions. Simultaneously, an IoT communication module is introduced to enable data interaction between the system and a remote management platform, supporting real-time monitoring and remote optimization. Finally, a hydraulic execution module translates the control commands into precise lifting and angle adjustment actions, ensuring efficient system execution. The entire research and development process emphasizes the synergy of sensor fusion, algorithm optimization, and system integration, aiming to build a highly efficient, safe, and adaptable intelligent control system.

[0036] Figure 1 This application provides a schematic diagram of an IoT-based intelligent vehicle tailgate hydraulic control system, as shown in the embodiment. Figure 1 As shown, the system includes a PLC control module 1, a multi-sensor module 2, an IoT communication module 3, and a hydraulic actuation module 4. The multi-sensor module 2 includes a pressure sensor, a displacement sensor, and a tilt sensor, used to collect the load status and environmental parameters of the vehicle's tailgate in real time. The PLC control module 1 is signal-connected to the multi-sensor module 2 and the IoT communication module 3, used to receive the load status and environmental parameters of the vehicle's tailgate and generate control commands according to an intelligent control algorithm. The hydraulic actuation module 4 is signal-connected to the PLC control module 1, used to receive the control commands to drive the tailgate to perform lifting and angle adjustment actions.

[0037] The intelligent control algorithm includes a one-click automatic leveling algorithm and an anti-collision protection algorithm, which are used to dynamically adjust the hydraulic output based on the feedback signals from the multi-sensor module.

[0038] In this embodiment of the invention, the IoT-based intelligent automotive tailgate hydraulic control system integrates a PLC control module, a multi-sensor module, an IoT communication module, and a hydraulic actuation module to achieve intelligent control of tailgate lifting and angle adjustment. The PLC control module, as the core controller, receives feedback data from the multi-sensor module via a digital signal interface. This data includes tailgate load pressure measured by a pressure sensor (unit: MPa, obtained by measuring hydraulic oil pressure and converting it into an electrical signal using a piezoelectric element built into the pressure sensor, range 0-40 MPa, accuracy ±0.5%), tailgate lifting height measured by a displacement sensor (unit: mm, detected by a magnetostrictive displacement sensor to detect hydraulic cylinder piston displacement, range 0-2000 mm, accuracy ±0.1 mm), and tailgate tilt angle measured by a tilt sensor (unit: degrees, detected by a MEMS tilt sensor to detect angle changes, range ±30°, accuracy ±0.1°). The multi-sensor module collects these parameters in real time and transmits them to the PLC control module via a CAN bus. The PLC control module runs intelligent control algorithms, including a one-click automatic leveling algorithm and a collision avoidance protection algorithm. The one-click automatic leveling algorithm, based on tilt sensor data, adjusts the output pressure and flow rate of the hydraulic actuator module through PID control logic (proportional, integral, and derivative parameters are Kp=0.8, Ki=0.2, and Kd=0.05, respectively, obtained based on experimental calibration) to keep the tailgate horizontal (error ≤0.5°). The anti-collision protection algorithm detects sudden load changes (pressure change rate ≥5MPa / s, calculated based on a sensor sampling frequency of 100Hz) using a pressure sensor, triggering the hydraulic actuator module to reduce pressure to avoid overload. The IoT communication module uses a 4G / 5G module (supporting MQTT protocol, data transmission rate ≥10Mbps) to upload sensor data and control status to a remote monitoring platform and receive remote commands. The hydraulic actuator module regulates the hydraulic oil flow rate (range 0-50L / min, accuracy ±1L / min) through the control valve group, driving the hydraulic cylinder to complete the tailgate lifting (speed 0-0.5m / s) and angle adjustment (angle change rate 0-5° / s). All parameters are directly measured by sensor hardware or calculated by the PLC's internal algorithm to ensure system real-time performance and accuracy.

[0039] Here is a specific implementation example:

[0040] In a heavy-duty truck tailgate control scenario, the system is deployed on the tailgate hydraulic mechanism. A pressure sensor (Honeywell PX3, range 0-40MPa) is installed at the hydraulic cylinder inlet to collect load pressure in real time, for example, detecting a stable load of 10MPa. A displacement sensor (MTSTemposonics R series, range 0-2000mm) is installed on the hydraulic cylinder piston to measure the tailgate lifting height as 1500mm. A tilt sensor (Bosch BNO055, range ±30°) is fixed at the bottom of the tailgate to detect a tilt angle of 2°. This data is transmitted to the PLC control module (Siemens S7-1200) via the CAN bus at 100ms intervals. The PLC runs a one-button automatic leveling algorithm. After detecting a 2° tilt, it calculates the output through PID control logic and adjusts the control valve group (Bosch Rexroth 4WRPEH) to increase the hydraulic oil flow to 20L / min, driving the hydraulic cylinder to correct the tailgate angle to 0°±0.5° in 3 seconds. The anti-collision protection algorithm detects a sudden pressure surge to 15MPa (rate of change 6MPa / s) during load handling and immediately reduces the hydraulic oil flow to 5L / min to prevent equipment overload. The IoT communication module (model: Quectel EC25, 4G connection) uploads sensor data (pressure, displacement, angle) and system status to a remote monitoring platform via the MQTT protocol. The platform issues a command to raise the tailgate to 1800mm. Upon receiving the command, the PLC controls the hydraulic actuator to complete the action, maintaining a stable lifting speed of 0.3m / s. This system significantly improves the automation level of tailgate operation, reduces manual intervention, and ensures the safety and stability of load handling.

[0041] This application provides an IoT-based intelligent automotive tailgate hydraulic control system. By integrating a multi-sensor module, a PLC control module, an IoT communication module, and a hydraulic actuation module, combined with a one-click automatic leveling algorithm and a collision avoidance protection algorithm, the system achieves intelligent and automated tailgate operation. The system can collect load status and environmental parameters in real time, dynamically adjust hydraulic output, ensure the stability and safety of the tailgate under complex working conditions, significantly improve operational efficiency, reduce the need for manual intervention and operational risks, and simultaneously achieve remote monitoring and management through IoT technology, providing efficient and reliable technical support for modern intelligent logistics systems.

[0042] Example 2:

[0043] In some embodiments, the system further includes a safety protection module that is signal-connected to the PLC control module, the safety protection module including an overload alarm unit, an emergency braking unit, and a fault self-diagnosis unit.

[0044] In this embodiment of the invention, the safety protection module, through signal connection with the PLC control module, integrates an overload alarm unit, an emergency braking unit, and a fault self-diagnosis unit to enhance system safety. The overload alarm unit monitors the tailplate load based on pressure sensor data (range 0-40MPa, accuracy ±0.5%, measured by piezoelectric elements to measure hydraulic oil pressure) and sets an overload threshold (e.g., 30MPa, determined through statistical analysis of historical load data, calculated as average load plus twice the standard deviation). When the load exceeds the threshold, an audible and visual alarm is triggered (the alarm outputs an 80dB sound and a flashing red LED, response time ≤100ms). The emergency braking unit, through PLC detection of pressure surges (rate of change ≥5MPa / s, calculated based on a 100Hz sampling frequency) or tilt anomalies (angle deviation ≥10°, measured by a tilt sensor), sends a stop command to the hydraulic actuator module, controlling the valve group to close the hydraulic circuit (closing time ≤50ms). The fault self-diagnosis unit identifies system faults (such as sensor disconnection or hydraulic pump malfunction) by collecting data on the PLC's internal operating status (e.g., CPU utilization, ranging from 0-100%, obtained through the PLC's built-in monitoring program) and sensor signal integrity (signal loss rate ≤0.1%, calculated through CAN bus data packet verification). It then generates fault codes (e.g., E001 indicates a pressure sensor fault, defined by the PLC fault mapping table). These parameters are measured directly by sensors or calculated by PLC algorithms, ensuring that the safety protection module can quickly respond to anomalies and record fault information for subsequent maintenance.

[0045] Here is a specific implementation example:

[0046] In the tailgate system of a logistics truck, the safety protection module and the PLC control module (Siemens S7-1200) are connected via a CAN bus. The overload alarm unit detects a load pressure of 32 MPa from the pressure sensor (Honeywell PX3), exceeding the preset threshold of 30 MPa (based on historical data, with an average load of 20 MPa and a standard deviation of 5 MPa). This triggers an audible and visual alarm (model: Patlite LKEH, 80dB buzzer and red LED) to alert the operator to reduce the load; the alarm response time is 80 ms. When the emergency braking unit detects a tailgate tilt angle of 12° (exceeding the threshold of 10°) from the tilt sensor (Bosch BNO055) while loading a heavy load, the PLC immediately sends a stop command to the control valve assembly (Bosch Rexroth 4WRPEH), shutting off the hydraulic circuit and stopping the tailgate movement; the shutdown time is 40 ms. The fault self-diagnosis unit detects a pressure sensor signal loss rate of 0.2% (exceeding the threshold of 0.1%) through the PLC monitoring program, generates fault code E001, and uploads it to the remote monitoring platform via the IoT communication module, prompting maintenance personnel to replace the sensor. Maintenance personnel locate the problem based on the fault code, replace the sensor, and the system returns to normal. This safety protection module effectively prevents accidents caused by overload, tipping, and equipment failure, improving the safety of tailgate operation.

[0047] Example 3:

[0048] In some embodiments, the system further includes an emergency manual operation device, which is mechanically or hydraulically connected to the hydraulic actuator module, for manually controlling the tailgate in the event of a power outage or malfunction of the system.

[0049] In this embodiment of the invention, the emergency manual operation device is connected to the hydraulic actuator module via a mechanical or hydraulic connection to ensure manual control of the tailgate lifting and angle adjustment in the event of a power outage or malfunction. The device includes a manual pump (output pressure 0-25MPa, converted to hydraulic oil pressure via handle torque, torque range 10-50N·m, calibrated through mechanical testing) and a manual valve (controlling the oil circuit opening and closing, opening time ≤200ms, driven by a mechanical spring). In the event of a power outage or malfunction, the operator applies torque (e.g., 30N·m, measured with a torque wrench) through the manual pump to generate hydraulic oil pressure, driving the hydraulic cylinder (piston diameter 50mm, stroke 0-2000mm) to lift the tailgate (speed 0-0.1m / s). The manual valve adjusts the oil flow rate (0-10L / min) by rotating the valve (0-90°, calibrated via a dial), controlling the tailgate angle change (rate 0-2° / s). The device is also equipped with a pressure gauge (range 0-40MPa, accuracy ±1%) and an angle indicator (range ±30°, accuracy ±0.5°), which display the hydraulic oil pressure and tailgate angle in real time, respectively. The parameters are read directly through mechanical instruments. These parameters ensure that the operator can accurately control the tailgate in the absence of power, meeting emergency operation needs.

[0050] Here is a specific implementation example:

[0051] In the tailgate system of a transport vehicle, an emergency manual operating device is installed next to the hydraulic actuator module. A manual pump (model: Enerpac P-39, maximum output 25MPa) generates hydraulic pressure via a handle. For example, if the operator applies a torque of 40 N·m (measured with a torque wrench), a pressure of 15 MPa is generated, driving a hydraulic cylinder (piston diameter 50 mm) to raise the tailgate to a height of 1000 mm at a speed of 0.08 m / s, taking 12 seconds. A manual valve (model: YukenDSG-01) adjusts the oil flow to 5 L / min by rotating it to 45° (diagram confirmation), adjusting the tailgate angle from 5° to 0° in 5 seconds. A pressure gauge (model: WIKA213.53, range 0-40 MPa) displays the current oil pressure as 15 MPa, and an angle indicator (mechanical, range ±30°) displays the tailgate angle as 0° ±0.5°. In a system power outage scenario, the operator manually operated the device to raise and level the tailgate, successfully loading and unloading goods and avoiding downtime losses. This device provides a reliable emergency control measure for the system, ensuring operational continuity and safety.

[0052] Example 4:

[0053] In some embodiments, the hydraulic actuation module includes a hydraulic pump, a hydraulic cylinder, and a control valve group controlled by the PLC control module.

[0054] In this embodiment of the invention, the hydraulic actuator module consists of a hydraulic pump, a hydraulic cylinder, and a control valve assembly. It receives control commands (voltage signal 0-10V, current signal 4-20mA) from the PLC control module to drive the tailplate movement. The hydraulic pump (output pressure 0-40MPa, flow rate 0-50L / min, calibrated by a motor speed of 1800rpm) provides hydraulic oil power, and its parameters are measured by a built-in pressure sensor (range 0-40MPa, accuracy ±0.5%) and a flow meter (range 0-50L / min, accuracy ±1%). The hydraulic cylinder (piston diameter 50mm, stroke 0-2000mm) converts the hydraulic oil pressure into mechanical motion, driving the tailplate to lift (speed 0-0.5m / s, calculated by dividing the flow rate by the piston cross-sectional area) and adjust the angle (rate 0-5° / s, calculated by the hydraulic oil distribution ratio). The control valve assembly (proportional valve, model: Bosch Rexroth 4WRPEH) adjusts the oil flow and pressure according to PLC commands, with a response time ≤50ms and a flow regulation accuracy of ±1L / min. All parameters are acquired in real time by sensors or calculated based on the hydraulic system characteristics by PLC algorithms, ensuring that the hydraulic actuator responds to control commands efficiently and accurately.

[0055] Here is a specific implementation example:

[0056] In the tailgate system of a cold chain logistics vehicle, the hydraulic actuator module is equipped with a hydraulic pump (model: Parker PV series, maximum pressure 40MPa, flow rate 50L / min), which is driven by a motor (speed 1800rpm) to generate 20MPa oil pressure and 30L / min flow rate. Pressure sensors and flow meters confirm the accuracy of the parameters. The hydraulic cylinder (piston diameter 50mm, stroke 2000mm) receives oil pressure and drives the tailgate to rise from 0mm to 1500mm at a speed of 0.4m / s, taking 3.75 seconds. The control valve group receives a 4-20mA signal (corresponding to a flow rate of 0-50L / min) from the PLC (Siemens S7-1200), adjusts the flow rate to 25L / min, and adjusts the tailgate angle from 3° to 0° in 4 seconds. The parameters are monitored in real time by a pressure sensor (Honeywell PX3) and a flow meter (Omega FLR1000) to ensure the error is within ±1%. During a loading and unloading operation, the hydraulic actuator quickly completed the lifting and leveling of the tail plate according to the PLC instructions, improving loading and unloading efficiency by 20% and demonstrating the advantages of high precision and high reliability.

[0057] Example 5:

[0058] In some embodiments, the PLC control module is configured to receive feedback signals from the displacement sensor and the tilt sensor, and adjust the control commands output to the hydraulic actuator module in real time through a closed-loop control algorithm to achieve precise positioning of the tailplate movement.

[0059] In this embodiment of the invention, the PLC control module receives feedback signals from a displacement sensor (range 0-2000mm, accuracy ±0.1mm, measuring piston displacement based on the magnetostrictive principle) and an inclination sensor (range ±30°, accuracy ±0.1°, measuring angle based on MEMS technology) through a closed-loop control algorithm. It then adjusts the control commands of the hydraulic actuator module (voltage 0-10V, current 4-20mA) in real time to achieve precise positioning of the tailplate movement. The closed-loop control algorithm employs PID control logic, with parameters including a proportional coefficient Kp = 0.8, an integral coefficient Ki = 0.2, and a derivative coefficient Kd = 0.05 (calibrated using the Ziegler-Nichols method: initially setting Ki = 0 and Kd = 0, gradually increasing Kp until system oscillation occurs, recording the oscillation period, and calculating Ki and Kd). The algorithm calculates the control output based on displacement deviation (difference between target height and actual height, unit: mm) and angle deviation (difference between target angle and actual angle, unit: degrees), adjusting the oil flow rate of the control valve group (0-50 L / min, accuracy ±1 L / min). The algorithm executes every 10 ms, collecting sensor data, calculating deviations, and updating the output to ensure positioning accuracy (height error ≤ 1 mm, angle error ≤ 0.5°). Parameters are directly measured by sensors. The algorithm is implemented in C language within the PLC and runs on a real-time operating system (RTOS) to ensure low latency.

[0060] Here is a specific implementation example:

[0061] In the tailgate system of an engineering transport vehicle, the PLC control module (Siemens S7-1200) runs a closed-loop control algorithm. It receives tailgate height feedback of 1500mm (target 1600mm, deviation 100mm) from a displacement sensor (MTSTemposonics R series) and angle feedback of 2° (target 0°, deviation 2°) from a tilt sensor (Bosch BNO055). The algorithm calculates the PID output in 10ms cycles, with Kp=0.8, Ki=0.2, and Kd=0.05, generating a 4-20mA signal to control the valve group (Bosch Rexroth 4WRPEH). This adjusts the flow rate to 30L / min, driving the hydraulic cylinder to raise the tailgate to 1600mm±1mm in 2.5 seconds, while simultaneously correcting the angle to 0°±0.5° in 3 seconds. Parameters are acquired in real-time via sensors, and the PLC's internal RTOS ensures algorithm execution latency is less than 5ms. During a heavy-load operation, the tailgate needs to be precisely positioned at a height of 1600mm and an angle of 0°. The closed-loop control algorithm responds quickly, and the positioning error is controlled within 1mm and 0.5°, ensuring loading and unloading accuracy and safety.

[0062] Example 6:

[0063] In some embodiments, the IoT communication module is used to upload system status data, fault codes and sensor data to a remote monitoring platform, and to receive instructions from the remote monitoring platform.

[0064] In this embodiment of the invention, the IoT communication module uploads system status data (PLC operating status, range 0-100%, obtained through the PLC monitoring program), fault codes (e.g., E001, generated through the PLC fault mapping table), and sensor data (pressure 0-40MPa, displacement 0-2000mm, angle ±30°, collected by sensors) to the remote monitoring platform via a 4G / 5G network (supporting the MQTT protocol, transmission rate ≥10Mbps, based on the LTECat4 technology of the Quectel EC25 module). It also receives instructions from the platform (e.g., adjusting the tailplate height, in MQTT message format). The module collects data at 100ms intervals, encrypts the data using an encryption algorithm (AES-128, 128-bit key length, implemented based on the OpenSSL library, encryption time ≤10ms) before uploading. The remote monitoring platform parses the data using a cloud server (e.g., AWS EC2) to generate visual reports (e.g., pressure trend charts) and control instructions (e.g., adjusting the height to 1800mm). The module receives commands by subscribing to topics via MQTT (e.g., / vehicle / tailgate / control), decrypts them, and transmits them to the PLC. Parameters are directly acquired by sensors and the PLC, with communication latency ≤200ms (measured via ping test), ensuring the real-time performance and security of remote monitoring.

[0065] Example 7:

[0066] In some embodiments, the multi-sensor module further includes a terrain scanning unit; the PLC control module is further configured to: receive terrain data from the terrain scanning unit and assess ground bearing capacity before the tailplate is deployed; if soft ground is detected, automatically trigger an anti-sinking mode; wherein, in the anti-sinking mode, the PLC control module controls the hydraulic actuation module to reduce the impact force when the tailplate contacts the ground and dynamically maintain a safe grounding pressure.

[0067] In this embodiment of the invention, by integrating a terrain scanning unit into a multi-sensor module and combining it with the intelligent analysis function of the PLC control module, the safe deployment of the vehicle tailgate and dynamic adjustment of ground pressure under complex terrain are achieved. The terrain scanning unit refers to a device based on lidar or ultrasonic sensors used to collect real-time terrain data below the tailgate. Its output data includes ground height distribution, slope angle, and surface hardness indicators, specifically obtained through laser point cloud or ultrasonic echo time difference calculations. Ground bearing capacity refers to the maximum pressure that a unit area of ​​the ground surface can withstand, measured in kilopascals (kPa). It is estimated by combining the surface hardness indicators of the terrain scanning unit with a pre-set soil mechanics model. The model is constructed based on the mapping relationship between surface echo intensity and soil density. The specific steps are as follows: First, the terrain scanning unit scans the area below the tailgate at a fixed frequency (e.g., 10Hz) to generate point cloud data or echo time difference data; then, the PLC control module calls the soil mechanics model to convert the height difference or echo intensity in the point cloud data into soil density parameters (e.g., the density of soft ground is 0.8 g / cm³). 3 Then, based on the density, look up the table to obtain the bearing capacity (e.g., density 0.8 g / cm³). 3 (Corresponding to a bearing capacity of 50 kPa). When the bearing capacity is below the safety threshold (e.g., 100 kPa), the PLC control module determines it to be soft ground and triggers the anti-sinking mode. The anti-sinking mode refers to reducing the impact force when the tailplate contacts the ground (defined as the force at the moment the tailplate touches the ground, in Newtons, N) by dynamically adjusting the output pressure and speed of the hydraulic actuator module, and maintaining a safe grounding pressure (defined as the pressure per unit area after the tailplate is stably grounded, in kPa). In specific implementation, the PLC control module receives real-time data from the terrain scanning unit, calculates the tailplate deployment speed (in m / s, calculated through the displacement change rate fed back by the displacement sensor) and the grounding impact force (instantaneous pressure measured by the pressure sensor), and adjusts the opening of the control valve group of the hydraulic actuator module according to the bearing capacity data (e.g., reducing the valve opening from 50% to 30%), thereby controlling the impact force within a safe range (e.g., below 500 N). At the same time, the output pressure of the hydraulic cylinder is dynamically adjusted through a closed-loop control algorithm to keep the grounding pressure below the safety threshold (e.g., 50 kPa). The closed-loop control algorithm is based on proportional-integral-derivative (PID) control. Specifically, it first initializes the proportional coefficient Kp (e.g., 0.5), integral coefficient Ki (e.g., 0.1), and derivative coefficient Kd (e.g., 0.05). Then, based on the error between the real-time ground pressure and the target pressure (50 kPa), the control output is calculated, and the thrust of the hydraulic cylinder (in N) is adjusted. All parameters are acquired through real-time sensor measurement or calculation using a preset model to ensure control accuracy and response speed.

[0068] In practical applications, taking the unloading of a logistics truck at a construction site as an example, the tailgate hydraulic control system integrates a terrain scanning unit (using LiDAR, such as Velodyne VLP-16, scanning frequency 10Hz, point cloud resolution 0.02m) to assess the ground conditions before the tailgate is deployed. When the system starts, the terrain scanning unit scans a 2m×2m area below the tailgate at a frequency of 10Hz, generating point cloud data. The PLC control module (such as Siemens S7-1200) receives the point cloud data and extracts the ground height difference (e.g., maximum height difference 0.1m) and echo intensity (e.g., intensity value 0.7, lower than the hard ground threshold of 1.0). It then calls a preset soil mechanics model (based on experimental data tables of soil density and bearing capacity, stored in the PLC memory) to calculate the ground bearing capacity as 60kPa, which is lower than the safety threshold of 100kPa, thus determining it to be soft ground and triggering the anti-sinking mode. In anti-sinking mode, the PLC control module receives feedback data from pressure sensors (such as Honeywell PX2, range 0-1000kPa) and displacement sensors (such as MTL linear displacement sensors, range 0-500mm) in real time through a closed-loop PID control algorithm (Kp=0.5, Ki=0.1, Kd=0.05). It calculates the tailplate deployment speed as 0.1m / s and the initial grounding impact force as 800N, exceeding the safety threshold of 500N. Subsequently, the PLC control module adjusts the valve opening of the hydraulic actuator module (using Rexroth hydraulic pump A10VSO and proportional control valve 4WREE) from 50% to 30%, reducing the hydraulic cylinder thrust to 400N, thus reducing the impact force to 450N. At the same time, it dynamically monitors the grounding pressure as 45kPa, which is lower than the safety threshold of 50kPa, ensuring stable grounding of the tailplate. The entire process is completed through real-time calculations by the PLC control module and feedback from sensor data. The system response time is less than 100ms, which successfully avoids tilting or equipment damage caused by the tail plate sinking due to soft ground, and significantly improves the safety and stability of operations in complex terrain.

[0069] This invention, through the collaborative operation of a terrain scanning unit and a PLC control module, enables the safe deployment of the vehicle tailgate and dynamic adjustment of ground pressure in complex terrain, effectively avoiding the risk of tailgate sinking or equipment damage caused by soft ground. The terrain scanning unit accurately collects ground data using laser point cloud or ultrasonic echo technology, and accurately estimates bearing capacity using a soil mechanics model, providing a reliable basis for triggering the anti-sinking mode. The anti-sinking mode dynamically adjusts the hydraulic output through a closed-loop PID control algorithm, controlling the ground impact force and pressure within a safe range, significantly improving the system's environmental adaptability and operational safety. In practical applications, this design can maintain stable tailgate operation in complex scenarios such as construction sites and muddy roads, reducing equipment maintenance costs and the risk of operational interruptions. Simultaneously, precise pressure control extends the service life of the hydraulic actuator module, providing crucial assurance for the reliability and intelligence level of the intelligent vehicle tailgate system.

[0070] Example 8:

[0071] In some embodiments, the system further includes a precision positioning unit; the Internet of Things communication module is configured to: communicate and network with the intelligent vehicle tailgate hydraulic control system of a neighboring vehicle, and based on the data from the precision positioning unit, enable the tailgate of this vehicle and the tailgate of the neighboring vehicle to coordinately adjust their height and angle to form a continuous collaborative loading and unloading operation surface.

[0072] In this embodiment of the invention, the precise positioning unit employs an RTK-GPS module (positioning accuracy ±10mm, based on differential positioning technology, calculated through the signal difference between base stations and mobile stations) to provide three-dimensional position data (longitude, latitude, and altitude, units: degrees and meters) of the tailgate. The IoT communication module networks with the tailgate systems of neighboring vehicles via a 5G network (transmission rate ≥100Mbps, supporting V2V protocol) to exchange position data and control commands (data packet size ≤1KB, transmission delay ≤50ms, measured using network testing tools). The PLC control module adjusts the hydraulic actuator module based on the positional difference between the tailgates of the current vehicle and the neighboring vehicle (height difference ≤50mm, angle difference ≤1°, calculated using RTK-GPS data) through a collaborative control algorithm (based on a distributed consensus algorithm, nodes synchronize states via the Gossip protocol, iteration count ≤10 times, convergence time ≤100ms) to align the height and angle of the current vehicle's tailgate with those of the neighboring vehicle (height error ≤10mm, angle error ≤0.5°). The algorithm is implemented in C language within the PLC, and parameters are acquired in real time via RTK-GPS and 5G network to ensure the continuity of multi-vehicle collaborative loading and unloading.

[0073] Here is a specific implementation example:

[0074] In a collaborative loading and unloading scenario involving two logistics trucks, the precise positioning unit (RTK-GPS module: Trimble BX992) detects the height of the tailgate of its own truck as 1500mm, while the adjacent truck's tailgate height is 1520mm, a height difference of 20mm and an angle difference of 0.8°. The IoT communication module (Quectel RM500Q, 5G connection) exchanges data via V2V protocol with a delay of 40ms. The PLC (Siemens S7-1200) runs a collaborative control algorithm, iterating 8 times to calculate the adjustment amount, and controls the hydraulic actuator to raise the tailgate of its own truck to 1520mm ± 10mm, correcting the angle to 0° ± 0.5°, taking 4 seconds. The tailgates of the two trucks form a continuous loading and unloading surface, ensuring smooth cargo transfer and improving efficiency by 30%. This collaborative mechanism significantly improves the accuracy and efficiency of multi-vehicle collaborative operations.

[0075] Example 9:

[0076] In some embodiments, the multi-sensor module further includes an inertial measurement unit for acquiring high-frequency inertial measurement data of the vehicle;

[0077] The PLC control module is further configured as follows:

[0078] After the tailplate operation command is issued, high-frequency inertial measurement data from the inertial measurement unit within the time window prior to the issuance of the operation command is acquired.

[0079] Based on the inertial measurement data, the dominant vibration modes of the cargo inside the vehicle are estimated;

[0080] A control signal is generated, the spectral characteristics of which are configured to actively suppress the dominant vibration mode;

[0081] The hydraulic actuator is controlled to perform the main lifting action while applying high-frequency micro-motion to the tail plate platform according to the control signal, so as to counteract the residual vibration inside the cargo.

[0082] In this embodiment of the invention, the automotive tailgate hydraulic control system integrates a high-frequency inertial measurement unit (IMU) from a multi-sensor module, combined with signal processing and control algorithms from a PLC control module, to actively suppress cargo vibration during unloading, thereby improving the transportation safety of high-value, fragile goods. The inertial measurement unit refers to a sensor module containing a three-axis accelerometer and a three-axis gyroscope, used to collect real-time three-dimensional vibration data of the vehicle in motion or at rest. Output parameters include acceleration (unit: m / s²). 2The measurement range is ±16g, accuracy ±0.01g (measured by a MEMS accelerometer) and the angular velocity (unit: ° / s, range ±2000° / s, accuracy ±0.1° / s, measured by a MEMS gyroscope) are sampled at a frequency of 1000Hz to capture high-frequency vibration signals. After the tailboard operation command (such as lifting or leveling command) is issued, the PLC control module acquires the vibration data of the IMU within a fixed time window (such as the first 10 seconds, the length of the time window is determined experimentally to cover the typical vibration period) before the operation. The data format is time series acceleration and angular velocity values. Based on this data, the PLC control module estimates the vibration characteristics of the cargo-vehicle system using a time-frequency analysis algorithm. This algorithm employs a Fast Fourier Transform (FFT), with the following steps: First, the acceleration data within the time window is preprocessed (DC component removed, mean filtered, with a filtering window of 10ms). Then, an FFT transformation is performed (1024 sampling points, frequency resolution of 0.98Hz, calculated as sampling frequency divided by the number of points). This extracts the spectral characteristics of the vibration signal and identifies the dominant vibration mode parameters of the cargo-vehicle system, including the natural frequency (unit: Hz, range 0-100Hz, representing the system's main vibration frequency) and the damping ratio (dimensionless, range 0-1, representing the vibration's attenuation characteristics). The natural frequency is determined by the peak value of the frequency with the largest amplitude in the spectrum, and the damping ratio is calculated using the half-power bandwidth method (i.e., the bandwidth at which the amplitude drops to 1 / √2 at the frequency peak divided by the natural frequency). Based on these parameters, the PLC control module generates an inverse control signal with spectral characteristics opposite to the dominant vibration mode (e.g., if the natural frequency is 10Hz, the main frequency of the control signal is 10Hz, with a phase shift of 180°). The signal is sinusoidal with an amplitude range of 0-0.01m (tested to ensure that micro-motion does not affect the main lifting action). The control signal is output to the servo valve of the hydraulic actuator module (response frequency ≥100Hz, model such as MoogD633) via a digital signal processor (DSP) in pulse width modulation (PWM) form (frequency 10kHz, duty cycle 0-100%). While performing regular lifting actions (speed 0-0.5m / s, angle adjustment rate 0-5° / s), the hydraulic actuator module controls the hydraulic cylinder through the servo valve to apply high-frequency micro-motion (amplitude 0-10mm, frequency 0-100Hz) to counteract residual vibration energy inside the cargo. Micro-motion is achieved by adjusting the hydraulic oil flow rate (range 0-5L / min, accuracy ±0.1L / min) via a servo valve. The flow rate is proportional to the PWM duty cycle of the control signal (e.g., 50% duty cycle corresponds to 2.5L / min). All parameters are directly measured by the IMU or calculated by the PLC's internal algorithm. The algorithm is implemented in C language within the PLC's real-time operating system (RTOS) with an execution cycle of 1ms, ensuring the real-time performance and accuracy of vibration suppression.The entire process actively suppresses vibration through a feedforward control strategy (based on vibration mode prediction rather than real-time feedback), preventing cargo from becoming unstable due to vibration at the moment of unloading. It is particularly suitable for transportation scenarios of fragile goods such as precision instruments and glass products.

[0083] Here is a specific implementation example:

[0084] In the tailgate system of a logistics truck transporting precision medical equipment, a high-frequency inertial measurement unit (IMU) (model: Bosch BMI088, range ±16g, ±2000° / s, sampling frequency 1000Hz) is integrated and installed on the truck floor near the tailgate to collect vehicle vibration data in real time. Before the tailgate operation command is issued, the PLC control module (model: Siemens S7-1200) acquires the IMU's three-dimensional acceleration data (e.g., maximum X-axis acceleration 2.5m / s²) within a 10-second time window before the operation. 2 Y-axis 1.8m / s 2 Z-axis 3.2m / s 2The PLC control module uses an FFT algorithm (based on the open-source FFTW library, 1024 sampling points, 0.98Hz frequency resolution) to preprocess the Z-axis acceleration data (10ms mean filtering to remove noise), performs FFT transformation, extracts the spectrum, and identifies the natural frequency of the cargo-vehicle system as 12Hz (at the peak of the spectrum), with a damping ratio of 0.15 (calculated using the half-power bandwidth method, with a bandwidth of 1.8Hz). Based on this, the PLC generates an inverse control signal (main frequency 12Hz, phase offset 180°, amplitude 0.008m), which is output as a 10kHz PWM signal (60% duty cycle) to the servo valve (MoogD633, response frequency 150Hz) of the hydraulic actuator module via the DSP module (model: TIC2000). The servo valve adjusts the hydraulic oil flow to 3L / min based on the signal, driving the hydraulic cylinder (piston diameter 50mm, stroke 2000mm) to perform a normal lifting action (speed 0.3m / s, from 0mm to 1500mm, time 5 seconds) while simultaneously applying a micro-motion with a frequency of 12Hz and an amplitude of 8mm. This micro-motion is achieved through the high-frequency reciprocating motion of the hydraulic cylinder, with an action cycle of 83.3ms (1 / 12Hz), ensuring synchronization and out-of-phase with the vibration mode of the cargo. During actual unloading, the system detected that the vibration amplitude of the medical equipment (weighing 500kg) decreased from the initial 0.015m to 0.002m, a reduction of 85% in vibration energy, effectively preventing damage to the equipment due to unloading impact. The entire process is scheduled in real-time by the PLC's RTOS, with an algorithm execution delay of less than 1ms, a servo valve response time of 6ms, and an overall system response time of less than 10ms. This active vibration suppression technology significantly improves the safety of unloading high-value and fragile goods, reduces the risk of damage during transportation, and at the same time reduces mechanical wear on the tailgate system through precise vibration control, thereby extending the service life of the equipment.

[0085] This invention integrates a high-frequency inertial measurement unit (IMU) into a multi-sensor module, combined with time-frequency analysis and feedforward control algorithms from a PLC control module, to actively suppress cargo vibration during unloading at a vehicle's tailgate. The IMU captures vehicle vibration data at a high sampling frequency and accurately extracts the vibration mode parameters of the cargo-vehicle system using a fast Fourier transform, providing a reliable basis for generating an inverse control signal. The hydraulic actuation module applies micro-amplitude movements through a high-frequency servo valve, effectively offsetting residual vibration energy within the cargo and significantly reducing the risk of instability during unloading. This technology is particularly suitable for transporting high-value, fragile goods such as precision instruments, medical equipment, and glass products. Precise vibration control improves the safety and reliability of unloading, while reducing mechanical wear caused by vibration impact and extending the lifespan of the tailgate system. Furthermore, the system's real-time performance and high-precision control capabilities ensure stable operation under complex conditions, providing efficient and reliable technical support for modern intelligent logistics systems and significantly reducing cargo damage rates and maintenance costs during transportation.

[0086] Example 10:

[0087] Figure 2 A flowchart of an IoT-based intelligent vehicle tailgate hydraulic control method is provided as an embodiment of this application, such as... Figure 2 As shown, the method includes:

[0088] S1. The load status and environmental parameters of the vehicle tailgate are collected in real time through a multi-sensor module, which includes a pressure sensor, a displacement sensor and a tilt sensor.

[0089] S2. The load status and environmental parameters are received through the PLC control module, and control commands are generated according to the intelligent control algorithm. The intelligent control algorithm includes a one-key automatic leveling algorithm and an anti-collision protection algorithm, which are used to dynamically adjust the hydraulic output according to the feedback signals of the multi-sensor module.

[0090] S3. Remote data transmission and monitoring via IoT communication module;

[0091] S4. Receive the control command through the hydraulic actuator module and drive the tailgate to perform lifting and angle adjustment actions.

[0092] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A smart automotive tailgate hydraulic control system based on the Internet of Things, characterized in that, include: The system comprises a PLC control module, a multi-sensor module, an IoT communication module, and a hydraulic actuator module. The multi-sensor module includes pressure sensors, displacement sensors, and tilt sensors, used to collect real-time data on the load status and environmental parameters of the vehicle's tailgate. The PLC control module is signal-connected to the multi-sensor module and the IoT communication module, used to receive the load status and environmental parameters of the vehicle's tailgate and generate control commands based on an intelligent control algorithm. The hydraulic actuator module is signal-connected to the PLC control module, used to receive the control commands to drive the tailgate to perform lifting and angle adjustment actions. The intelligent control algorithm includes a one-click automatic leveling algorithm and an anti-collision protection algorithm, which are used to dynamically adjust the hydraulic output based on the feedback signals from the multi-sensor module. The anti-collision protection algorithm is configured to continuously collect load pressure data and calculate the pressure change rate through the pressure sensor. When the pressure change rate is detected to be ≥5MPa / s, it is determined to be a sudden load change, and the hydraulic actuator is triggered to reduce the hydraulic oil flow to reduce pressure, so as to avoid instantaneous overload collision during load handling. The multi-sensor module also includes a terrain scanning unit; The PLC control module is further configured to receive terrain data from the terrain scanning unit and assess ground bearing capacity before the tail plate is deployed. If soft ground is detected, the anti-sinking mode is automatically triggered. In this anti-sinking mode, the PLC control module controls the hydraulic actuation module to reduce the impact force when the tail plate contacts the ground and dynamically maintain a safe grounding pressure. The multi-sensor module also includes an inertial measurement unit for collecting high-frequency inertial measurement data of the vehicle; The PLC control module is further configured as follows: After the tailplate operation command is issued, high-frequency inertial measurement data from the inertial measurement unit within the time window prior to the issuance of the operation command is acquired. Based on the inertial measurement data, the dominant vibration modes of the cargo inside the vehicle are estimated; A control signal is generated, the spectral characteristics of which are configured to actively suppress the dominant vibration mode; The hydraulic actuator is controlled to perform the main lifting action while applying high-frequency micro-motion to the tail plate platform according to the control signal, so as to counteract the residual vibration inside the cargo.

2. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, The system also includes a safety protection module that is connected to the PLC control module via signals. The safety protection module includes an overload alarm unit, an emergency braking unit, and a fault self-diagnosis unit.

3. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, The system also includes an emergency manual operation device, which is mechanically or hydraulically connected to the hydraulic actuator module and is used to manually control the tailgate in the event of a power outage or malfunction.

4. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, The hydraulic actuator module includes a hydraulic pump, a hydraulic cylinder, and a control valve group controlled by the PLC control module.

5. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, The PLC control module is configured to receive feedback signals from the displacement sensor and tilt sensor, and adjust the control commands output to the hydraulic actuator in real time through a closed-loop control algorithm to achieve precise positioning of the tailplate movement.

6. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, The IoT communication module is used to upload system status data, fault codes and sensor data to the remote monitoring platform, and to receive instructions from the remote monitoring platform.

7. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, The system also includes a precise positioning unit; the Internet of Things communication module is configured to communicate and network with the intelligent vehicle tailgate hydraulic control system of a neighboring vehicle, and based on the data from the precise positioning unit, enable the tailgate of this vehicle and the tailgate of the neighboring vehicle to coordinately adjust their height and angle to form a continuous collaborative loading and unloading operation surface.

8. A hydraulic control method for a smart car tailgate based on the Internet of Things, characterized in that, include: The load status and environmental parameters of the vehicle's tailgate are collected in real time through a multi-sensor module, which includes a pressure sensor, a displacement sensor, and a tilt sensor. The load status and environmental parameters are received by the PLC control module, and control commands are generated according to the intelligent control algorithm. The intelligent control algorithm includes a one-key automatic leveling algorithm and an anti-collision protection algorithm, which are used to dynamically adjust the hydraulic output according to the feedback signals of the multi-sensor module. When the anti-collision protection algorithm is running, the load pressure data is continuously collected by the pressure sensor and the pressure change rate is calculated. When the pressure change rate is detected to be ≥5MPa / s, it is determined to be a sudden load change, and the hydraulic actuator is triggered to reduce the hydraulic oil flow to reduce pressure, so as to avoid instantaneous overload collision during load handling. Remote data transmission and monitoring are achieved through an IoT communication module; The control command is received by the hydraulic actuator module, which then drives the tailgate to perform lifting and angle adjustment actions. The multi-sensor module also includes a terrain scanning unit; The PLC control module is further configured to receive terrain data from the terrain scanning unit and assess ground bearing capacity before the tail plate is deployed. If soft ground is detected, the anti-sinking mode is automatically triggered. In this anti-sinking mode, the PLC control module controls the hydraulic actuation module to reduce the impact force when the tail plate contacts the ground and dynamically maintain a safe grounding pressure. The multi-sensor module also includes an inertial measurement unit for collecting high-frequency inertial measurement data of the vehicle; The PLC control module is further configured as follows: After the tailplate operation command is issued, high-frequency inertial measurement data from the inertial measurement unit within the time window prior to the issuance of the operation command is acquired. Based on the inertial measurement data, the dominant vibration modes of the cargo inside the vehicle are estimated; A control signal is generated, the spectral characteristics of which are configured to actively suppress the dominant vibration mode; The hydraulic actuator is controlled to perform the main lifting action while applying high-frequency micro-motion to the tail plate platform according to the control signal, so as to counteract the residual vibration inside the cargo.

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