Intelligent automobile tailboard hydraulic control system and method based on Internet of Things

Abstract

The invention provides an intelligent automobile tailboard hydraulic control system and method based on the Internet of Things, and relates to the technical field of the Internet of Things. In the system, a multi-sensor module comprises a pressure sensor, a displacement sensor and a tilt angle sensor and is used for collecting the load state and environment parameters of an automobile tailboard in real time; the PLC control module is in signal connection with the multi-sensor module and the Internet of Things communication module, and is used for receiving the load state and environmental parameters of the automobile tailboard and generating a control instruction according to an intelligent control algorithm; the hydraulic execution module is in signal connection with the PLC control module and is used for receiving a control instruction to drive the tail plate to execute lifting and angle adjusting actions; the intelligent control algorithm comprises a one-key automatic leveling algorithm and an anti-collision protection algorithm and is used for dynamically adjusting hydraulic output according to feedback signals of the multi-sensor module. Remote monitoring and management are achieved through the Internet of Things technology, and efficient and reliable technical support is provided for a modern intelligent logistics system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, and particularly relates to an intelligent automobile tailboard hydraulic control system and method based on Internet of Things. BACKGROUND

[0002] With the rapid development of the logistics industry, the intelligent and automatic level of the automobile tailboard, as an important equipment for loading and unloading goods, directly affects the efficiency and safety of logistics.

[0003] The traditional automobile tailboard hydraulic control system mainly relies on manual operation or simple mechanical control, and has problems such as slow response speed, low precision, lack of environmental adaptability, etc. Especially in complex working conditions, such as uneven ground or heavy load scenes, improper manual adjustment can easily cause the tailboard to tilt, uneven load, and even equipment damage. In addition, the traditional system lacks real-time monitoring and data interaction capabilities, and cannot realize remote management or dynamic optimization, which limits its application in modern intelligent logistics systems. In recent years, the rise of Internet of Things technology has provided new opportunities for the intelligentization of equipment. Through multi-sensor fusion and remote communication, real-time monitoring and precise control of equipment status can be realized. However, in the existing technology, the intelligentization scheme for the automobile tailboard hydraulic system is still relatively single, lacking integrated sensor data processing and intelligent algorithm optimization, especially the adaptive control research for dynamic load changes and complex environments is insufficient.

[0004] Therefore, developing an intelligent automobile tailboard hydraulic control system based on Internet of Things, integrating multi-sensor modules, PLC control modules, Internet of Things communication modules, and hydraulic execution modules, and realizing one-key automatic leveling and anti-collision protection through intelligent algorithms, has become an important direction to solve the above problems. The system aims to improve the automation level, safety and adaptability of tailboard operation through real-time data acquisition and intelligent control algorithms, to meet the needs of modern logistics for efficient, safe and intelligent equipment. SUMMARY

[0005] The present application aims to provide an intelligent automobile tailboard hydraulic control system and method based on Internet of Things to solve the problems pointed out in the background.

[0006] In a first aspect, the embodiments of the present application provide a kind of intelligent automobile tailgate hydraulic control system based on Internet of Things, including PLC control module, multi-sensor module, Internet of Things communication module and hydraulic execution module;The multi-sensor module includes pressure sensor, displacement sensor and inclination sensor, for real-time acquisition of the load state and environmental parameters of automobile tailgate;The PLC control module is signal connected with the multi-sensor module and Internet of Things communication module, for receiving the load state and environmental parameters of automobile tailgate and generating control instruction according to intelligent control algorithm;The hydraulic execution module is signal connected with the PLC control module, for receiving the control instruction to drive tailgate to execute lifting and angle adjustment action;

[0007] The intelligent control algorithm includes one-key automatic leveling algorithm and anti-collision protection algorithm, for dynamically adjusting hydraulic output according to the feedback signal of the multi-sensor module.

[0008] Optionally, the system further includes a safety protection module signal connected with the PLC control module, and 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 operating device, which is mechanically or hydraulically connected with the hydraulic execution module, for manually controlling the tailgate when the system is powered off or fails.

[0010] Optionally, the hydraulic execution 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 the feedback signals of the displacement sensor and the inclination sensor, and to adjust the control instruction output to the hydraulic execution module in real time through a closed-loop control algorithm to achieve precise positioning of the tailgate movement.

[0012] Optionally, the Internet of Things communication module is used to upload system state data, fault codes and sensor data to a remote monitoring platform, and 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 evaluate ground bearing capacity before the tailgate is deployed, and if soft ground is identified, an anti-sinking mode is automatically triggered, wherein in the anti-sinking mode, the PLC control module controls the hydraulic execution module to reduce the impact force when the tailgate contacts the ground and dynamically maintain a safe ground pressure.

[0014] Optionally, the system further comprises a precise positioning unit; the Internet of Things communication module is configured to: communicate networking with the intelligent automobile tailboard hydraulic control system of the adjacent vehicle, and based on the data of the precise positioning unit, make the tailboard of the vehicle and the tailboard of the adjacent vehicle cooperatively adjust the height and angle to form a continuous cooperative loading and unloading working surface.

[0015] Optionally, the multi-sensor module further comprises an inertial measurement unit for collecting high-frequency inertial measurement data of the vehicle.

[0016] The PLC control module is further configured to:

[0017] After the tailboard operation instruction is issued, high-frequency inertial measurement data in a time window before the operation instruction is issued is obtained from the inertial measurement unit;

[0018] Based on the inertial measurement data, the dominant vibration mode of the goods in the vehicle is estimated.

[0019] A control signal is generated, and the frequency spectrum characteristics of the control signal are configured to actively suppress the dominant vibration mode.

[0020] The hydraulic execution module is controlled to apply high-frequency micro-movement to the tailboard platform according to the control signal while performing the main lifting action, so as to offset the residual vibration inside the goods.

[0021] In a second aspect, the embodiments of the present application provide an intelligent automobile tailboard hydraulic control method based on the Internet of Things, comprising:

[0022] The load state and environmental parameters of the automobile tailboard are collected in real time by a multi-sensor module, and the multi-sensor module comprises a pressure sensor, a displacement sensor and an inclination sensor.

[0023] The load state and environmental parameters are received by a PLC control module, and control instructions are generated according to an intelligent control algorithm; the intelligent control algorithm comprises a one-key automatic leveling algorithm and a collision prevention algorithm, which are used to dynamically adjust the hydraulic output according to the feedback signal of the multi-sensor module.

[0024] Remote data transmission and monitoring are performed by an Internet of Things communication module.

[0025] The control instructions are received by a hydraulic execution module, and the tailboard performs lifting and angle adjustment actions.

[0026] The present application has the following beneficial effects:

[0027] The application provides an intelligent automobile tailboard hydraulic control system based on Internet of Things, which realizes the intelligentization and automation of tailboard operation by integrating a multi-sensor module, a PLC control module, an Internet of Things communication module and a hydraulic execution module, combining a one-key automatic leveling algorithm and a collision protection algorithm.

[0028] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art upon examination of the following or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by the structure particularly pointed out in the written description and claims hereof.

[0029] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate the present application, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation on the present application. In the drawings:

[0031] Figure 1 It is a schematic diagram of an intelligent automobile tailboard hydraulic control system based on Internet of Things in an embodiment of the present application.

[0032] Figure 2 It is a flow chart of an intelligent automobile tailboard hydraulic control method based on Internet of Things in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The preferred embodiments of the present application are described below in combination with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not constitute a limitation on the present application.

[0034] Example 1:

[0035] The research and development idea of the present application is to improve the intelligence and adaptability of the hydraulic control system of the automobile tailgate as the core. In view of the shortcomings of the traditional system under complex working conditions, an integrated solution based on the Internet of Things is proposed. First, by designing a multi-sensor module including pressure sensors, displacement sensors and inclination sensors, real-time acquisition of load state and environmental parameters is realized, providing a data basis for precise control. Second, a PLC control module is developed, combined with intelligent control algorithms such as one-key automatic leveling algorithm and anti-collision protection algorithm, to realize real-time analysis and processing of sensor data and generate dynamic control instructions to adapt to the tailgate adjustment requirements under different working conditions. At the same time, the Internet of Things communication module is introduced to realize data interaction between the system and the remote management platform, supporting real-time monitoring and remote optimization. Finally, the hydraulic execution module converts the control instructions into precise lifting and angle adjustment actions to ensure efficient execution of the system. The entire research and development process focuses on the synergy of sensor fusion, algorithm optimization and system integration, aiming to build an efficient, safe and adaptable intelligent control system.

[0036] Figure 1 A schematic diagram of an intelligent automobile tailgate hydraulic control system based on the Internet of Things is provided for the embodiments of the present application, as shown in Figure 1 The system includes a PLC control module 1, a multi-sensor module 2, an Internet of Things communication module 3 and a hydraulic execution module 4. The multi-sensor module 2 includes pressure sensors, displacement sensors and inclination sensors for real-time acquisition of load state and environmental parameters of the automobile tailgate. The PLC control module 1 is signal connected with the multi-sensor module 2 and the Internet of Things communication module 3 for receiving load state and environmental parameters of the automobile tailgate and generating control instructions according to intelligent control algorithms. The hydraulic execution module 4 is signal connected with the PLC control module 1 for receiving the control instructions to drive the tailgate to perform lifting and angle adjustment actions.

[0037] The intelligent control algorithm includes one-key automatic leveling algorithm and anti-collision protection algorithm for dynamically adjusting hydraulic output according to the feedback signals of the multi-sensor module.

[0038] In the embodiment of the application, the intelligent automobile tailgate hydraulic control system based on Internet of Things realizes intelligent control of tailgate lifting and angle adjustment by integrating PLC control module, multi-sensor module, Internet of Things communication module and hydraulic execution module. The PLC control module as the core controller receives feedback data of the multi-sensor module through a digital signal interface, including tailgate load pressure measured by a pressure sensor (unit: MPa, acquisition method: piezoelectric element built-in pressure sensor measures hydraulic oil pressure and converts it into an electrical signal, range 0-40 MPa, accuracy ±0.5%), tailgate lifting height measured by a displacement sensor (unit: mm, hydraulic cylinder piston displacement is detected by a magnetostrictive displacement sensor, range 0-2000 mm, accuracy ±0.1 mm), and tailgate inclination angle measured by an inclination sensor (unit: degrees, angle change is detected by a MEMS inclination sensor, range ±30°, accuracy ±0.1°). The multi-sensor module collects these parameters in real time and transmits them to the PLC control module through the CAN bus. The PLC control module runs intelligent control algorithms, including one-key automatic leveling algorithm and anti-collision protection algorithm. The one-key automatic leveling algorithm is based on inclination sensor data and adjusts the output pressure and flow of the hydraulic execution module through PID control logic (proportional, integral, and derivative parameters are Kp=0.8, Ki=0.2, and Kd=0.05, respectively, based on experimental calibration) to keep the tailgate level (error ≤0.5°). The anti-collision protection algorithm detects load mutation through the pressure sensor (pressure change rate ≥5 MPa / s, based on sensor sampling frequency 100 Hz) to trigger the hydraulic execution module to reduce pressure to avoid overload. The Internet of Things communication module uses a 4G / 5G module (supports MQTT protocol, data transmission rate ≥10 Mbps) to upload sensor data and control status to a remote monitoring platform and receive remote instructions. The hydraulic execution module adjusts hydraulic oil flow through a control valve group (range 0-50 L / min, accuracy ±1 L / min) to drive the hydraulic cylinder to complete tailgate lifting (speed 0-0.5 m / s) and angle adjustment (angle change rate 0-5° / s). All parameters are measured directly by sensor hardware or calculated by PLC internal algorithms to ensure system real-time performance and accuracy.

[0039] A specific implementation example is provided as follows:

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

[0041] The present application provides an intelligent automobile tailgate hydraulic control system based on the Internet of Things, which realizes the intelligentization and automation of tailgate operation by integrating multiple sensor modules, PLC control modules, Internet of Things communication modules and hydraulic execution modules, combined with one-key automatic leveling algorithm and anti-collision protection algorithm. The system can collect real-time load state and environmental parameters, dynamically adjust hydraulic output, ensure the stability and safety of the tailgate under complex working conditions, significantly improve the operation efficiency, reduce the demand for manual intervention and operation risk, and realize remote monitoring and management through Internet of Things technology, providing efficient and reliable technical support for modern intelligent logistics system.

[0042] Example 2:

[0043] In some embodiments, the system further comprises a safety protection module connected with the PLC control module, which comprises an overload alarm unit, an emergency braking unit and a fault self-diagnosis unit.

[0044] In the embodiments of the present application, the safety protection module is connected with the PLC control module, and integrates an overload alarm unit, an emergency braking unit and a fault self-diagnosis unit, so as to improve the system safety. The overload alarm unit monitors the tailboard load based on pressure sensor data (range 0-40 MPa, accuracy ±0.5%, and the hydraulic oil pressure is measured by a piezoelectric element), and sets an overload threshold value (for example, 30 MPa, which is determined by historical load data statistical analysis, and the calculation method is average load plus 2 times standard deviation). When the load exceeds the threshold value, an audible and visual alarm is triggered (the alarm outputs 80 dB sound and red LED flashes, and the response time is less than or equal to 100 ms). The emergency braking unit detects pressure mutation (change rate greater than or equal to 5 MPa / s, calculated based on a 100 Hz sampling frequency) or inclination angle anomaly (angle deviation greater than or equal to 10°, measured by an inclination sensor) through the PLC, and sends a shutdown instruction to the hydraulic execution module to control the valve group to close the hydraulic oil circuit (the closing time is less than or equal to 50 ms). The fault self-diagnosis unit collects the internal running state of the PLC (such as CPU occupancy, ranging from 0 to 100%, obtained by a PLC built-in monitoring program) and sensor signal integrity (signal loss rate less than or equal to 0.1%, calculated by CAN bus data packet verification), identifies system faults (such as sensor disconnection or hydraulic pump anomaly), and generates fault codes (for example, E001 represents a pressure sensor fault, defined by a PLC fault mapping table). These parameters are directly measured by sensors or calculated by PLC algorithms, so that the safety protection module can quickly respond to abnormalities and record fault information for subsequent maintenance.

[0045] A specific embodiment is provided as follows:

[0046] In a tailgate system of a logistics truck, the safety protection module is connected with the PLC control module (Siemens S7-1200) through CAN bus. When the overload alarm unit detects that the load pressure fed back by the pressure sensor (Honeywell PX3) is 32 MPa, which exceeds the preset threshold of 30 MPa (based on historical data statistics, the average load is 20 MPa, and the standard deviation is 5 MPa), the audible and visual alarm (Patlite LKEH, 80 dB buzzer and red LED) is triggered to issue an alarm, reminding the operator to reduce the load, and the alarm response time is 80 ms. When the emergency brake unit detects that the inclination angle of the tailgate fed back by the inclination sensor (Bosch BNO055) reaches 12° (exceeding the threshold of 10°) when loading heavy objects, the PLC immediately sends a stop command to the control valve group (Bosch Rexroth 4WRPEH) to close the hydraulic oil circuit, and the tailgate stops moving, and the closing time is 40 ms. When the fault self-diagnosis unit detects that the loss rate of the pressure sensor signal reaches 0.2% (exceeding the threshold of 0.1%) through the PLC monitoring program, a fault code E001 is generated and uploaded to the remote monitoring platform through the Internet of Things communication module, prompting the maintenance personnel to replace the sensor. The maintenance personnel locate the problem according to the fault code, and the system returns to normal after replacing the sensor. This safety protection module effectively prevents accidents caused by overload, tipping and equipment failure, and improves the safety of tailgate operation.

[0047] Example 3:

[0048] In some embodiments, the system further comprises an emergency manual operating device mechanically or hydraulically connected with the hydraulic execution module, for manually controlling the tailgate when the system is powered off or fails.

[0049] In the embodiment of the present application, the emergency manual operating device is connected to the hydraulic actuator module through mechanical or hydraulic connection, ensuring manual control of the tailgate lifting and angle adjustment in case of power failure or system failure. The device includes a manual pump (output pressure 0-25 MPa, torque converted to hydraulic oil pressure through a handle, torque range 10-50 N·m, calibrated by mechanical test) and a manual valve (controls the on-off of the oil circuit, opening time ≤200 ms, driven by a mechanical spring). In the case of power failure or failure, the operator applies torque (for example 30 N·m, measured by torque wrench) to the manual pump to generate hydraulic oil pressure, drive the hydraulic cylinder (piston diameter 50 mm, stroke 0-2000 mm) to realize tailgate lifting (speed 0-0.1 m / s). The manual valve adjusts the oil flow (0-10 L / min) by rotating the angle (0-90°, calibrated by a scale dial) to control the tailgate angle change (rate 0-2° / s). The device is also equipped with a pressure gauge (range 0-40 MPa, accuracy ±1%) and an angle indicator (range ±30°, accuracy ±0.5°), which display the real-time hydraulic oil pressure and tailgate angle respectively, and the parameters are directly read by mechanical instruments. These parameters ensure that the operator can accurately control the tailgate in the absence of electricity, meeting the emergency operation requirements.

[0050] A specific implementation example is provided as follows:

[0051] In the tailgate system of a transport vehicle, the emergency manual operating device is installed beside the hydraulic actuator module. The manual pump (model: Enerpac P-39, maximum output 25 MPa) generates hydraulic oil pressure through handle operation, for example, the operator applies a 40 N·m torque (measured by torque wrench) to generate a 15 MPa oil pressure, which drives the hydraulic cylinder (piston diameter 50 mm) to lift the tailgate to a height of 1000 mm, with a lifting speed of 0.08 m / s and a time consumption of 12 seconds. The manual valve (model: Yuken DSG-01) adjusts the oil flow to 5 L / min by rotating to 45° (scale dial confirmation), which adjusts the tailgate angle from 5° to 0°, with a time consumption of 5 seconds. The pressure gauge (model: WIKA 213.53, range 0-40 MPa) displays the current oil pressure as 15 MPa, and the angle indicator (mechanical, range ±30°) displays the tailgate angle as 0°±0.5°. In a power failure scenario, the operator completes the tailgate lifting and leveling through the manual operating device, successfully loads and unloads the cargo, avoiding downtime losses. This device provides a reliable emergency control means for the system, ensuring the continuity and safety of the operation.

[0052] Embodiment 4:

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

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

[0055] A specific implementation example is provided as follows:

[0056] In the tailgate system of a cold-chain logistics vehicle, the hydraulic execution module is configured 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. The pressure sensor and flow meter confirm the accuracy of the parameters respectively. The hydraulic cylinder (piston diameter 50mm, stroke 2000mm) receives oil pressure to drive the tailgate to rise from 0mm to 1500mm at a speed of 0.4m / s, taking 3.75 seconds. The control valve group receives the 4-20mA signal (corresponding to flow rate 0-50L / min) sent by the PLC (Siemens S7-1200) and adjusts the flow rate to 25L / min, making the tailgate angle adjust from 3° to 0° in 4 seconds. The parameters are monitored in real time by the pressure sensor (Honeywell PX3) and flow meter (Omega FLR1000) to ensure that the error is within ±1%. In a loading and unloading operation, the hydraulic execution module quickly completes the tailgate lifting and leveling according to the PLC instructions, improving the loading and unloading efficiency by 20%, and demonstrating the advantages of high precision and high reliability.

[0057] Embodiment 5:

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

[0059] In an embodiment of the application, the PLC control module receives feedback signals from a displacement sensor (range 0-2000 mm, accuracy ±0.1 mm, measuring piston displacement based on magnetostrictive principle) and an inclination sensor (range ±30°, accuracy ±0.1°, measuring angle based on MEMS technology) through a closed-loop control algorithm, adjusts the control command (voltage 0-10V, current 4-20mA) of the hydraulic actuator in real time, and realizes precise positioning of the tailgate. The closed-loop control algorithm uses PID control logic, with parameters including proportional coefficient Kp=0.8, integral coefficient Ki=0.2, and differential coefficient Kd=0.05 (calibrated by Ziegler-Nichols method: first set Ki=0, Kd=0, gradually increase Kp until the system oscillates, record the oscillation period, and calculate Ki and Kd). The algorithm calculates the control output based on displacement deviation (target height minus actual height, unit: mm) and angle deviation (target angle minus actual angle, unit: °), and adjusts the oil flow (0-50L / min, accuracy ±1L / min) of the control valve group. The algorithm is executed every 10ms, collects sensor data, calculates the deviation and updates the output, ensuring positioning accuracy (height error ≤1mm, angle error ≤0.5°). Parameters are directly measured by sensors, and the algorithm is implemented in C language inside the PLC, running on a real-time operating system (RTOS) to ensure low latency.

[0060] A specific implementation example is provided as follows:

[0061] In the tailgate system of an engineering transport vehicle, the PLC control module (Siemens S7-1200) runs a closed-loop control algorithm, receiving feedback from a displacement sensor (MTS Temposonics R series) of tailgate height 1500mm (target 1600mm, deviation 100mm) and an inclination sensor (Bosch BNO055) of angle 2° (target 0°, deviation 2°). The algorithm calculates the PID output every 10ms, with Kp=0.8, Ki=0.2, and Kd=0.05, generating a 4-20mA signal to control the valve group (Bosch Rexroth 4WRPEH), adjusting the flow to 30L / min, driving the hydraulic cylinder to raise the tailgate to 1600mm±1mm, taking 2.5 seconds, and simultaneously correcting the angle to 0°±0.5°, taking 3 seconds. Parameters are collected in real time by sensors, and the RTOS inside the PLC ensures that the algorithm execution delay is less than 5ms. In a heavy-duty operation, the tailgate needs to be precisely positioned to a height of 1600mm and an angle of 0°, and the closed-loop control algorithm responds quickly, with positioning errors controlled within 1mm and 0.5°, ensuring loading and unloading accuracy and safety.

[0062] Embodiment 6:

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

[0064] In some embodiments, the IoT communication module is configured to upload system status data, fault codes, and sensor data to a remote monitoring platform and receive instructions from the remote monitoring platform.

[0065] In some embodiments, the IoT communication module is configured to upload system status data, fault codes, and sensor data to a remote monitoring platform and receive instructions from the remote monitoring platform.

[0066] In some embodiments, the multi-sensor module further comprises a terrain scanning unit, and the PLC control module is further configured to receive terrain data from the terrain scanning unit and evaluate ground bearing capacity before the tailgate is deployed, and automatically trigger a sinking prevention mode if soft ground is identified, wherein in the sinking prevention mode, the PLC control module controls the hydraulic execution module to reduce the impact force when the tailgate contacts the ground and dynamically maintain a safe ground pressure.

[0067] In the embodiment of the present application, by integrating the terrain scanning unit in the multi-sensor module, combined with the intelligent analysis function of the PLC control module, the safe deployment and ground pressure dynamic adjustment of the truck tailgate under complex terrain are realized. The terrain scanning unit refers to a device based on laser radar or ultrasonic sensor for real-time collection of terrain data under the tailgate. Its output data includes ground height distribution, slope angle and surface hardness index, which is obtained by laser point cloud or ultrasonic echo time difference calculation. The ground bearing capacity refers to the maximum pressure that the unit area of the ground can bear, with the unit of kilopascal (kPa), which is estimated by the surface hardness index of the terrain scanning unit combined with the pre-set soil mechanics model. The model is constructed based on the mapping relationship between ground echo intensity and soil density, and the specific steps are as follows: first, the terrain scanning unit scans the area under the tailgate at a fixed frequency (such as 10 Hz) 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 in the point cloud data or the echo intensity into the soil density parameter (such as the density of soft ground is 0.8 g / cm 3 ), and then obtains the bearing capacity according to the density (such as the density of 0.8 g / cm 3 corresponds to the bearing capacity of 50 kPa). When the bearing capacity is lower than the safety threshold (such as 100 kPa), the PLC control module determines that it is soft ground and triggers the anti-sink mode. The anti-sink mode refers to dynamically adjusting the output pressure and speed of the hydraulic execution module to reduce the impact force (defined as the force at the moment of tailgate grounding, with the unit of Newton, N) when the tailgate contacts the ground, and maintain a safe grounding pressure (defined as the pressure per unit area after the tailgate stably grounds, with the unit of kPa). In the specific implementation, the PLC control module receives the real-time data of the terrain scanning unit, calculates the tailgate deployment speed (unit: m / s, calculated by the displacement change rate feedback by the displacement sensor) and the grounding impact force (measured by the instantaneous pressure of the pressure sensor), and adjusts the control valve group opening of the hydraulic execution module according to the bearing capacity data (such as reducing the valve opening from 50% to 30%), so as to control the impact force within a safe range (such as less than 500 N), and at the same time, dynamically adjust the output pressure of the hydraulic cylinder through the closed-loop control algorithm to keep the grounding pressure below the safety threshold (such as 50 kPa). The closed-loop control algorithm is based on proportional-integral-derivative (PID) control, which is specifically: first, initialize the proportional coefficient Kp (such as 0.5), the integral coefficient Ki (such as 0.1) and the differential coefficient Kd (such as 0.05); then, according to the error between the real-time grounding pressure and the target pressure (50 kPa), calculate the control output and adjust the thrust of the hydraulic cylinder (unit: N). All parameters are obtained by real-time measurement of sensors or pre-set model calculation to ensure control accuracy and response speed.

[0068] In practical applications, take a logistics truck unloading at a construction site as an example, the tailgate hydraulic control system integrates a terrain scanning unit (using a laser radar, model such as Velodyne VLP-16, scanning frequency 10 Hz, point cloud resolution 0.02 m), which is used to evaluate the ground conditions of the site before the tailgate is expanded. When the system starts, the terrain scanning unit scans the 2m x 2m area below the tailgate at a frequency of 10 Hz, generating point cloud data, and the PLC control module (model such as Siemens S7-1200) receives the point cloud data and extracts the ground height difference (e.g. maximum height difference 0.1 m) and echo intensity (e.g. intensity value 0.7, below the hard ground threshold 1.0), calls the pre-set soil mechanics model (based on the experimental data table of soil density and bearing capacity, stored in the PLC memory) to calculate the ground bearing capacity as 60 kPa, which is below the safety threshold of 100 kPa, and determines it as soft ground, triggering the anti-sinking mode. In the anti-sinking mode, the PLC control module receives the feedback data of the pressure sensor (model such as Honeywell PX2, range 0-1000 kPa) and displacement sensor (model such as MTL linear displacement sensor, range 0-500 mm) in real time through the closed-loop PID control algorithm (Kp=0.5, Ki=0.1, Kd=0.05), calculates the tailgate expansion speed as 0.1 m / s, the initial ground impact force as 800 N, which exceeds the safety threshold of 500 N; subsequently, the PLC control module adjusts the valve opening of the hydraulic execution module (using Rexroth hydraulic pump A10VSO and proportional control valve 4WREE) from 50% to 30%, reduces the hydraulic cylinder thrust to 400 N, and the impact force to 450 N, while dynamically monitoring the ground pressure as 45 kPa, which is below the safety threshold of 50 kPa, ensuring the stable grounding of the tailgate. The entire process is completed through real-time calculation of the PLC control module and sensor data feedback, the system response time is less than 100 ms, successfully avoiding the tilting or equipment damage of the tailgate due to sinking on soft ground, significantly improving the operation safety and stability on complex terrain.

[0069] The embodiment of the application realizes the safe unfolding and ground pressure dynamic adjustment of the automobile tailgate under complex terrain through the cooperative work of the terrain scanning unit and the PLC control module, effectively avoiding the risk of tailgate subsidence or equipment damage caused by soft ground. The terrain scanning unit accurately collects ground data through laser point cloud or ultrasonic echo technology, accurately estimates the bearing capacity in combination with the soil mechanics model, and provides a reliable basis for triggering the anti-submersion mode; the anti-submersion mode dynamically adjusts the hydraulic output through the closed-loop PID control algorithm, controls the ground impact force and pressure within a safe range, and significantly improves the environmental adaptability and operation safety of the system. In actual application, the design can keep the tailgate stable operation under complex scenes such as construction sites and muddy roads, reduce the equipment maintenance cost and operation interruption risk, and prolong the service life of the hydraulic execution module through precise pressure control, thereby providing an important guarantee for the reliability and intelligent level of the intelligent automobile tailgate system.

[0070] Embodiment 8:

[0071] In some embodiments, the system further comprises a precise positioning unit; the Internet of Things communication module is configured to: communicate networking with the intelligent automobile tailgate hydraulic control system of adjacent vehicles, and based on the data of the precise positioning unit, the tailgate of the vehicle and the tailgate of the adjacent vehicle are cooperatively adjusted in height and angle to form a continuous cooperative loading and unloading operation surface.

[0072] In the embodiment of the application, the precise positioning unit adopts an RTK-GPS module (positioning accuracy ±10 mm, based on differential positioning technology, calculated by the signal difference between the base station and the mobile station), which provides three-dimensional position data (longitude, latitude, height, unit: degree, meter) of the tailgate. The Internet of Things communication module is networked with the tailgate system of adjacent vehicles through a 5G network (transmission rate ≥100 Mbps, supporting V2V protocol) to exchange position data and control instructions (data packet size ≤1 KB, transmission delay ≤50 ms, measured by a network test tool). The PLC control module adjusts the hydraulic execution module according to the position difference (height difference ≤50 mm, angle difference ≤1°, calculated by RTK-GPS data) between the tailgate of the vehicle and the tailgate of the adjacent vehicle through a cooperative control algorithm (based on a distributed consistency algorithm, nodes are synchronized through a Gossip protocol, iteration number ≤10 times, convergence time ≤100 ms) to align the height and angle of the tailgate of the vehicle with those of the adjacent vehicle (height error ≤10 mm, angle error ≤0.5°). The algorithm is realized in C language inside the PLC, and parameters are obtained in real time through RTK-GPS and 5G network, thereby ensuring the continuity of multi-vehicle cooperative loading and unloading.

[0073] A specific implementation example is provided as follows:

[0074] In the collaborative loading and unloading scenario of two logistics trucks, the precise positioning unit (RTK-GPS module: Trimble BX992) detects that the height of the tailgate of the vehicle is 1500 mm, the height of the tailgate of the adjacent vehicle is 1520 mm, the height difference is 20 mm, and the angle difference is 0.8°. The Internet of Things communication module (Quectel RM500Q, 5G connection) exchanges data through the V2V protocol, with a delay of 40 ms. The PLC (Siemens S7-1200) runs the collaborative control algorithm, and after 8 iterations, the adjustment amount is calculated, the hydraulic execution module is controlled to raise the tailgate of the vehicle to 1520 mm ± 10 mm, and the angle is corrected to 0° ± 0.5°, which takes 4 seconds. The tailgates of the two vehicles form a continuous loading and unloading surface, the goods are smoothly transferred, and the efficiency is improved by 30%. This collaborative mechanism significantly improves the accuracy and efficiency of multi-vehicle collaborative operation.

[0075] Embodiment 9:

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

[0077] The PLC control module is further configured to:

[0078] After the tailgate operation instruction is issued, high-frequency inertial measurement data within a time window before the operation instruction is issued is obtained from the inertial measurement unit;

[0079] Based on the inertial measurement data, the dominant vibration mode of the goods in the vehicle is estimated;

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

[0081] The hydraulic execution module is controlled to apply high-frequency micro-movement to the tailgate platform according to the control signal while performing the main lifting action, so as to offset the residual vibration inside the goods.

[0082] In the embodiment of the application, the automobile tailgate hydraulic control system realizes active suppression of goods vibration during unloading by integrating the high-frequency inertial measurement unit (IMU, Inertial Measurement Unit) in the multi-sensor module and combining the signal processing and control algorithm of the PLC control module, thereby improving the transportation safety of high-value and easily damaged goods. The inertial measurement unit refers to a sensor module containing a three-axis accelerometer and a three-axis gyroscope, which is used to collect three-dimensional vibration data of the vehicle in real time in the driving or stationary state, and the output parameters include acceleration (unit: m / s 2Hz, range 0-100 Hz, representing the main vibration frequency of the system) and damping ratio (dimensionless, range 0-1, representing the attenuation characteristic of the vibration). The natural frequency is determined by the frequency peak with the largest amplitude in the spectrum, and the damping ratio is calculated by the half-power bandwidth method (i.e., the bandwidth at which the amplitude drops to 1 / √2 of the peak value divided by the natural frequency). Based on these parameters, the PLC control module generates a counter-phase control signal with spectral characteristics opposite to the dominant vibration mode (e.g., if the natural frequency is 10 Hz, the control signal has a main frequency of 10 Hz with a phase shift of 180°), and the signal form is a sinusoidal wave with an amplitude range of 0-0.01 m (calibrated by experiments to ensure that the micro-amplitude motion does not affect the main lifting action). The control signal is output to the servo valve (response frequency ≥ 100 Hz, model such as Moog D633) of the hydraulic execution module in the form of pulse width modulation (PWM) (frequency 10 kHz, duty cycle 0-100%) through a digital signal processor (DSP). The hydraulic execution module, while performing the regular lifting action (speed 0-0.5 m / s, angular adjustment rate 0-5° / s), applies high-frequency micro-amplitude motion (amplitude 0-10 mm, frequency 0-100 Hz) to the hydraulic cylinder through the servo valve to counteract the residual vibration energy inside the cargo. The realization of micro-amplitude motion is achieved by adjusting the hydraulic oil flow (range 0-5 L / min, accuracy ±0.1 L / min) through the servo valve, which is directly proportional to the PWM duty cycle of the control signal (e.g., 50% duty cycle corresponds to 2.5 L / min). All parameters are measured directly by the IMU or calculated by the PLC internal algorithm, which is implemented in C language in the real-time operating system (RTOS) of the PLC with an execution period of 1 ms, ensuring the real-time and accuracy of vibration suppression.The whole process achieves active suppression through a feedforward control strategy (based on vibration modal prediction rather than real-time feedback), avoiding instability of the goods at the moment of unloading due to vibration, and is particularly suitable for transportation scenarios of fragile goods such as precision instruments and glass products.

[0083] A specific implementation example is provided as follows:

[0084] In a logistics truck tailgate system transporting precision medical equipment, a high-frequency inertial measurement unit (model: Bosch BMI088, range ±16g, ±2000° / s, sampling frequency 1000Hz) is installed on the truck bed near the tailgate to collect real-time vehicle vibration data. Before the tailgate operation instruction is issued, the PLC control module (model: Siemens S7-1200) obtains the three-dimensional acceleration data of the IMU within a 10-second time window before operation (for example, the maximum acceleration of the X-axis is 2.5m / s 2 , the Y-axis is 1.8m / s 2 , and the Z-axis is 3.2m / s 2) and angular velocity data (maximum angular velocity 5° / s). The PLC control module invokes the FFT algorithm (based on the open-source FFTW library, number of sampling points 1024, frequency resolution 0.98 Hz) to preprocess the Z-axis acceleration data (10 ms mean filter to remove noise), extract the frequency spectrum after performing the FFT transform, and identify the natural frequency of the cargo-vehicle system as 12 Hz (at the spectral peak) and the damping ratio as 0.15 (calculated by the half-power bandwidth method, bandwidth 1.8 Hz). Based on this, the PLC generates an anti-phase control signal (primary frequency 12 Hz, phase shift 180°, amplitude 0.008 m) and outputs it to the servo valve (Moog D633, response frequency 150 Hz) of the hydraulic execution module through the DSP module (model: TIC2000) as a 10 kHz PWM signal (duty cycle 60%). The servo valve adjusts the hydraulic oil flow to 3 L / min according to the signal to drive the hydraulic cylinder (piston diameter 50 mm, stroke 2000 mm) to perform the regular lifting action (speed 0.3 m / s, from 0 mm to 1500 mm, time-consuming 5 seconds) while applying a micro-motion with a frequency of 12 Hz and an amplitude of 8 mm. The micro-motion is realized through the high-frequency reciprocating action of the hydraulic cylinder, with an action period of 83.3 ms (1 / 12 Hz) to ensure synchronization and anti-phase with the cargo vibration mode. During the actual unloading process, the system detects that the vibration amplitude of the medical equipment (weight 500 kg) decreases from the initial 0.015 m to 0.002 m, and the vibration energy decreases by 85%, effectively preventing the equipment from being damaged due to unloading impact. The entire process is real-time scheduled by the RTOS of the PLC, with an algorithm execution delay of less than 1 ms, a servo valve response time of 6 ms, and a system overall response time of less than 10 ms. This active vibration suppression technology significantly improves the unloading safety of high-value and easily damaged cargo, reduces the damage risk during transportation, and reduces the mechanical wear of the tailgate system through precise vibration control, improving the service life of the equipment.

[0085] The embodiment of the application realizes active suppression of cargo vibration during the unloading process of the automobile tailgate by integrating a high-frequency inertial measurement unit in the multi-sensor module, combining the time-frequency analysis and feedforward control algorithm of the PLC control module. The inertial measurement unit captures vehicle vibration data at a high sampling frequency, accurately extracts the vibration modal parameters of the cargo-vehicle system through fast Fourier transform, and provides a reliable basis for generating an anti-phase control signal; the hydraulic execution module applies micro-movement through a high-frequency response servo valve, effectively offsets the residual vibration energy inside the cargo, and significantly reduces the instability risk at the unloading moment. This technology is particularly suitable for transportation scenarios of high-value and easily damaged goods, such as precision instruments, medical equipment and glass products, etc., and improves the safety and reliability of unloading through precise vibration control, while reducing mechanical wear and tear caused by vibration impact, prolonging the service life of the tailgate system. In addition, the real-time and high-precision control capability of the system ensures stable operation under complex working conditions, providing efficient and reliable technical support for modern intelligent logistics systems, significantly reducing the damage rate of goods and maintenance costs during transportation.

[0086] Embodiment 10:

[0087] Figure 2 A flowchart of an intelligent automobile tailgate hydraulic control method based on the Internet of Things is provided for the embodiments of the application, as shown in Figure 2 The method comprises the following steps:

[0088] S1, real-time acquisition of the load state and environmental parameters of the automobile tailgate through a multi-sensor module, wherein the multi-sensor module comprises a pressure sensor, a displacement sensor and an inclination sensor;

[0089] S2, receiving the load state and environmental parameters by a PLC control module, and generating control instructions according to an intelligent control algorithm; the intelligent control algorithm comprises a one-key automatic leveling algorithm and a 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 through an Internet of Things communication module;

[0091] S4, receiving the control instructions by a hydraulic execution module, and driving the tailgate to perform lifting and angle adjustment actions.

[0092] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application 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.

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 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 tailplate 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 actuator to reduce the impact force when the tailplate contacts the ground and dynamically maintain a safe grounding pressure.

8. 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.

9. The IoT-based intelligent vehicle tailgate hydraulic control system as described in claim 1, characterized in that, 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-amplitude motion to the tail plate platform according to the control signal, so as to counteract the residual vibration inside the cargo.

10. 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. 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.

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