Container crane sling potential energy recovery and storage device

Abstract

The invention discloses a container crane lifting appliance potential energy recovery and storage device which comprises a lifting appliance potential energy recovery and storage system, and the lifting appliance potential energy recovery and storage system comprises an energy recovery execution layer, an intelligent control layer and a collaborative application layer. The energy recovery execution layer is used for capturing and converting potential energy generated in a container crane lifting appliance, the energy recovery execution layer comprises an electric potential energy recovery system, a hydraulic potential energy recovery system and a dual-mode switching module, and the electric potential energy recovery system comprises an electric potential energy hardware layer; by recycling the potential energy of the lifting appliance of the container crane, the originally wasted potential energy is collected and stored in the energy storage device to be reused in subsequent operation, the recycled potential energy can directly supplement power required by lifting of the lifting appliance, energy dependence on a power grid or an engine is reduced, energy consumption of the whole machine can be reduced by 15%-30% through potential energy recycling, and the energy consumption of the whole machine is reduced by 20%-30%. And the long-term operation cost is obviously reduced.

Description

Technical Field

[0001] This invention relates to the field of crane spreader technology, specifically to a container crane spreader potential energy recovery and storage device. Background Technology

[0002] Container crane spreaders are specialized equipment used for loading and unloading containers. They are typically installed on bridge cranes, gantry cranes, or reach stackers. Common types include fixed spreaders and master-slave spreaders. Fixed spreaders, also known as integral spreaders, can only handle containers of one size. They lack a dedicated power unit and use a ratchet mechanism driven by the raising and lowering of a wire rope to rotate a rotary lock, automatically opening and closing the locking pin. They are simple in structure and lightweight, but inconvenient to use, and are generally used on multi-purpose gantry cranes and general gantry cranes. Master-slave spreaders, also known as combined spreaders, consist of two spreaders, typically an upper spreader of 20 ft and a lower spreader of 40 ft. The upper spreader is equipped with a power unit. When lifting containers of different sizes, the lower spreader can be loaded or unloaded, making them convenient to use, but they are heavier.

[0003] In existing technologies, container crane spreaders complete hundreds or thousands of lifting cycles every day during operation. The potential energy wasted in each descent accumulates to an astonishing level of energy loss. However, traditional container crane spreaders do not have good potential energy recovery capabilities, thus causing energy waste.

[0004] A search revealed that Chinese patent literature discloses a control method, system, device, and storage medium for potential energy recovery in crane equipment (Publication No.: CN116885822A). This application relates to a control method, system, device, and storage medium for potential energy recovery in crane equipment, belonging to the field of potential energy recovery technology. The method includes: a control module configuring upper / lower limits for potential energy recovery voltage based on upper / lower limits of braking chopper voltage, wherein the upper limit of braking chopper voltage is greater than the upper limit of potential energy recovery voltage, and the lower limit of braking chopper voltage is less than the lower limit of potential energy recovery voltage; when the real-time voltage of the inverter's DC bus is detected to be greater than the upper limit of potential energy recovery voltage, the control module, based on a preset charging current, controls the DCDC module to charge the energy storage module through a current loop adjustment; when the real-time voltage of the inverter's DC bus is detected to be less than the lower limit of potential energy recovery voltage, the control module, based on a preset discharge current, controls the DCDC module to discharge the energy storage module through a current loop adjustment. Using this application, the potential energy of crane equipment can be effectively stored and reused, saving significant electricity costs, reducing energy consumption, and improving port economic efficiency. However, the following drawbacks still exist:

[0005] Although the aforementioned control methods, systems, equipment, and storage media for potential energy recovery of crane equipment can effectively store and reuse the potential energy of crane equipment, saving a significant amount of electricity costs, reducing energy consumption, and improving the economic benefits of ports, they still suffer from insufficient intelligence in the kinetic energy recovery process, resulting in resource waste during the potential energy recovery process. Summary of the Invention

[0006] The purpose of this invention is to provide a potential energy recovery and storage device for container crane spreaders, in order to solve the problem mentioned in the background art. In the operation of container crane spreaders, hundreds or thousands of lifting and lowering cycles are completed every day. The potential energy wasted in each descent accumulates and the energy loss is staggering. However, traditional container crane spreaders do not have good potential energy recovery, thus causing energy waste.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a container crane spreader potential energy recovery and storage device, comprising a spreader potential energy recovery and storage system, wherein the spreader potential energy recovery and storage system comprises an energy recovery execution layer, an intelligent control layer, and a collaborative application layer;

[0008] The function of the energy recovery execution layer is to capture and convert the potential energy generated in the container crane spreader. The energy recovery execution layer includes an electric potential energy recovery system, a hydraulic potential energy recovery system, and a dual-mode switching module. The electric potential energy recovery system includes an electric potential energy hardware layer, which includes an energy storage device group, a bidirectional DC / DC converter, an energy storage device group, and an energy distribution valve. The energy storage device group includes a capacitor and a lithium iron phosphate battery pack. The hydraulic potential energy recovery system includes a hydraulic potential energy hardware layer, which includes a double-acting hydraulic cylinder, a fixed-displacement hydraulic motor, and a permanent magnet generator.

[0009] The intelligent control layer is responsible for processing and making decisions on the data generated during the potential energy recovery process. The intelligent control layer includes a sensor data acquisition module, a data calculation module, and an intelligent control measurement module.

[0010] The collaborative application layer is used to coordinate operations with external systems in the container crane spreader. The collaborative application layer includes a data monitoring module, a remote operation and maintenance management platform, and a scheduling system.

[0011] Preferably, the function of the potential energy recovery system is to convert gravitational potential energy into electrical energy when the lifting device descends via the permanent magnet synchronous lifting motor, and to store it in a capacitor after rectification by a bidirectional DC / DC converter for rapid supply in subsequent operations. At the same time, the surplus electrical energy is stored in a lithium iron phosphate battery pack, and when the lifting device rises via the permanent magnet synchronous lifting motor, the energy is replenished to the DC end of the frequency converter through the converter.

[0012] The function of the hydraulic potential energy recovery system is that when the lifting device is lowered by the double-acting hydraulic cylinder, the high-pressure oil in the return oil chamber inside the double-acting hydraulic cylinder enters the energy recovery oil circuit through the one-way valve and drives the fixed-displacement hydraulic motor to rotate. The fixed-displacement hydraulic motor drives the permanent magnet generator to generate electricity, and the electrical energy generated by the permanent magnet generator is stored in the lithium iron phosphate battery pack.

[0013] The function of the dual-mode switching module is to switch between electric drive mode and hydraulic drive mode by inputting load weight parameter data and operating frequency parameter data.

[0014] Preferably, the specific workflow of the energy recovery execution layer is as follows:

[0015] S1: The spreader is positioned and locked, and load and operating frequency parameters are obtained;

[0016] S2: The lifting device is driven to descend, and the electro-potential energy recovery system or hydraulic potential energy recovery system recovers potential energy.

[0017] S3: Energy conversion and initial distribution, adapted to the characteristics of energy storage devices;

[0018] S4: Continuous recovery and dynamic monitoring ensure efficient energy capture;

[0019] S5: The lifting device is unlocked upon landing, terminating the recovery process and sealing off the energy.

[0020] S6: The lifting device starts lifting, and the execution layer releases stored energy;

[0021] S7: The lifting device is positioned and reset, and the energy recovery execution layer returns to standby mode.

[0022] Preferably, the sensor data acquisition module is used to complete millisecond-level data acquisition of the sensor components contained in the crane spreader. The sensor components include a spreader status sensor, an energy flow sensor, and an environmental and equipment health sensor. The spreader status sensor includes a tilt sensor, a weight sensor, and a weight sensor. The energy flow sensor includes a voltage sensor, a current sensor, a hydraulic pressure sensor, and a hydraulic flow sensor. The environmental and equipment health sensor includes a temperature sensor, a vibration sensor, and a Beidou positioning module.

[0023] Preferably, the computing module includes an edge computing module and an AI computing module. The function of the edge computing module is to use an industrial-grade edge gateway to acquire data from the sensor components contained in the crane spreader in real time, perform data cleaning, and then perform feature extraction.

[0024] The AI ​​computing module includes an energy recovery optimization algorithm, an energy storage balancing management algorithm, and a fault prediction and health management algorithm. The energy recovery optimization algorithm predicts the descent trajectory of the lifting device based on historical operation data using a reinforcement learning model and dynamically adjusts the recovery power. The energy storage balancing management algorithm monitors the remaining capacity, voltage, and temperature of the capacitor and lithium iron phosphate battery pack in real time, and finally avoids overcharging of individual cells and capacitors in the lithium iron phosphate battery pack through active balancing technology. The fault prediction and health management algorithm uses parameter data obtained from all environmental and equipment health sensors and LSTM neural networks to predict braking components and issue maintenance warnings 15 days in advance based on the remaining lifespan of the energy storage device to avoid sudden shutdowns.

[0025] Preferably, the intelligent control measurement module is based on the parameter data acquired by the sensor data acquisition module, performs calculations on the data through the calculation module, makes decisions, and finally generates execution instructions through monitoring to complete the execution task.

[0026] Preferably, the operating procedure of the intelligent control and measurement module is as follows:

[0027] Step 1: Multi-dimensional data perception and real-time acquisition;

[0028] Step 2: Edge computing and data preprocessing;

[0029] Step 3: AI algorithm decision-making and control strategy generation;

[0030] Step 4: Issuance of execution instructions and multi-unit collaborative actions;

[0031] Step 5: Real-time feedback and dynamic strategy adjustment;

[0032] Step Six: Finishing the Work and Archiving the Data.

[0033] Preferably, the data monitoring module is used to deploy a display device in the container crane operator's cab, and to display energy flow data, equipment status and operation suggestions in real time through the display device in conjunction with the data monitoring module.

[0034] The remote operation and maintenance management platform is used to receive real-time data from cranes via a 5G network to enable remote monitoring, energy consumption analysis, and remote diagnosis and upgrades.

[0035] Preferably, the scheduling system provides an open API interface and works in conjunction with the work area operating system. It obtains container transportation plans and container stacking locations through the work area operating system, and the AI ​​controller predicts the operation trajectory of the spreader in advance, pre-adjusts the charging and discharging strategy of the energy storage device, and obtains the peak and valley electricity prices of the power grid through the work area operating system, thereby automatically adjusting the charging and discharging timing of the energy storage device.

[0036] Preferably, the lifting device potential energy recovery and storage system incorporates integrated digital twin technology. By constructing a virtual simulation model of the crane and lifting device using integrated digital twin technology, full life-cycle digital management is achieved. Specifically, the construction of the virtual simulation model of the crane and lifting device using integrated digital twin technology requires the collection of geometric structure data, physical attribute data, and real-time sensor data, and the construction is completed through the fusion of geometric modeling, physical modeling, and control modeling.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. This invention recovers the potential energy of a container crane spreader, collecting the previously wasted potential energy and storing it in an energy storage device for reuse in subsequent operations. The recovered potential energy can directly supplement the power required for the spreader to lift, reducing the energy dependence on the power grid or engine. Potential energy recovery can reduce the overall energy consumption of the machine by 15% to 30%, resulting in a significant reduction in long-term operating costs.

[0039] 2. By recovering the potential energy of container crane spreaders, this invention can reduce the consumption of fossil fuels or reduce the demand for electricity from the power grid, thereby indirectly reducing carbon emissions from thermal power generation. At the same time, reducing dust generated by braking friction can also reduce pollution to the working environment.

[0040] 3. This invention optimizes the traditional crane's reliance on friction braking to consume potential energy by recovering the potential energy of the container crane's spreader. Components such as brake pads and brake wheels wear out quickly due to frequent friction, requiring regular replacement, resulting in high maintenance costs and affecting operational continuity. This invention significantly reduces braking load, extends the life of braking components, and reduces downtime for maintenance. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the modular structure of the lifting device potential energy recovery and storage system in this invention;

[0042] Figure 2 This is a schematic diagram of the energy recovery execution layer in this invention;

[0043] Figure 3 This is a schematic diagram of the intelligent control layer in this invention;

[0044] Figure 4 This is a schematic diagram of the collaborative application layer in this invention;

[0045] Figure 5 This is a schematic diagram of the specific operation process of the energy recovery execution layer in this invention;

[0046] Figure 6 This is a schematic diagram of the operation process of the intelligent control and measurement module in this invention. Detailed Implementation

[0047] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0048] Example 1

[0049] Please see Figures 1-4 The present invention provides a container crane spreader potential energy recovery and storage device, including a spreader potential energy recovery and storage system, characterized in that: the spreader potential energy recovery and storage system includes an energy recovery execution layer, an intelligent control layer and a collaborative application layer.

[0050] The function of the energy recovery execution layer is to capture and convert the potential energy generated in the container crane spreader. The energy recovery execution layer includes an electric potential energy recovery system, a hydraulic potential energy recovery system, and a dual-mode switching module. The electric potential energy recovery system includes an electric potential energy hardware layer, which includes an energy storage device group, a bidirectional DC / DC converter, an energy storage device group, and an energy distribution valve. The energy storage device group includes capacitors and lithium iron phosphate battery packs. The hydraulic potential energy recovery system includes a hydraulic potential energy hardware layer, which includes a double-acting hydraulic cylinder, a fixed displacement hydraulic motor, and a permanent magnet generator.

[0051] Both the electric potential energy recovery system and the hydraulic potential energy recovery system are electrically connected to the dual-mode switching module.

[0052] The power of the permanent magnet synchronous hoisting motor is adapted to the rated lifting capacity of the crane, and the permanent magnet synchronous hoisting motor supports four-quadrant operation. The efficiency of the bidirectional DC / DC converter is ≥96%, and the bidirectional DC / DC converter supports voltage adaptive adjustment and is compatible with 380V / 690V power grid. The parameters of the lithium iron phosphate battery pack are 200kWh and the cycle life is ≥3000 times. The parameters of the capacitor are 1200F / 750V, the charge and discharge response time is ≤20ms, and the parameters of the energy distribution valve are intelligent control of the power flow.

[0053] The double-acting hydraulic cylinder is adapted to the rated load of the lifting device and is equipped with a pressure sensor. The parameters of the fixed displacement hydraulic motor are: displacement 160mL / r, efficiency ≥92%. The parameters of the permanent magnet generator are: 50kW, output voltage 380V.

[0054] The role of the intelligent control layer is to process and make decisions on the data generated during the potential energy recovery process. The intelligent control layer includes a sensor data acquisition module, a data calculation module, and an intelligent control measurement module.

[0055] The sensor data acquisition module is electrically connected to the data calculation module and the intelligent control and measurement module, and the data calculation module is electrically connected to the intelligent control and measurement module.

[0056] The collaborative application layer is responsible for enabling coordinated operations with external systems in the container crane spreader. The collaborative application layer includes a data monitoring module, a remote operation and maintenance management platform, and a scheduling system.

[0057] The execution layer, intelligent control layer, and collaborative application layer are electrically connected to each other.

[0058] The function of the potential energy recovery system is to convert gravitational potential energy into electrical energy when the lifting device descends via the permanent magnet synchronous lifting motor, and to store it in a capacitor after rectification by a bidirectional DC / DC converter for rapid supply in subsequent operations. At the same time, the surplus electrical energy is stored in the lithium iron phosphate battery pack, and when the lifting device rises via the permanent magnet synchronous lifting motor, the converter replenishes the DC end of the frequency converter.

[0059] The function of the hydraulic potential energy recovery system is that when the lifting device is lowered by the double-acting hydraulic cylinder, the high-pressure oil in the return oil chamber inside the double-acting hydraulic cylinder enters the energy recovery oil circuit through the one-way valve and drives the fixed-displacement hydraulic motor to rotate. The fixed-displacement hydraulic motor drives the permanent magnet generator to generate electricity, and the electrical energy generated by the permanent magnet generator is stored in the lithium iron phosphate battery pack.

[0060] The dual-mode switching module is used to switch between electric drive mode and hydraulic drive mode by inputting load weight parameters and operating frequency parameters.

[0061] The dual-mode switching module includes a heavy-load mode and a light-load mode. The heavy-load mode is characterized by load weight parameters exceeding the specified weight and high-frequency operation. The heavy-load mode adopts a hybrid electric drive and capacitor mode, and utilizes the fast charging and discharging characteristics of the capacitor to reduce the impact on the power grid. The light-load mode is characterized by load weight parameters less than the specified weight and low-frequency operation. The light-load mode adopts hydraulic drive, thereby effectively reducing system energy consumption.

[0062] The function of the sensor data acquisition module is to complete millisecond-level data acquisition of the sensor components contained in the crane spreader. The sensor components include spreader status sensors, energy flow sensors, and environmental and equipment health sensors. The spreader status sensors include tilt sensors, weight sensors, and weight sensors. The energy flow sensors include voltage sensors, current sensors, hydraulic pressure sensors, and hydraulic flow sensors. The environmental and equipment health sensors include temperature sensors, vibration sensors, and a Beidou positioning module.

[0063] The tilt sensor detects the levelness of the lifting device with an accuracy of ±0.1°. The weight sensor collects the load weight in real time. The lock status sensor detects whether the lock is properly engaged with a response time of ≤10ms. The voltage and current sensors monitor the power of the power grid and energy storage devices with an accuracy of 0.5%. The hydraulic pressure and flow sensors detect oil pressure with a range of 0-40MPa and an accuracy of ±0.2%. The temperature sensor monitors the temperature of the motor and hydraulic oil with a range of -40 to 125℃. The vibration sensor is deployed on the motor bearings to monitor vibration acceleration and provide early warning of equipment failures. The Beidou positioning module obtains the crane's position and links it to the dispatching system.

[0064] The computing module includes an edge computing module and an AI computing module. The edge computing module uses an industrial-grade edge gateway to acquire data from the sensor components contained in the crane spreader in real time, cleans the data, and then extracts features.

[0065] The AI ​​computing module includes an energy recovery optimization algorithm, an energy storage balancing management algorithm, and a fault prediction and health management algorithm. The energy recovery optimization algorithm predicts the descent trajectory of the lifting device based on historical operation data using a reinforcement learning model and dynamically adjusts the recovery power. The energy storage balancing management algorithm monitors the remaining capacity, voltage, and temperature of the capacitor and lithium iron phosphate battery pack in real time. Finally, it avoids overcharging of individual cells and capacitors in the lithium iron phosphate battery pack through active balancing technology. The fault prediction and health management algorithm uses parameter data obtained from all environmental and equipment health sensors and LSTM neural networks to predict braking components and issue maintenance warnings 15 days in advance based on the remaining lifespan of the energy storage device, thus avoiding sudden shutdowns.

[0066] The intelligent control measurement module is based on the parameter data acquired by the sensor data acquisition module, and performs calculations on the data through the calculation module to make decisions. Finally, it generates execution instructions through monitoring to complete the execution of the task.

[0067] The data monitoring module is designed to deploy display equipment in the container crane's control room, and to display energy flow data, equipment status, and operational suggestions in real time through the display equipment in conjunction with the data monitoring module.

[0068] Energy flow data should include at least the recovered power parameter data, energy storage SOC parameter data, grid supplementation ratio parameter data, and cumulative energy saving parameter data.

[0069] The equipment status includes at least the following parameters: the levelness of the lifting device, the status of the twistlock, the temperature of the motor system, the temperature of the hydraulic system, and fault warning information.

[0070] The recommended takeoff and landing speeds are based on AI algorithms.

[0071] The remote operation and maintenance management platform is used to receive real-time data from cranes via 5G networks to enable remote monitoring, energy consumption analysis, and remote diagnosis and upgrades.

[0072] The scheduling system provides an open API interface and works in conjunction with the operating system of the work area. It obtains container transportation plans and container stacking locations through the operating system of the work area, and the AI ​​controller predicts the operation trajectory of the spreader in advance, pre-adjusts the charging and discharging strategy of the energy storage device, and obtains the peak and valley electricity prices of the power grid through the operating system of the work area, thereby automatically adjusting the charging and discharging timing of the energy storage device.

[0073] The potential energy recovery and storage system for lifting equipment incorporates integrated digital twin technology. By using integrated digital twin technology to construct a virtual simulation model of the crane and lifting equipment, it achieves full lifecycle digital management. Specifically, the construction of the virtual simulation model of the crane and lifting equipment using integrated digital twin technology requires the collection of geometric structure data, physical attribute data, and real-time sensor data, and is completed through the fusion of geometric modeling, physical modeling, and control modeling.

[0074] Example 2

[0075] Please see Figure 5 This invention provides a container crane spreader potential energy recovery and storage device, including an energy recovery execution layer. The specific operation process of the energy recovery execution layer is as follows:

[0076] S1: The spreader is positioned and locked, and load and operating frequency parameters are obtained;

[0077] S2: The lifting device is driven to descend, and the electro-potential energy recovery system or hydraulic potential energy recovery system recovers potential energy.

[0078] S3: Energy conversion and initial distribution, adapted to the characteristics of energy storage devices;

[0079] S4: Continuous recovery and dynamic monitoring ensure efficient energy capture;

[0080] S5: The lifting device is unlocked upon landing, terminating the recovery process and sealing off the energy.

[0081] S6: The lifting device starts lifting, and the execution layer releases stored energy;

[0082] S7: The lifting device is positioned and reset, and the energy recovery execution layer returns to standby mode.

[0083] In S1, the spreader positioning and locking is achieved by driving the rotary lock to insert into the top corner piece of the container, and the rotary lock status sensor provides real-time feedback of the locking position signal.

[0084] In S4, dynamic monitoring is used to monitor load changes in real time and control the bidirectional DC / DC converter to adjust the recovered power and match the potential energy release rate.

[0085] Example 3

[0086] Please see Figure 6 This invention provides a container crane spreader potential energy recovery and storage device, including an intelligent control and measurement module. The operation process of the intelligent control and measurement module is as follows:

[0087] Step 1: Multi-dimensional data perception and real-time acquisition;

[0088] Step 2: Edge computing and data preprocessing;

[0089] Step 3: AI algorithm decision-making and control strategy generation;

[0090] Step 4: Issuance of execution instructions and multi-unit collaborative actions;

[0091] Step 5: Real-time feedback and dynamic strategy adjustment;

[0092] Step Six: Finishing the Work and Archiving the Data.

[0093] In step one, multi-dimensional data perception and real-time acquisition realize a closed-loop input end and obtain comprehensive and accurate operation data, covering four dimensions: load status, equipment operating parameters, energy storage status and environmental information.

[0094] In step two, the data preprocessing specifically involves removing sensor noise using a filtering algorithm to retain the true load data; using interpolation to complete missing data to ensure data integrity; extracting key control features from the original data; and identifying abnormal data through threshold judgment and trend analysis. If an anomaly is detected, a primary warning is immediately triggered, and subsequent decision-making operations are suspended until the fault is resolved and the closed loop is restarted.

[0095] In step three, the AI ​​algorithm decision-making includes at least an energy recovery optimization algorithm, an energy storage balance management algorithm, and a safety and collaboration algorithm;

[0096] The input values ​​for the energy recovery optimization algorithm are load weight parameter data, descent speed parameter data, operation plan parameter data, and ambient wind speed parameter data. The algorithm logic is to use a reinforcement learning model to make decisions by maximizing recovery efficiency and minimizing equipment wear as reward functions, combined with historical operation data.

[0097] The input values ​​of the energy storage equalization management algorithm are capacitor SOC parameter data, lithium iron phosphate battery pack SOC parameter data, individual capacitor voltage deviation parameter data, and lithium iron phosphate battery pack temperature parameter data. The algorithm logic of the energy storage equalization management algorithm is based on a multi-objective optimization algorithm to formulate an allocation strategy.

[0098] The input values ​​for the safety and collaboration algorithm are spreader levelness parameter data, brake pad remaining thickness parameter data, and port TOS scheduling instruction parameter data. The algorithm logic of the safety and collaboration algorithm is to add safety and collaboration constraints and optimize strategy details.

[0099] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A container crane spreader potential energy recovery and storage device, comprising a spreader potential energy recovery and storage system, characterized in that: The spreader potential energy recovery and storage system includes an energy recovery execution layer, an intelligent control layer, and a collaborative application layer; The function of the energy recovery execution layer is to capture and convert the potential energy generated in the container crane spreader. The energy recovery execution layer includes an electric potential energy recovery system, a hydraulic potential energy recovery system, and a dual-mode switching module. The electric potential energy recovery system includes an electric potential energy hardware layer, which includes an energy storage device group, a bidirectional DC / DC converter, an energy storage device group, and an energy distribution valve. The energy storage device group includes a capacitor and a lithium iron phosphate battery pack. The hydraulic potential energy recovery system includes a hydraulic potential energy hardware layer, which includes a double-acting hydraulic cylinder, a fixed-displacement hydraulic motor, and a permanent magnet generator. The intelligent control layer is responsible for processing and making decisions on the data generated during the potential energy recovery process. The intelligent control layer includes a sensor data acquisition module, a data calculation module, and an intelligent control measurement module. The collaborative application layer is used to coordinate operations with external systems in the container crane spreader. The collaborative application layer includes a data monitoring module, a remote operation and maintenance management platform, and a scheduling system.

2. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The function of the potential energy recovery system is to convert gravitational potential energy into electrical energy when the lifting device descends via the permanent magnet synchronous lifting motor, and to store it in a capacitor after rectification by a bidirectional DC / DC converter for rapid supply in subsequent operations. At the same time, the surplus electrical energy is stored in the lithium iron phosphate battery pack, and when the lifting device rises via the permanent magnet synchronous lifting motor, the converter replenishes the DC end of the frequency converter. The function of the hydraulic potential energy recovery system is that when the lifting device is lowered by the double-acting hydraulic cylinder, the high-pressure oil in the return oil chamber inside the double-acting hydraulic cylinder enters the energy recovery oil circuit through the one-way valve and drives the fixed-displacement hydraulic motor to rotate. The fixed-displacement hydraulic motor drives the permanent magnet generator to generate electricity, and the electrical energy generated by the permanent magnet generator is stored in the lithium iron phosphate battery pack. The function of the dual-mode switching module is to switch between electric drive mode and hydraulic drive mode by inputting load weight parameter data and operating frequency parameter data.

3. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The specific workflow of the energy recovery execution layer is as follows: S1: The spreader is positioned and locked, and load and operating frequency parameters are obtained; S2: The lifting device is driven to descend, and the electro-potential energy recovery system or hydraulic potential energy recovery system recovers potential energy. S3: Energy conversion and initial distribution, adapted to the characteristics of energy storage devices; S4: Continuous recovery and dynamic monitoring ensure efficient energy capture; S5: The lifting device is unlocked upon landing, terminating the recovery process and sealing off the energy. S6: The lifting device starts lifting, and the execution layer releases stored energy; S7: The lifting device is positioned and reset, and the energy recovery execution layer returns to standby mode.

4. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The function of the sensor data acquisition module is to complete millisecond-level data acquisition of the sensor components contained in the crane spreader. The sensor components include a spreader status sensor, an energy flow sensor, and an environmental and equipment health sensor. The spreader status sensor includes a tilt sensor, a weight sensor, and a weight sensor. The energy flow sensor includes a voltage sensor, a current sensor, a hydraulic pressure sensor, and a hydraulic flow sensor. The environmental and equipment health sensor includes a temperature sensor, a vibration sensor, and a Beidou positioning module.

5. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The computing module includes an edge computing module and an AI computing module. The edge computing module uses an industrial-grade edge gateway to acquire data from the sensor components contained in the crane spreader in real time, cleans the data, and then extracts features. The AI ​​computing module includes an energy recovery optimization algorithm, an energy storage balancing management algorithm, and a fault prediction and health management algorithm. The energy recovery optimization algorithm predicts the descent trajectory of the lifting device based on historical operation data using a reinforcement learning model and dynamically adjusts the recovery power. The energy storage balancing management algorithm monitors the remaining capacity, voltage, and temperature of the capacitor and lithium iron phosphate battery pack in real time, and finally avoids overcharging of individual cells and capacitors in the lithium iron phosphate battery pack through active balancing technology. The fault prediction and health management algorithm uses parameter data obtained from all environmental and equipment health sensors and LSTM neural networks to predict braking components and issue maintenance warnings 15 days in advance based on the remaining lifespan of the energy storage device to avoid sudden shutdowns.

6. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The intelligent control and measurement module is based on the parameter data acquired by the sensor data acquisition module, and performs calculations on the data through the calculation module to make decisions. Finally, it generates execution instructions through monitoring to complete the execution of the task.

7. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The operating procedure of the intelligent control and measurement module is as follows: Step 1: Multi-dimensional data perception and real-time acquisition; Step 2: Edge computing and data preprocessing; Step 3: AI algorithm decision-making and control strategy generation; Step 4: Issuance of execution instructions and multi-unit collaborative actions; Step 5: Real-time feedback and dynamic strategy adjustment; Step Six: Finishing the Work and Archiving the Data.

8. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The data monitoring module is designed to deploy a display device in the container crane's control room, and to display energy flow data, equipment status, and operational suggestions in real time through the display device in conjunction with the data monitoring module. The remote operation and maintenance management platform is used to receive real-time data from cranes via a 5G network to enable remote monitoring, energy consumption analysis, and remote diagnosis and upgrades.

9. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The scheduling system provides an open API interface and works in conjunction with the operating system of the work area. It obtains container transportation plans and container stacking locations through the operating system of the work area, and the AI ​​controller predicts the operation trajectory of the spreader in advance, pre-adjusts the charging and discharging strategy of the energy storage device, and obtains the peak and valley electricity prices of the power grid through the operating system of the work area, thereby automatically adjusting the charging and discharging timing of the energy storage device.

10. The container crane spreader potential energy recovery and storage device according to claim 1, characterized in that: The lifting device potential energy recovery and storage system incorporates integrated digital twin technology. By constructing a virtual simulation model of the crane and lifting device using integrated digital twin technology, it achieves full lifecycle digital management. Specifically, the construction of the virtual simulation model of the crane and lifting device using integrated digital twin technology requires the collection of geometric structure data, physical attribute data, and real-time sensor data, and the construction is completed through the fusion of geometric modeling, physical modeling, and control modeling.

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