Lifting type cable guide and electric take-up and pay-off integrated charging pile system

Abstract

The invention discloses a lifting type cable guiding and electric winding and unwinding integrated charging pile system, and relates to the technical field of new energy automobile charging, and the system comprises an information collection module used for collecting the vehicle plugging state and charging port position information, and a height calculation module used for calculating the height of a charging pile based on the vehicle plugging state and charging port position information. The optimal lifting height calculation module is used for calculating the optimal lifting height of the cable guide mechanism, the lifting control module is used for controlling the cable guide mechanism to carry out lifting adjustment according to the optimal lifting height, and the plugging execution module is used for executing automatic alignment and plugging operation of the cable; according to the lifting type cable guiding and electric winding and unwinding integrated charging pile system, the lifting height of the cable guiding mechanism is regulated and controlled according to the vehicle insertion state and position recognition, so that the problem that insertion and extraction are difficult due to insufficient alignment precision is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicle charging, and in particular to a charging pile system integrating lifting cable guidance and electric retraction. Background Art

[0002] In the development of new energy vehicle charging technology, traditional charging piles mostly use fixed cable connections, requiring users to manually plug and unplug the cable to complete charging operations. However, in actual use, factors such as vehicle parking position deviations and manual insertion and removal errors often lead to insufficient alignment accuracy between the charging gun and the vehicle socket, causing insertion and removal difficulties, affecting the user experience, and even causing damage to the charging port or cable.

[0003] To this end, some systems have begun to incorporate cable guides with lifting functions or electrically retractable structures to reduce the burden of manual operation. However, existing lifting cable guides generally suffer from delayed response or inaccurate positioning. This is primarily due to the lack of effective vehicle position recognition and plug-in status determination mechanisms, which prevent the cable end from adjusting height in real time. As a result, even when the vehicle interface position changes, the cable head still cannot be accurately aligned with the vehicle socket, and plugging and unplugging operations still experience significant resistance or deviation. In addition, some electrically retractable systems fail to synchronize with the vehicle status and only adjust based on a preset height, further limiting the system's adaptability and intelligence. Summary of the Invention

[0004] The purpose of the present invention is to provide an integrated charging pile system with lifting cable guidance and electric retraction, which can adjust the lifting height of the cable guide mechanism according to the vehicle plug-in status and position recognition to solve the problem of difficulty in plugging and unplugging caused by insufficient alignment accuracy.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a lifting cable guide and electric retractable integrated charging pile system, the system comprising:

[0006] Information collection module, used to collect vehicle plug-in status and charging port location information;

[0007] A height calculation module is used to calculate the optimal lifting height of the cable guide mechanism based on the vehicle plug-in status and charging port position information;

[0008] A lifting control module is used to control the cable guide mechanism to adjust the lifting height according to the optimal lifting height;

[0009] The plugging and unplugging execution module is used to perform automatic alignment and plugging and unplugging operations of cables.

[0010] Preferably, the information collection module includes a plurality of visual sensors or infrared sensors installed on the charging pile body and the ground within a preset range, which are used to obtain the vehicle parking posture, body contour and three-dimensional spatial coordinates of the charging port in real time.

[0011] Preferably, the height calculation module calculates the optimal lifting height of the cable guide mechanism by fusing the vehicle plug-in status, vehicle type database and historical plug-in trajectory data, and adopts a posture estimation algorithm based on deep learning to improve the adaptability and accuracy of the lifting control.

[0012] Preferably, the lifting control module and a group of multi-stage electric lifting columns form a closed-loop control structure. The electric lifting columns have displacement feedback capabilities and can dynamically correct the target height based on a real-time height adjustment strategy during the lifting process.

[0013] Preferably, it also includes a posture stabilization module for dynamically adjusting the tilt posture of the cable guiding mechanism according to environmental parameters such as the tilt angle of the vehicle charging port, the tire compression state and the ground slope, so as to ensure that the cable plug always maintains an angle aligned with the charging interface.

[0014] Preferably, a flexible force control unit is integrated into the plug-in execution module, and the flexible force control unit automatically adjusts the insertion force and insertion speed by monitoring the change of the contact force between the cable plug and the vehicle charging port in real time.

[0015] Preferably, the information acquisition module also includes a laser radar unit and a three-dimensional imaging module, the laser radar is used to construct a high-precision point cloud model of the vehicle's surroundings, and the three-dimensional imaging module is used to assist in identifying the vehicle body posture and spatial obstacles.

[0016] Preferably, it also includes a user identity recognition and preference learning module, which is used to identify the user's identity through face recognition, license plate recognition or mobile terminal authentication, and combines the user's charging behavior habits, parking location history records and personalized needs.

[0017] Preferably, it also includes a health diagnosis and life prediction module, which establishes an equipment fatigue model by collecting the key parameters of each component's usage frequency, temperature rise curve, mechanical impact record, cable bending radius and tension change in real time, and then predicts the component life and generates maintenance warnings, thereby realizing early diagnosis and life cycle management of key components.

[0018] Preferably, it also includes a self-learning intelligent control module, which continuously optimizes the plug-in and unplugging path, cable release speed and lifting logic based on the reinforcement learning algorithm, and can self-adjust parameters according to operational feedback and error data during long-term use, thereby achieving dynamic improvement in plug-in and unplugging efficiency and system response performance.

[0019] It can be seen from the above technical solution that the present invention has the following beneficial effects:

[0020] The lifting cable guidance and electric retractable integrated charging pile system obtains the actual parking posture of the vehicle and the three-dimensional position information of the charging port in real time through the information acquisition module, and combines the dynamic calculation of the optimal lifting height by the height calculation module to achieve precise docking of the cable plug in the spatial position, significantly reducing the difficulty of plugging and unplugging and the risk of equipment damage caused by plugging deviation. The system as a whole constructs a closed-loop intelligent control process from information perception, path calculation to action execution, avoiding the uncertainty of manual plugging and unplugging operations, realizing unattended automatic plugging and unplugging functions, improving user convenience and operating efficiency. Compared with the traditional electric retractable system that only relies on preset height, this system The system can respond in real time to different vehicle models, different parking positions and environmental changes, dynamically adjust the cable guidance path, and has higher environmental adaptability and compatibility. It is suitable for complex scenarios and multiple types of vehicles. It can accurately control the lifting and lowering process and plugging and unplugging actions of the cable end, effectively avoiding multiple plug docking failures or cable fatigue caused by excessive pulling, thereby extending the service life of key components of the system and reducing maintenance costs. The system plug-in execution module automatically completes the cable connection action throughout the whole process, reducing the user's chance of contact with high-voltage components, and can be combined with the identification module to monitor abnormal conditions in real time, effectively preventing misoperation, and improving the overall system's operational safety and user comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a system connection diagram of the present invention. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] like Figure 1 As shown, the present invention provides a technical solution: a lifting cable guide and electric retractable integrated charging pile system, the system comprising:

[0024] Information collection module, used to collect vehicle plug-in status and charging port location information;

[0025] A height calculation module is used to calculate the optimal lifting height of the cable guide mechanism based on the vehicle plug-in status and charging port position information;

[0026] A lifting control module is used to control the cable guide mechanism to adjust the lifting height according to the optimal lifting height;

[0027] The plugging and unplugging execution module is used to perform automatic alignment and plugging and unplugging operations of cables.

[0028] The system first uses an information acquisition module to identify and locate the vehicle being charged. The information acquisition module includes a camera, an infrared ranging sensor, and an angle detector. The camera is installed on the front or top of the charging station to capture the vehicle's parking position and body structure. The system uses an image recognition program to analyze the vehicle's front face features to identify the vehicle type and the approximate location of the charging port. The infrared ranging sensor measures the distance between the front end of the vehicle and the charging station, further locating the relative spatial relationship between the vehicle and the charging device. The angle detector is responsible for determining whether the vehicle has lateral or fore-aft offset and sends the offset angle data to the system control center for subsequent posture correction.

[0029] Once this information is collected, the system activates the height calculation module to accurately calculate the required lift height for the cable guide mechanism. Based on the identified vehicle type, this module accesses the standard charging port height information stored in a pre-set vehicle model database. The system compares this height with parameters such as the currently measured vehicle-to-ground distance, the charging station outlet height, and the vehicle's parking angle, ultimately determining a target lift height appropriate for the current situation. This height is then transmitted as a control command to the lift control module.

[0030] The lift control module houses an electric actuator drive mechanism and position detection sensors. The electric actuator, driven by a motor, moves the screw up and down, achieving vertical lift and lowering of the cable guide mechanism. The control system inputs the target height command to the actuator controller, which activates the actuator and moves at the set speed until the cable guide mechanism reaches the target position. The real-time position of the cable guide during the lift is detected by sensors and fed back to the control system, ensuring that the cable guide mechanism is accurately positioned within the desired height range and automatically stops within the tolerance range.

[0031] When the cable guiding mechanism completes the lifting and positioning, the plug-in execution module starts working. The plug-in execution module consists of a multi-joint robotic arm and an end charging gun. The joints of the robotic arm are driven by multiple servo motors and can move flexibly in the horizontal and vertical directions. Based on the three-dimensional coordinate information of the charging port collected by the system in the early stage, the control program calculates the optimal path of the robotic arm, and drives each joint in turn to adjust the posture so that the end of the charging gun is aligned with the vehicle charging port. After the alignment is completed, the end effector pushes the charging gun forward until it is fully inserted into the charging port and a reliable electrical connection is achieved. The insertion process is monitored by a pressure sensor to ensure that the insertion action is smooth, safe, and does not cause mechanical damage. After charging is completed, the system drives the robotic arm in reverse to perform the extraction and storage operations. The entire process does not require human intervention.

[0032] This system significantly improves the automation of the charging process, resolving issues such as low efficiency, large errors, and heavy user burden associated with traditional manual plugging and unplugging. Through intelligent recognition and automatic lifting and adjustment, it effectively improves cable connection accuracy and charging safety, reducing the need for manual intervention. The system can adapt to different vehicle models and environments with varying heights, enhancing the versatility and flexibility of charging facilities, and boasts excellent scalability and market application prospects. Furthermore, the motorized retraction mechanism facilitates orderly cable management, preventing entanglement and wear, and improving the overall reliability and ease of maintenance of the system.

[0033] The information collection module includes multiple visual sensors or infrared sensors installed on the charging pile body and the ground within a preset range, which are used to obtain the vehicle's parking posture, body outline and three-dimensional spatial coordinates of the charging port in real time.

[0034] The information acquisition module constructs a three-dimensional perception network covering the area in front of the vehicle by installing multiple visual sensors and infrared sensors at different heights of the charging pile body and on the ground in front of it. The visual sensor uses a wide-angle lens and an image recognition chip integrated into a package, which can capture the overall outline, parking angle and front features of the vehicle after it enters the charging position. Infrared sensors are deployed on both sides of the ground and continuously measure the distance between the lower part of the front of the vehicle and the ground to assist in determining whether the vehicle has been completely parked in the designated charging area and whether it is parked at an angle or crooked. After the vehicle stops, the system automatically starts the coordinate recognition algorithm, processes the image information and superimposes the distance measurement data to complete the vehicle posture recognition and reconstruction of the three-dimensional spatial coordinates of the charging port. Finally, the processing results are transmitted by the controller to the height calculation module and the plug-in execution module, providing accurate spatial parameter support for subsequent lifting height calculation and robotic arm path planning.

[0035] By deploying multiple sensors on the charging pile itself and on the ground, the system can capture the vehicle's shape and position from multiple angles, enhancing the accuracy of the charging port's spatial coordinates. This ensures stable recognition, especially in conditions of poor lighting or when vehicles are parked in varying locations. Compared to single-point or single-side recognition solutions, this modular structure offers greater environmental adaptability and anti-interference capabilities. It can significantly improve the positioning accuracy of the cable guide mechanism and plug-in actuator module, thereby enhancing the overall system's adaptability to different vehicle types and complex parking postures, ensuring safety and automation throughout the charging process.

[0036] The height calculation module integrates the vehicle connection status, vehicle type database and historical connection trajectory data, and uses a deep learning-based posture estimation algorithm to calculate the optimal lifting height of the cable guide mechanism, thereby improving the adaptability and accuracy of the lifting control.

[0037] After receiving the vehicle docking status from the information acquisition module, the height calculation module first extracts the current vehicle's parking angle, front face position, and body posture parameters. Simultaneously, the module accesses the internal vehicle type database and, based on the identified vehicle model, retrieves the standard charging port height, front face structural outline, and parameter records of past successful docking. The module matches the current recognition data with the standard model in the database to select representative docking trajectory samples. The real-time data collected, along with the selected historical docking trajectory data, is then fed into a pre-trained deep neural network. Based on large-scale sample learning, this network automatically determines the optimal docking path and the corresponding cable guide mechanism lift height. The neural network model includes a posture estimation structure that corrects the vehicle's spatial position relative to the charging station and outputs a robust lift height command. This height command is then passed to the lift control module to guide the cable guide mechanism to the corresponding position adjustment.

[0038] Compared with traditional geometric calculation methods, this solution significantly improves the adaptability to non-standard parking postures by introducing deep learning algorithms and historical data fusion mechanisms. The system can effectively identify subtle differences between different models at different parking angles, automatically correct the height deviation of the charging port, and improve the control accuracy and plugging success rate of the cable lifting mechanism. The use of neural network algorithms can also continuously learn user usage behavior, continuously optimize the lifting strategy in long-term operation, and enhance the system's adaptability and response speed. At the same time, this method can maintain stable computing capabilities even in complex environments (such as tilted parking spaces, rainy and snowy weather, etc.), thereby improving the reliability and intelligence level of the entire charging system.

[0039] The lifting control module and a set of multi-stage electric lifting columns form a closed-loop control structure. The electric lifting columns have displacement feedback capabilities and can dynamically correct the target height based on the real-time height adjustment strategy during the lifting process.

[0040] The lift control module, along with a set of multi-stage electric lifting columns installed within the charging station, forms a complete lift execution unit. Each electric lifting column consists of multiple telescopic segments, integrated with a linear motor drive system and a high-precision position encoder. Upon receiving the target height command, the lift control module activates each motor segment according to a preset speed profile, driving the lifting column to extend or retract sequentially, achieving the up and down movement of the cable guide mechanism. During operation, the lifting column's displacement feedback unit monitors the difference between the current extension length and the target position in real time and transmits this data to the control module via a communication interface. Based on this feedback, the control module executes closed-loop correction logic, dynamically adjusting the output current or control pulses to ensure that the actual motion trajectory closely matches the target curve, avoiding overshoot or positional offset. If external interference or system errors cause the displacement deviation to exceed a set threshold, the control module automatically triggers a fine-tuning strategy to compensate for the displacement of each column segment, ensuring that the cable guide mechanism remains precisely at the specified height.

[0041] By constructing a closed-loop control structure, the system achieves high-precision control of the cable guide mechanism's lifting position, significantly improving its response speed and control stability. The multi-stage electric lifting column offers a wider travel range and higher structural strength, adapting to the needs of different vehicle models and charging port height differences. The displacement feedback function provides the system with dynamic correction capabilities, enabling real-time correction based on actual motion during the lifting process. This improves fault tolerance to unforeseen disturbances and environmental adaptability, further enhancing system reliability and automation.

[0042] It also includes a posture stabilization module, which is used to dynamically adjust the tilt posture of the cable guide mechanism according to environmental parameters such as the tilt angle of the vehicle charging port, the tire compression status and the ground slope, so as to ensure that the cable plug always maintains an angle aligned with the charging port.

[0043] The attitude stabilization module consists of multiple angle sensors, pressure detection devices, and attitude adjustment actuators. The module first uses angle sensors installed at the end of the cable guide mechanism and around the charging station to collect real-time information on the tilt direction and slope of the vehicle's parking area. Simultaneously, the pressure sensor array located in front of the charging station senses changes in pressure on the vehicle's front wheels, thereby determining whether the tires are compressing and deforming due to load differences. Combining these environmental parameters, the system uses a built-in attitude solution model to calculate the current tilt angle of the vehicle's charging port, including fore-aft tilt, left-right offset, and spatial orientation. The processing unit compares the attitude difference with the standard plug-in attitude to determine the angle amplitude and direction that need to be adjusted.

[0044] The attitude adjustment actuator, consisting of a set of micro-servo motors or universal adjustment bases, is mounted on the cable guide's connection base, enabling micro-adjustments in pitch, roll, and twist. When the control system issues an attitude adjustment command, the servo motors activate and synchronously adjust the cable guide's attitude angle to align it spatially with the charging port. This process continues throughout the entire plug-in process, ensuring that the cable plug remains precisely aligned with the charging port, even with slight vehicle movement or environmental changes.

[0045] A flexible force control unit is integrated into the plug-in execution module. The flexible force control unit automatically adjusts the insertion force and speed by monitoring the changes in the contact force between the cable plug and the vehicle charging port in real time.

[0046] The plug-in / plug-out execution module features a flexible force control unit at the end of the robotic arm. This unit comprises a multi-axis force sensor, an elastic buffer structure, and an intelligent controller. The multi-axis force sensor, affixed to the charging gun's connection structure, collects real-time information on the force generated at the interface between the plug and the charging port during insertion, including information such as axial pressure, lateral resistance, and torsional force. An elastic buffer structure, positioned between the sensor and the robotic arm connection, possesses a certain degree of deformation and is used to absorb excessive impact forces, preventing damage to the plug or charging port due to improper insertion force control.

[0047] During the plugging and unplugging process, the force sensor feeds real-time contact force change data back to the intelligent controller. The controller, based on the preset safe plugging force range, determines whether the current insertion force is excessive or insufficient. Based on this determination, it dynamically adjusts the servo motor's output parameters, thereby controlling the thrust and speed of the insertion process. If an abnormal increase in resistance is detected, such as due to plug misalignment or insertion angle deviation, the system automatically slows down or pauses the insertion action, issuing an adjustment command to correct the posture angle, and then resuming the plugging operation after the parameters return to normal. The entire process is closed-loop controlled within a millisecond period, achieving smooth, safe, and adaptive adjustment of the plugging action.

[0048] The information collection module also includes a lidar unit and a three-dimensional imaging module. The lidar is used to build a high-precision point cloud model of the vehicle's surroundings, and the three-dimensional imaging module is used to assist in identifying the vehicle's posture and spatial obstacles.

[0049] The information acquisition module enhances vehicle environment perception accuracy and spatial modeling capabilities by adding a LiDAR unit and a 3D imaging module. The LiDAR unit is fixedly mounted on the front upper portion or on either side of the charging station. It features a 360-degree rotating scanning function, enabling a full scan of the surrounding environment after a vehicle enters, collecting data on the time delay and intensity of reflected laser light. The system converts this data into a spatial point cloud, constructing a 3D environmental model between the vehicle and the charging station, accurately locating the vehicle's relative position, boundary contours, and distance to the ground and obstacles.

[0050] The 3D imaging module, using structured light or time-of-flight sensing technology, captures stereo images of the vehicle from multiple angles, assisting in identifying the vehicle's posture, including pitch and roll angles, as well as its specific orientation in space. The module also identifies obstacles in the surrounding environment, such as other vehicles, pedestrians, and protruding objects. Based on these identification results, the system performs path planning and posture corrections, ensuring safety and unobstructed access to the subsequent charging area.

[0051] The lidar point cloud data and three-dimensional imaging image data are aligned and comprehensively analyzed through a fusion algorithm, and a complete environmental data package containing spatial position, attitude angle and obstacle distribution is output and transmitted to the control center, providing a high-precision decision-making basis for subsequent height calculation, attitude adjustment and insertion and removal path planning.

[0052] It also includes a user identity recognition and preference learning module, which is used to identify user identities through face recognition, license plate recognition or mobile terminal authentication, and combines user charging behavior habits, parking location history records and personalized needs.

[0053] The user identification and preference learning module consists of an identification unit, a data analysis unit, and a personalized configuration interface. The system automatically initiates the identification process when a vehicle approaches a charging station. It first uses a camera mounted on the charging station to capture the driver's facial image and matches it against a local or cloud-based facial database. If facial recognition fails or is unavailable, the system uses the front-end camera to read the license plate information and confirms a match with the user's vehicle registration database. Furthermore, the system supports automatic identity authentication via Bluetooth or NFC near-field communication technology on mobile terminals, identifying the user's device ID and establishing an encrypted connection to complete login.

[0054] After completing identity recognition, the data analysis unit extracts the user's charging behavior habits from historical data, including common charging time periods, average charging time, preferred parking location (such as left or right), and charging port location records for specific models. The system optimizes the current charging strategy based on this preference information, such as adjusting the position and posture of the cable guide mechanism in advance to shorten alignment time; or automatically selecting the user's commonly used charging mode (such as fast charging, energy-saving charging, etc.). If the user has special preferences (such as avoiding cable contact with the car paint, preferring far-end parking spaces), the system will also record them and adapt them during subsequent charging.

[0055] All preference information can be customized by the user through the personalized configuration interface, including the login platform, App interface or in-vehicle interactive system, allowing users to adjust the recognition method priority, privacy policy and charging parameter preferences.

[0056] It also includes a health diagnosis and life prediction module, which establishes an equipment fatigue model by collecting key parameters such as the frequency of use of each component, temperature rise curve, mechanical impact record, cable bending radius and tension change in real time, and then predicts the life of the component and generates maintenance warnings, thereby realizing early diagnosis and life cycle management of key components.

[0057] The health diagnosis and life prediction module consists of multiple condition monitoring sensors, a data acquisition system, a fatigue modeling unit, and an early warning control system. Condition monitoring sensors are installed in key locations throughout the system, such as the electric lifting column drive, cable guide arm connection, cable retraction mechanism, robotic arm joints, and charging cable plug-in / unplug interface. Each sensor monitors the operating status of its corresponding component in real time, recording every lifting and lowering motion, plugging and unplugging, and cable bending and tension changes during extension and retraction. Furthermore, built-in temperature sensors record temperature rises in key components over extended periods of operation, and vibration sensors capture mechanical shock events to analyze the impact of abnormal operation or sudden shock on equipment life.

[0058] The system's data acquisition module periodically integrates these parameters and transmits them to the fatigue modeling unit for analysis. Based on material fatigue theory, this unit combines the component's historical workload, environmental conditions, and manufacturing parameters to construct a life degradation model for each component. The model parameters are continuously updated to reflect the equipment's current operating status. The model outputs a current health score and an estimated remaining useful life, which are then compared against the system's preset safe life threshold.

[0059] Once the monitoring results show that a component is approaching its fatigue limit or the lower limit of its lifespan, the early warning control system will automatically trigger a maintenance reminder and send a maintenance alert message through the human-machine interface, platform notification, or mobile terminal. At the same time, the system can generate a maintenance plan, indicating the parts that need to be replaced or maintained, the estimated time required, and the operating instructions, to assist operation and maintenance personnel in precise operation and maintenance management.

[0060] It also includes a self-learning intelligent control module, which continuously optimizes the plug-in and unplugging paths, cable release speed and lifting logic based on a reinforcement learning algorithm. It can self-adjust parameters according to operational feedback and error data during long-term use, thereby dynamically improving plug-in and unplugging efficiency and system response performance.

[0061] The self-learning intelligent control module consists of a policy learning engine, a state feedback acquisition unit, and an action execution interface. During each charging operation, the system first collects current environmental and operational data, including vehicle position, posture parameters, cable tension, cable guide mechanism height, robotic arm insertion and removal trajectory, and final insertion success rate. The state feedback acquisition unit normalizes these parameters and then feeds them into the policy learning engine as the current "state" input.

[0062] The policy learning engine uses reinforcement learning algorithms (such as deep Q-networks and proximal policy optimization) to make action decisions and update policies. During each operation, the system selects control parameters such as lift adjustment, cable release speed, and insertion / removal path based on the current state. It also records the results of the operation, including insertion time, alignment accuracy, success, and any collisions or unusual delays. Based on this feedback, it calculates a "reward value" to evaluate the effectiveness of the control strategy for that round. The system then uses this reward signal to iteratively update the policy model.

[0063] Through continuous trial and error and accumulated experience, the self-learning module automatically adjusts system control parameters, achieving adaptive control optimization for different vehicle types, parking postures, and environmental conditions. As the number of operations increases, the system's plugging and unplugging paths become more precise, the lifting and lowering logic becomes more efficient, and the cable release action becomes smoother, significantly improving overall operational efficiency and response speed.

[0064] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A lifting cable guide and electric retractable integrated charging pile system, characterized in that: The system comprises: Information collection module, used to collect vehicle plug-in status and charging port location information; A height calculation module is used to calculate the optimal lifting height of the cable guide mechanism based on the vehicle plug-in status and charging port position information; A lifting control module is used to control the cable guide mechanism to adjust the lifting height according to the optimal lifting height; The plugging and unplugging execution module is used to perform automatic alignment and plugging and unplugging operations of cables.

2. The charging pile system with integrated lifting cable guidance and electric retraction according to claim 1 is characterized in that: The information collection module includes multiple visual sensors or infrared sensors installed on the charging pile body and the ground within a preset range, which are used to obtain the vehicle parking posture, body outline and three-dimensional spatial coordinates of the charging port in real time.

3. The charging pile system with integrated lifting cable guidance and electric retraction according to claim 1, characterized in that: The height calculation module integrates the vehicle connection status, vehicle type database and historical connection trajectory data, and uses a posture estimation algorithm based on deep learning to calculate the optimal lifting height of the cable guide mechanism, thereby improving the adaptability and accuracy of the lifting control.

4. The charging pile system with integrated lifting cable guidance and electric retraction according to claim 1, characterized in that: The lifting control module and a group of multi-stage electric lifting columns form a closed-loop control structure. The electric lifting columns have displacement feedback capabilities and can dynamically correct the target height based on a real-time height adjustment strategy during the lifting process.

5. The lifting cable guide and electric retractable integrated charging pile system according to claim 1 is characterized in that: It also includes a posture stabilization module, which is used to dynamically adjust the tilt posture of the cable guide mechanism according to environmental parameters such as the tilt angle of the vehicle charging port, the tire compression status and the ground slope, so as to ensure that the cable plug always maintains an angle aligned with the charging port.

6. The charging pile system with integrated lifting cable guidance and electric retraction according to claim 1, characterized in that: The plug-in execution module is integrated with a flexible force control unit, which automatically adjusts the insertion force and insertion speed by monitoring the contact force changes between the cable plug and the vehicle charging port in real time.

7. The charging pile system with integrated lifting cable guidance and electric retraction according to claim 1, characterized in that: The information acquisition module also includes a laser radar unit and a three-dimensional imaging module. The laser radar is used to construct a high-precision point cloud model of the vehicle's surroundings, and the three-dimensional imaging module is used to assist in identifying the vehicle body posture and spatial obstacles.

8. The lifting cable guide and electric retractable integrated charging pile system according to claim 1, characterized in that: It also includes a user identity recognition and preference learning module, which is used to identify user identities through face recognition, license plate recognition or mobile terminal authentication, and combines user charging behavior habits, parking location history records and personalized needs.

9. The lifting cable guide and electric retractable integrated charging pile system according to claim 1, characterized in that: It also includes a health diagnosis and life prediction module, which establishes an equipment fatigue model by collecting key parameters such as the frequency of use of each component, temperature rise curve, mechanical impact record, cable bending radius and tension change in real time, and then predicts the life of the component and generates maintenance warnings, thereby realizing early diagnosis and life cycle management of key components.

10. The lifting cable guide and electric retractable integrated charging pile system according to claim 1, characterized in that: It also includes a self-learning intelligent control module, which continuously optimizes the plug-in and unplugging paths, cable release speed and lifting logic based on a reinforcement learning algorithm. It can self-adjust parameters according to operational feedback and error data during long-term use, thereby dynamically improving plug-in and unplugging efficiency and system response performance.

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