Combined mobile photovoltaic energy storage device and control method thereof

Abstract

The invention discloses a combined mobile photovoltaic energy storage device and a control method thereof, and belongs to the technical field of photovoltaic energy storage devices. The combined mobile photovoltaic energy storage device comprises a mobile base and an energy storage battery pack; the reel type photovoltaic array comprises a plurality of photovoltaic module units and a plurality of intelligent hinges connected with the photovoltaic module units; deploying a driving mechanism; the sensor group comprises an inertial measurement unit and a sensor; and the central control system is arranged in the movable base, and the central control system is connected with and controls the deployment driving mechanism, the energy storage battery pack and the sensor group to work. By means of the internal structure of the intelligent hinge, the high-precision strain gauge, the integrated data interface and the piezoelectric ceramic sensor are integrated in the intelligent hinge, the system can distinguish different types of potential risks such as normal stress but fatigue cracks exist in the intelligent hinge or stress concentration exists in the intelligent hinge due to intact materials, the accuracy of fault early warning is greatly improved, and the fault early warning efficiency is improved. And the technical transition from passive connection to active sensing is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic energy storage devices, and in particular to a combined mobile photovoltaic energy storage device and a control method thereof. Background Art

[0002] Mobile photovoltaic energy storage devices, particularly modular or modular designs, have widespread applications in emergency response, military frontier operations, field exploration, and temporary facility power supply. The core advantages of these devices lie in their portability and rapid deployment. Existing mobile photovoltaic devices typically focus on improving photoelectric conversion efficiency, energy storage density, and lightweight and compact mechanical structures.

[0003] Existing technologies present a significant pain point: such devices require frequent transportation, deployment, and retraction during use. Road bumps, impact vibrations, and repeated mechanical deployment and folding during transportation can cause cumulative micro-damage to the device's connection structure, locking mechanism, and the flatness of the photovoltaic array. These damages are difficult to detect through visual inspection in the early stages, but they gradually accumulate and may eventually lead to sudden mechanical failures (for example, the deployment mechanism becomes stuck or malfunctions), or prevent the photovoltaic array from fully unfolding, affecting power generation efficiency and system stability.

[0004] Health assessments for these devices rely primarily on regular offline inspections or repairs after a significant failure. There is a lack of technology that can conduct real-time, non-destructive, automated assessments on-site, before deployment, or during deployment. This poses a significant risk to device reliability in critical applications, such as disaster relief. Therefore, the market urgently needs intelligent mobile photovoltaic energy storage devices that can self-diagnose structural health, predict deployment reliability, and assess performance degradation.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] The object of the present invention is to provide a combined mobile photovoltaic energy storage device and a control method thereof to solve the problems raised in the above background technology.

[0007] The technical solution of the present invention is: a combined mobile photovoltaic energy storage device, comprising:

[0008] a mobile base including an energy storage battery pack;

[0009] A roll-up photovoltaic array is stored in the mobile base, wherein the roll-up photovoltaic array includes a plurality of photovoltaic module units and a plurality of smart hinges connecting the photovoltaic module units;

[0010] A deployment drive mechanism, disposed in the mobile base, for driving the deployment and retraction of the roll-up photovoltaic array;

[0011] a sensor group, comprising an inertial measurement unit disposed on the mobile base and a sensor integrated into each of the smart hinges;

[0012] A central control system is provided in the mobile base, and the central control system is connected to control the operation of the deployment drive mechanism, the energy storage battery pack and the sensor group;

[0013] Wherein, each of the smart hinges comprises:

[0014] A high-precision strain gauge for sensing the stress and deformation of the smart hinge;

[0015] a piezoelectric ceramic sensor, configured to transmit and receive acoustic wave signals penetrating the smart hinge structure;

[0016] An integrated data interface is used to connect the signals obtained by the high-precision strain gauge and the piezoelectric ceramic sensor to the central control system.

[0017] In this embodiment, the piezoelectric ceramic sensor includes a first piezoelectric ceramic piece serving as an acoustic wave transmitting source and a second piezoelectric ceramic piece serving as an acoustic wave receiver.

[0018] In this embodiment, the deployment drive mechanism includes a drive motor and a transmission assembly;

[0019] Wherein, the deployment drive mechanism is mechanically connected to the drive shaft of the roll-type photovoltaic array.

[0020] In this embodiment, the central control system has a built-in multi-physical quantity coupling analysis and health assessment software model;

[0021] The software model includes a baseline fingerprint library, a real-time feature extractor and a coupling analysis engine.

[0022] In this embodiment, the baseline fingerprint library stores data flow templates of the sensor group during a complete deployment process when the device is in an ideal health state.

[0023] A control method for a combined mobile photovoltaic energy storage device, comprising:

[0024] S1. Controlling the inertial measurement unit to monitor and record shock and vibration data of the device during transportation;

[0025] S2. After receiving the deployment instruction, controlling the deployment drive mechanism to unfold the roll-up photovoltaic array at a preset diagnostic speed;

[0026] S3. During the deployment process, synchronously collect torque data from the deployment drive mechanism, stress data from the high-precision strain gauge in each smart hinge, and acoustic response data from the piezoelectric ceramic sensor in each smart hinge;

[0027] S4, controlling the central control system to compare and analyze the multi-source data collected in real time with a preset health baseline model;

[0028] S5. Generating a structural health and deployment reliability index and an expected power generation efficiency degradation rate based on the results of the comparison analysis;

[0029] S6. Based on the structural health and deployment reliability index, control the deployment drive mechanism to complete subsequent actions.

[0030] In this embodiment, in the step S3, when the roll-up photovoltaic array is unfolded to a preset angle position, the piezoelectric ceramic sensor is triggered to perform active acoustic detection and record acoustic response data.

[0031] In this embodiment, in step S4, the central control system integrates the shock and vibration data recorded during the transportation process as a priori conditions for analysis.

[0032] In this embodiment, the step S6 includes:

[0033] If the structural health and deployment reliability index is higher than a preset safety threshold, controlling the deployment drive mechanism to complete full deployment at a normal speed;

[0034] If the structural health and deployment reliability index is lower than the preset safety threshold, deployment is aborted and an alert is issued to the operator.

[0035] The present invention provides a combined mobile photovoltaic energy storage device and a control method thereof through improvements, which have the following improvements and advantages compared with the prior art:

[0036] The present invention integrates a high-precision strain gauge, an integrated data interface, and a piezoelectric ceramic sensor within the internal structure of the smart hinge. The high-precision strain gauge is used to convert any tiny tensile or compressive deformation when the hinge is unfolded, locked, or subjected to external loads such as wind loads into a measurable electrical signal, thereby accurately quantifying the real-time stress (force) at the connection point.

[0037] The function of the piezoelectric ceramic sensor is to actively transmit high-frequency sound wave pulses and receive echo signals after penetrating the structure under the command of the central control system. By analyzing the attenuation and phase changes of the signal, it can detect whether there are micro defects (sound) such as micro cracks, fatigue or connection gaps inside the material.

[0038] By coupling the measurement of two different dimensions of physical quantities, force and sound, at a single structural node, a comprehensive portrait of the structural health is achieved; stress measurement reflects the macroscopic load distribution, while acoustic detection reveals the integrity of the microscopic material; the direct technical consequence of this is that the system can distinguish different types of potential risks, such as normal stress but internal fatigue cracks or intact materials but with stress concentration, greatly improving the accuracy of fault warning and achieving a technological leap from passive connection to active perception. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention will be further explained below in conjunction with the accompanying drawings and Examples:

[0040] Figure 1 is a schematic diagram of the combined mobile photovoltaic energy storage device of the present invention;

[0041] Figure 2 It is a side view of the combined mobile photovoltaic energy storage device of the present invention;

[0042] Figure 3 It is a structural schematic diagram of the scroll-type photovoltaic array of the present invention;

[0043] Figure 4 It is a schematic diagram of the control method of the combined mobile photovoltaic energy storage device of the present invention.

[0044] Description of reference numerals:

[0045] 1. Mobile base; 2. Roll-up photovoltaic array; 3. Smart hinge; 4. Photovoltaic module unit; 5. Energy storage battery pack; 6. Deployment drive mechanism. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0047] Example 1:

[0048] See also Figure 1 The present invention provides a combined mobile photovoltaic energy storage device and a control method thereof: A combined mobile photovoltaic energy storage device, comprising:

[0049] A mobile base 1 including an energy storage battery pack 5;

[0050] A roll-up photovoltaic array 2 is housed in the mobile base 1 , wherein the roll-up photovoltaic array 2 includes a plurality of photovoltaic module units 4 and a plurality of smart hinges 3 connecting the photovoltaic module units 4 ;

[0051] A deployment drive mechanism 6 is provided in the mobile base 1 and is used to drive the deployment and retraction of the roll-up photovoltaic array 2;

[0052] A sensor group, including an inertial measurement unit provided on the mobile base 1 and a sensor integrated into each of the smart hinges 3;

[0053] A central control system is provided in the mobile base 1, and the central control system is connected to control the operation of the deployment drive mechanism 6, the energy storage battery group 5 and the sensor group;

[0054] Wherein, each of the smart hinges 3 includes:

[0055] A high-precision strain gauge, used to sense the stress and deformation of the smart hinge 3;

[0056] a piezoelectric ceramic sensor, configured to transmit and receive acoustic wave signals penetrating the structure of the smart hinge 3;

[0057] An integrated data interface is used to connect the signals obtained by the high-precision strain gauge and the piezoelectric ceramic sensor to the central control system.

[0058] To address the technical pain point of existing mobile photovoltaic devices, which have the potential for sudden failures due to accumulated minor damage after frequent transportation and deployment, this embodiment provides a combined mobile photovoltaic energy storage device.

[0059] The overall architecture of the device of the present invention is based on a mobile base 1 that serves as a supporting platform. It houses not only an energy storage battery pack 5 but also an integrated central control system, which serves as the brain of the system. The rollable photovoltaic array 2 is compactly housed within the base when stored. The array is composed of multiple rigid photovoltaic module units 4. The key to its roll-up is the flexible connection between the modules using specialized intelligent hinges 3. A deployment drive mechanism 6 is also installed within the base and, through connection to the photovoltaic array's drive shaft, provides controllable power for the array's deployment and retraction.

[0060] A core technical concept of this solution is to upgrade the originally passive mechanical connection structure into an active information perception node. To this end, a sensor group is set up in the device, which includes both macro and micro levels: at the macro level, an inertial measurement unit (IMU) is set on the mobile base 1 to monitor the vibration and impact status of the entire device during transportation; at the micro level, precise sensors are integrated inside each smart hinge 3.

[0061] A key technical detail lies in the internal structure of the smart hinge 3; it is no longer a purely mechanical component, but an integrated acoustic-mechanical-electrical sensing unit. It integrates:

[0062] High-precision strain gauges are precisely mounted on key stress paths within the hinge. When the hinge is deployed, locked, or subjected to external loads such as wind, any tiny tensile or compressive deformation is converted into a measurable electrical signal by the strain gauge, thereby accurately quantifying the real-time stress (force) at the connection point.

[0063] Piezoelectric ceramic sensors are encapsulated inside the hinge structure, such as near its locking mechanism. Under the command of the central control system, they actively transmit high-frequency acoustic pulses and receive echo signals after penetrating the structure. By analyzing changes in signal attenuation and phase, they detect microscopic defects (acoustics) such as microcracks, fatigue, or connection gaps within the material.

[0064] Integrated data interface: responsible for processing and digitizing the analog signals collected by the above two sensors, and establishing a reliable data connection with the central control system through the internal bus;

[0065] The ingenuity of this design lies in that by coupling the measurement of two different dimensions of physical quantities, force and sound, at a single structural node, a comprehensive portrait of the structural health is achieved; stress measurement reflects the macroscopic load distribution, while acoustic detection reveals the integrity of the microscopic material; the direct technical consequence of this is that the system can distinguish between different types of potential risks, such as normal stress but existing fatigue cracks or intact materials but with stress concentration, greatly improving the accuracy of fault warning and achieving a technological leap from passive connection to active perception.

[0066] In this embodiment, the piezoelectric ceramic sensor includes a first piezoelectric ceramic piece serving as an acoustic wave transmitting source and a second piezoelectric ceramic piece serving as an acoustic wave receiver.

[0067] In a preferred embodiment, in order to optimize the acoustic detection function, the piezoelectric ceramic sensor is designed to include two functionally separated parts: a first piezoelectric ceramic plate as an acoustic wave transmitter and a second piezoelectric ceramic plate as an acoustic wave receiver;

[0068] Its inherent physical logic is that by setting up independent transmitters and receivers, a clear, stable and predictable sound wave propagation path can be constructed; when the central controller excites the first piezoelectric ceramic plate, it generates a standardized acoustic detection pulse; after the pulse passes through the key structure of the hinge (such as the locking meshing interface), it is received by the second piezoelectric ceramic plate; this one-transmitter and one-receiver configuration can more accurately measure the transit time and signal attenuation amplitude of the sound wave compared to the single-piece self-transmitting and self-receiving mode; the direct technical consequence of this move is that it can more sensitively identify changes in acoustic impedance caused by defects such as microcracks, material fatigue or loose connections, thereby significantly improving the signal-to-noise ratio and reliability of micro-defect detection.

[0069] In this embodiment, the deployment drive mechanism 6 includes a drive motor and a transmission assembly;

[0070] The deployment drive mechanism 6 is mechanically connected to the drive shaft of the roll-type photovoltaic array 2 .

[0071] In this embodiment, the deployment drive mechanism 6 is specifically composed of a drive motor and a transmission assembly. In order to achieve this function, a necessary structural requirement is that the output end of the mechanism forms a reliable mechanical connection with the drive shaft of the scroll-type photovoltaic array 2.

[0072] The purpose of this design is not only to provide basic power for the deployment and retraction of the photovoltaic array, but also to integrate it into the closed-loop health assessment of the entire system. The drive motor (usually a servo motor or a stepper motor) is equipped with an encoder that can accurately feedback its rotation angle and output torque. During the deployment process, if one or a group of smart hinges 3 become stuck or deform, it will inevitably cause the resistance of the entire photovoltaic array to deploy to change. This change will be immediately and directly reflected in the torque output of the drive motor. Therefore, by real-time monitoring of the drive motor's torque data, the central control system obtains a third dimension of information source in addition to the hinge sensor, realizing macro-monitoring of the entire transmission chain and load status, and further enhancing the cross-validation capability of fault diagnosis.

[0073] In this embodiment, the central control system has a built-in multi-physical quantity coupling analysis and health assessment software model;

[0074] The software model includes a baseline fingerprint library, a real-time feature extractor and a coupling analysis engine.

[0075] In this embodiment, the baseline fingerprint library stores data flow templates of the sensor group during a complete deployment process when the device is in an ideal health state.

[0076] The solution's innovative supporting structure, also the core of intelligent diagnosis, is a multi-physics coupling analysis and health assessment software model embedded within the central control system. This software model serves as the brain of the entire intelligent system, transforming the massive, multi-source, and heterogeneous raw data collected by front-end sensors into holistic, forward-looking insights into the health status of the entire device.

[0077] The software model is mainly composed of three functional modules in structure:

[0078] Baseline fingerprint library: This module serves as the benchmark for all comparative analysis. Rather than a simple set of thresholds, this fingerprint library stores a continuous data stream template of all sensors (including the IMU, strain and acoustic data from all smart hinges, and drive motor torque and angle data) in the device's ideal health state at the factory, from startup and deployment to full expansion and locking. This is a high-dimensional, dynamic health fingerprint that accurately depicts the expected performance of a healthy device at every stage.

[0079] Real-time feature extractor: This module is responsible for applying signal processing algorithms (such as Fourier transform and wavelet analysis) to extract key features that best reflect state changes from the real-time collected raw data stream, such as the vibration energy spectrum, the slope and peak value of the stress curve, and the attenuation coefficient of the acoustic signal, providing high-quality input for subsequent analysis.

[0080] Coupled analysis engine: As the core of the model, this engine typically uses a machine learning algorithm (such as a recurrent neural network (RNN) or an ensemble learning model) to receive multiple feature data streams from the feature extractor and sample data from the baseline fingerprint library.

[0081] The subtlety of its working principle lies in that it does not make isolated threshold judgments on single sensor data, but rather deeply analyzes the dynamic correlation and cross-validation between multiple physical quantities; by performing morphological comparisons between real-time data and health fingerprints, the model can discover systemic risk signs caused by multiple factors that are difficult to detect with a single measurement, thereby realizing the transformation from data to information and then to decision support, greatly improving the accuracy of diagnosis and the ability of predictive maintenance.

[0082] Example 2

[0083] like Figure 4 As shown, a control method for a combined mobile photovoltaic energy storage device includes:

[0084] S1. Controlling the inertial measurement unit to monitor and record shock and vibration data of the device during transportation;

[0085] S2, after receiving the deployment instruction, controlling the deployment drive mechanism 6 to unfold the roll-up photovoltaic array 2 at a preset diagnostic speed;

[0086] S3. During the deployment process, synchronously collect torque data from the deployment drive mechanism 6, stress data from the high-precision strain gauge in each smart hinge 3, and acoustic response data from the piezoelectric ceramic sensor in each smart hinge 3;

[0087] S4, controlling the central control system to compare and analyze the multi-source data collected in real time with a preset health baseline model;

[0088] S5. Generating a structural health and deployment reliability index and an expected power generation efficiency degradation rate based on the results of the comparison analysis;

[0089] S6. Based on the structural health and deployment reliability index, control the deployment drive mechanism 6 to complete subsequent actions.

[0090] This embodiment discloses a control method for the aforementioned device, which transforms the device's hardware capabilities into an executable, closed-loop health assessment and decision-making process. This method is particularly suitable for scenarios such as emergency rescue and field exploration where equipment reliability is extremely important.

[0091] The inherent logic of the entire control process is to conduct a comprehensive dynamic physical examination of the device during the deployment process before it is officially put into use.

[0092] The process begins at S1: Transport Monitoring. During this phase, the device's inertial measurement unit (IMU) is activated, continuously recording the shock and vibration loads experienced throughout the entire transport process. These are quantified by the system into a transport stress history report.

[0093] When the device arrives at the site and the operator issues a deployment command, the process enters S2: diagnostic deployment phase. The system does not immediately deploy at full speed, but instead activates the deployment drive mechanism 6 at a slower, standardized, preset diagnostic speed. This is done to collect data under controllable and repeatable conditions, eliminating the interference of speed variations on the measurement results.

[0094] Key data collection occurs at S3. During the slow deployment process, the central control system simultaneously captures information streams from three different dimensions with millisecond-level accuracy: real-time torque data from the drive motor, microstress data from each smart hinge 3, and acoustic response data from each smart hinge 3. This is a multi-source data synchronization process.

[0095] Subsequently, in S4, these real-time data streams are fed into the aforementioned health assessment software model; the coupled analysis engine compares these data with the health samples in the baseline fingerprint library in real time, calculating deviations and anomalies;

[0096] The results of the analysis are converted into intuitive and understandable outputs for users in S5. The system generates two core indicators: the structural health and deployment reliability index, a percentage used to quantify the risk of deployment failure; and the expected power generation efficiency degradation rate, which is used to predict the potential loss of power generation due to structural deformation.

[0097] Finally, in S6, the system makes autonomous decisions based on these indices; this is an automated decision loop that directly links abstract health assessments to device actions.

[0098] In this embodiment, in step S3, when the roll-up photovoltaic array 2 is unfolded to a preset angle position, the piezoelectric ceramic sensor is triggered to perform active acoustic detection and record acoustic response data.

[0099] In this embodiment, in step S4, the central control system integrates the shock and vibration data recorded during the transportation process as a priori conditions for analysis.

[0100] In this embodiment, the step S6 includes:

[0101] If the structural health and deployment reliability index is higher than a preset safety threshold, the deployment drive mechanism 6 is controlled to complete full deployment at a normal speed;

[0102] If the structural health and deployment reliability index is lower than the preset safety threshold, deployment is aborted and an alert is issued to the operator.

[0103] In order to further improve the accuracy and practicality of the control method, this embodiment refines and defines several key steps.

[0104] A key optimization of the S3 data acquisition step is that, instead of performing continuous acoustic detection, detection is triggered when the photovoltaic array is deployed to a set of preset angular positions (such as 10%, 30%, 60%, 90% and 100% locked positions); its technical purpose is to ensure that the stress state and geometric shape of the structure are most representative and comparable at a specific deployment angle; taking measurements at these key nodes can not only reduce data redundancy, but more importantly, it can compare current data with historical data under exactly the same structural posture, greatly improving the accuracy and repeatability of acoustic diagnosis.

[0105] An important advancement in the S4 analysis step is that it requires the central control system to integrate the shock and vibration data recorded during transportation as a priori conditions for analysis when conducting comparative analysis. The direct technical consequence of this is that the evaluation model is no longer a static comparator, but an intelligent analysis system with memory and experience. For example, for a historical stress report on a transportation that experienced severe turbulence, the model will automatically increase the sensitivity weight to minor anomalies. This historical and current correlation analysis enables the system to discover early damage that may be overlooked under normal transportation conditions.

[0106] The refinement of the S6 decision-making step ensures that the entire method can be implemented and generate practical value. This step introduces the concept of a preset safety threshold (for example, in an emergency rescue scenario, this threshold can be set at 70%). This threshold is set based on risk assessment and the criticality of the application scenario. It is not an arbitrary setting, but rather a balance between ensuring basic equipment safety and mission success rate. The decision-making logic is clearly defined as follows:

[0107] If the calculated structural health and deployment reliability index is higher than this threshold, the system determines that the equipment is in good condition and the risk is controllable, and then automatically switches to normal speed to complete the deployment and enter the working mode;

[0108] On the contrary, if the index is lower than the threshold, the system will immediately terminate the deployment process and send a specific warning message to the operator (for example, indicating which hinge has potential risks);

[0109] This move transforms complex diagnostic results into a clear, black-and-white execution instruction, avoiding the need for operators to make complex judgments in emergency situations, and implementing the concept of predictive maintenance into automated, reliable protective actions, thereby fundamentally improving the availability and safety of the device in harsh environments.

[0110] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A combined mobile photovoltaic energy storage device, characterized in that: include: a mobile base including an energy storage battery pack; A roll-up photovoltaic array is stored in the mobile base, wherein the roll-up photovoltaic array includes a plurality of photovoltaic module units and a plurality of smart hinges connecting the photovoltaic module units; A deployment drive mechanism, disposed in the mobile base, for driving the deployment and retraction of the roll-up photovoltaic array; a sensor group, comprising an inertial measurement unit disposed on the mobile base and a sensor integrated into each of the smart hinges; A central control system is provided in the mobile base, and the central control system is connected to control the operation of the deployment drive mechanism, the energy storage battery pack and the sensor group; Wherein, each of the smart hinges comprises: A high-precision strain gauge for sensing the stress and deformation of the smart hinge; a piezoelectric ceramic sensor, configured to transmit and receive acoustic wave signals penetrating the smart hinge structure; An integrated data interface is used to connect the signals obtained by the high-precision strain gauge and the piezoelectric ceramic sensor to the central control system.

2. The combined mobile photovoltaic energy storage device according to claim 1, characterized in that: The piezoelectric ceramic sensor includes a first piezoelectric ceramic piece as an acoustic wave transmitting source and a second piezoelectric ceramic piece as an acoustic wave receiver.

3. The combined mobile photovoltaic energy storage device according to claim 1, characterized in that: The deployment drive mechanism includes a drive motor and a transmission assembly; Wherein, the deployment drive mechanism is mechanically connected to the drive shaft of the roll-type photovoltaic array.

4. The combined mobile photovoltaic energy storage device according to claim 1, characterized in that: The central control system has a built-in multi-physical quantity coupling analysis and health assessment software model; The software model includes a baseline fingerprint library, a real-time feature extractor and a coupling analysis engine.

5. The combined mobile photovoltaic energy storage device according to claim 4, characterized in that: The baseline fingerprint library stores data flow templates of the sensor group during a complete deployment process when the device is in an ideal health state.

6. A control method for a combined mobile photovoltaic energy storage device, applied to the combined mobile photovoltaic energy storage device according to any one of claims 1 to 5, characterized in that: include: S1. Controlling the inertial measurement unit to monitor and record shock and vibration data of the device during transportation; S2. After receiving the deployment instruction, controlling the deployment drive mechanism to unfold the roll-up photovoltaic array at a preset diagnostic speed; S3. During the deployment process, synchronously collect torque data from the deployment drive mechanism, stress data from the high-precision strain gauge in each smart hinge, and acoustic response data from the piezoelectric ceramic sensor in each smart hinge; S4, controlling the central control system to compare and analyze the multi-source data collected in real time with a preset health baseline model; S5. Generating a structural health and deployment reliability index and an expected power generation efficiency degradation rate based on the results of the comparison analysis; S6. Based on the structural health and deployment reliability index, control the deployment drive mechanism to complete subsequent actions.

7. The control method according to claim 6, characterized in that: In the step S3, when the roll-up photovoltaic array is unfolded to a preset angle position, the piezoelectric ceramic sensor is triggered to perform active acoustic detection and record acoustic response data.

8. The control method according to claim 6, characterized in that: In step S4, the central control system integrates the shock and vibration data recorded during the transportation process as a priori conditions for analysis.

9. The control method according to claim 6, characterized in that: The steps of S6 include: If the structural health and deployment reliability index is higher than a preset safety threshold, controlling the deployment drive mechanism to complete full deployment at a normal speed; If the structural health and deployment reliability index is lower than the preset safety threshold, deployment is aborted and an alert is issued to the operator.

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