Unmanned aerial vehicle nest integration system and method based on an engineering vehicle

Abstract

The application discloses an unmanned aerial vehicle nest integration system and method based on an engineering vehicle, which comprises a mechanical coupling module, an electrical coupling module, an environmental coupling module and a cooperative controller. The cooperative controller monitors the states of the modules, and synchronously adjusts other modules when the state of any module changes, thereby forming a cross-module cooperative control closed loop. An electrical control cooperative unit predicts voltage fluctuation according to electrical parameters of a vehicle-mounted power supply and a vehicle running state, triggers the electrical coupling module to switch the working mode, and realizes uninterrupted power supply. A machine control cooperative unit performs frequency spectrum analysis on vibration parameters, adjusts the locking force of the mechanical coupling module in combination with the locking state, and realizes active anti-vibration. An environmental control cooperative unit collects environmental parameters at multiple points in the cabin, reconstructs the temperature field distribution, and outputs a partition adjustment signal to realize precise temperature control. The application solves the cooperative operation problem of the vehicle-nest-machine under voltage fluctuation, random vibration and severe environment through the three cooperative closed loops, and improves the system reliability and environmental adaptability.

Description

Technical Field

[0001] This invention relates to the field of mobile robot deployment and vehicle integration technology, specifically to an unmanned aerial vehicle (UAV) nesting integration system and method based on engineering vehicles. Background Technology

[0002] With the widespread application of drone technology in fields such as inspection, surveying, and emergency response, its operation mode is evolving from single aircraft to systematic deployment. However, in engineering operation scenarios with high mobility and complex environments, such as communication base station inspection, power line repair, and pipeline inspection, traditional drone deployment methods are difficult to meet actual needs.

[0003] Existing vehicle-mounted drone deployment solutions mainly suffer from the following problems: Fixed drone nests are limited by mains power and network infrastructure, cannot cover linear engineering and distributed fault points, and have high construction and maintenance costs; Simple vehicle-mounted brackets only provide mechanical storage functions, lack shock absorption design and environmental protection, and the vibration of the vehicle during driving is directly transmitted to the precision components of the drone, resulting in a sharp reduction in equipment lifespan. At the same time, they cannot provide charging support for the drone, and the operation still requires manual intervention; Manual handling and deployment methods are highly dependent on professional pilots, and the process from parking to takeoff is cumbersome and time-consuming, making it difficult to meet the timeliness requirements of emergency response. Moreover, it is difficult to operate under adverse weather conditions and poses personnel safety risks.

[0004] In summary, existing technical solutions face four core technical challenges: First, power interruption. Engineering vehicle platforms typically operate on a 24V system, experiencing severe voltage fluctuations during engine start-up and sudden load changes. Existing simple voltage converters cannot handle wide-range fluctuations and transient impacts, leading to low charging efficiency and battery damage. Second, mechanical instability. The high-intensity random vibrations generated when engineering vehicles travel on unpaved roads far exceed the tolerance range of the precision components of drones. The lack of professional shock absorption and dynamic locking designs results in a high early failure rate and easy loosening of the locking mechanism. Third, inefficient deployment. The time from vehicle coming to a stop to drone takeoff relies on manual operation, which is time-consuming and fails to meet the "golden time" requirement for emergency operations. Fourth, poor environmental adaptability. Existing solutions lack effective sealing protection and temperature and humidity regulation capabilities, making it difficult to operate stably in harsh environments such as rain, snow, sandstorms, and extreme temperatures, limiting the application scenarios and operational windows of drones. These intertwined challenges restrict the reliable application of vehicle-mounted drone systems in complex engineering scenarios. Summary of the Invention

[0005] This invention aims to overcome the aforementioned shortcomings and provide an integrated system and method for unmanned aerial vehicle (UAV) nesting based on engineering vehicles. Its core lies in constructing three closed loops: electric-control collaboration, machine-control collaboration, and environmental-control collaboration, thereby achieving deep integration and adaptive collaboration among the vehicle, nesting system, and UAV.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an unmanned aerial vehicle (UAV) nesting integration system based on an engineering vehicle, comprising: The mechanical coupling module, installed on the engineering vehicle, is used to achieve mechanical connection and dynamic isolation between the drone nest and the engineering vehicle; The electrical coupling module is electrically connected to the on-board power supply of the engineering vehicle and is used to convert the on-board power supply into the working power required by the drone nest. An environmental coupling module, installed on an engineering vehicle and containing a sealed cabin, is used to provide sealed protection and temperature and humidity regulation for the drone. The collaborative controller is communicatively connected to the mechanical coupling module, the electrical coupling module, and the environmental coupling module, respectively. The collaborative controller monitors the status of each coupled module. When the status of any coupled module changes, the collaborative controller synchronously adjusts the working status of other coupled modules to form a cross-module collaborative control closed loop.

[0007] Furthermore, the collaborative controller integrates an electrical-control collaborative unit, a machine-control collaborative unit, and an environmental-control collaborative unit, wherein: The electric-control coordination unit monitors the electrical parameters of the vehicle power supply and the operating status parameters of the engineering vehicle, generates a prediction signal for voltage fluctuation events based on the monitored electrical parameters and operating status parameters, and outputs the prediction signal to the electrical coupling module to trigger the electrical coupling module to switch its working mode. The machine-control coordination unit monitors the vibration parameters of the engineering vehicle and the locking state parameters of the mechanical coupling module, performs spectral analysis on the vibration parameters to obtain the vibration spectrum, and generates a locking force adjustment signal based on the vibration spectrum and locking state parameters. The locking force adjustment signal is then output to the mechanical coupling module to drive the mechanical coupling module to adjust the locking force. The environmental-control collaborative unit monitors the environmental parameters inside the UAV nest, collects environmental parameter values ​​at multiple locations within the sealed cabin, generates an environmental parameter distribution map based on the environmental parameter values ​​at each location, and outputs a zonal adjustment signal to the environmental coupling module based on the environmental parameter distribution map.

[0008] Furthermore, the electrical coupling module includes a main power conversion unit and a transient power buffer unit connected in parallel with the main power conversion unit; The electronic-control coordination unit monitors the vehicle's power supply voltage, voltage change rate, and engine status signals, and inputs the monitoring data into a fusion decision model to calculate the warning confidence level for voltage drop events. The warning confidence level is calculated according to the following formula: In the formula: , , For the preset weighting coefficients, and = 0.5、 = 0.3、 = 0.2; Assess the confidence level for the engine start command when an engine start message is captured. = 1.0, otherwise = 0; For the confidence level of the rate of change of voltage, and ,in Preset calibration coefficients; dV / dt represents the rate of change of voltage, that is, the derivative of voltage with respect to time, which is used to characterize the severity of voltage drop; The load change confidence level is set when the load change rate exceeds a preset threshold. Increase; When the warning confidence exceeds the first threshold or the voltage is lower than the second threshold, the electronic-control coordination unit controls the transient power buffer unit to enter the pre-synchronization state before the voltage drop event actually occurs, so that its output voltage is in the same frequency, phase and amplitude as the output voltage of the main power conversion unit. When a voltage drop event actually occurs, the electrical-control coordination unit switches the transient power buffer unit from voltage control mode to current control mode, and outputs a current command value with the goal of compensating for the power deficit of the main power conversion unit.

[0009] The electrical coupling module operates in two modes: voltage control mode and current control mode. Voltage control mode uses the output voltage as the control target and stabilizes it at a preset value through closed-loop regulation. Current control mode uses the output current as the control target and makes it track a preset current command value. During normal operation, the main power conversion unit operates in voltage control mode. When a voltage drop event occurs, the electrical-control coordination unit switches the transient power buffer unit from voltage control mode to current control mode, causing it to output compensation current according to the current command value. The pre-synchronization state refers to the state where the output voltage of the transient power buffer unit is in the same frequency, phase, and amplitude as the output voltage of the main power conversion unit. Furthermore, the transient power buffer unit includes a supercapacitor array and a bidirectional power conversion circuit. The supercapacitor array is electrically connected to one end of the bidirectional power conversion circuit, and the other end of the bidirectional power conversion circuit is connected in parallel to the output terminal of the main power conversion unit. When a voltage drop event occurs, the electronic-control coordination unit controls the bidirectional power conversion circuit to switch to current control mode, so that the supercapacitor array outputs current to the load through the bidirectional power conversion circuit; After the voltage drop event ends, the electronic-control cooperative unit controls the bidirectional power conversion circuit to charge the supercapacitor array using a multi-stage adaptive charging strategy; The multi-stage adaptive charging strategy includes: constant current pre-charging stage, constant current fast charging stage, and constant voltage trickle charging stage, wherein the charging current value of the constant current fast charging stage is dynamically adjusted according to the current load capacity of the main power conversion unit.

[0010] Furthermore, the mechanical coupling module includes: The base is fixedly installed on the engineering vehicle; A shock-absorbing device is installed on the base; The platform, mounted on the shock-absorbing device, is used to support the drone nest; At least three locking mechanisms are disposed between the platform and the base, each locking mechanism including a drive element and a force sensor; The machine-control collaborative unit collects the vibration acceleration signal of the engineering vehicle and the actual locking force signal of the locking mechanism, and performs spectrum analysis on the vibration signal to identify the dominant frequency and amplitude of the vibration; The machine-control collaborative unit inputs the identification results into the vibration-force attenuation model to calculate the feedforward compensation amount. At the same time, it calculates the deviation between the actual locking force and the target locking force and calculates the feedback compensation amount through the feedback control algorithm. Then, it drives the locking mechanism with the superposition value of the feedforward compensation amount and the feedback compensation amount to dynamically adjust the locking force.

[0011] Furthermore, the vibration-force attenuation model is as follows: in, The Laplace transform of the predicted locking force attenuation. This represents the Laplace transform of the vibration acceleration amplitude, where K is the gain coefficient. Let ζ be the system's natural frequency, ζ be the damping ratio, and s be the Laplace operator; The gain coefficient K and the system natural frequency The damping ratio ζ is pre-calibrated through bench testing. The calibration process includes: applying vibration excitation of different frequencies and amplitudes on a standard vibration table, collecting pressure attenuation data of the locking mechanism, and fitting the value of ζ through a system identification algorithm; when dynamically adjusting the locking force, the steady-state error of the locking force relative to the target locking force is controlled within 5%.

[0012] Furthermore, the locking mechanism is a hydraulic locking mechanism, which includes an electro-hydraulic servo valve, a displacement sensor, and a pressure sensor; Once the engineering vehicle has come to a complete stop, the machine-control coordination unit controls the extension and retraction of each hydraulic locking mechanism based on the vehicle body attitude angle measured by the tilt sensor. Using the feedback value from the displacement sensor as the control basis, the unit performs closed-loop displacement control on the unmanned aerial vehicle nest platform to ensure that the platform's levelness is within ±1°. After leveling, the machine-control coordination unit switches to force closed-loop control mode, using the deviation between the pressure sensor feedback value and the target locking force as the control basis, and generates a dynamic pressure compensation signal in combination with the feedforward compensation amount. The dynamic pressure compensation signal is then output to the electro-hydraulic servo valve of each hydraulic locking mechanism to adjust the output pressure of each hydraulic locking mechanism.

[0013] Furthermore, the environmental coupling module includes a sealed chamber, multiple temperature sensors distributed at different locations within the sealed chamber, multiple adjustable guide vanes disposed in the airflow channel within the sealed chamber, and at least two independently controlled cooling fans. The ring-control collaborative unit collects the measured temperature values ​​of each temperature sensor at a preset sampling frequency, constructs discrete temperature sample points with the spatial coordinates of each temperature sensor and the corresponding measured temperature values, and reconstructs the temperature field distribution inside the sealed chamber using inverse distance weighted interpolation or radial basis function interpolation. In the inverse distance weighted interpolation method, the weight of each temperature sensor is inversely proportional to the distance from the sensor to the target point, and the radial basis function interpolation method uses Gaussian function or multiple quadratic function as basis functions. The ring-control collaborative unit calculates the temperature gradient of each region based on the reconstructed temperature field distribution, identifies regions with temperature gradients exceeding a preset threshold as hot spots, and calculates the target deflection angle of each adjustable guide vane and the target speed of each cooling fan based on the position coordinates of the hot spots within the sealed chamber. This causes each adjustable guide vane to deflect to the target angle to guide cold air to the hot spots, and causes each cooling fan to operate at the target speed to provide the corresponding airflow. The environmental coupling module also includes a PTC heating unit. When the environmental-control coordination unit detects that the temperature in any area of ​​the sealed chamber is lower than a preset low temperature threshold, the PTC heating unit is activated to heat the chamber and the speed of each cooling fan is adjusted according to the temperature field distribution to guide the hot air to the low temperature area. The PTC heating unit has a self-limiting temperature characteristic, and can raise the temperature of the area where the drone battery is located to above 0°C within 30 minutes under an external ambient temperature of -30°C.

[0014] On the other hand, the present invention provides a method for integrating unmanned aerial vehicle (UAV) nests based on engineering vehicles, comprising the following steps: Monitor the operating status parameters of engineering vehicles, and the mechanical, electrical, and environmental status parameters of unmanned aerial vehicle (UAV) nests; When at least one state parameter is detected to have changed, the collaborative controller synchronously adjusts the control parameters of at least two coupled modules to form a cross-module collaborative control closed loop. The collaborative control closed loop includes at least one of the following: The electric-control collaborative closed loop generates a predicted signal for voltage fluctuation events based on the electrical parameters of the vehicle power supply and the operating status parameters of the engineering vehicle, and outputs the predicted signal to the electrical coupling module to trigger the electrical coupling module to switch its working mode. The machine-control collaborative closed loop involves the machine-control collaborative unit performing spectral analysis on the vibration parameters of the engineering vehicle to obtain the vibration spectrum, generating a locking force adjustment signal based on the vibration spectrum and the locking state parameters of the mechanical coupling module, and outputting the locking force adjustment signal to the mechanical coupling module to drive the mechanical coupling module to adjust the locking force. The environmental-control collaborative closed loop involves the environmental-control collaborative unit collecting environmental parameter values ​​from multiple locations within the sealed chamber, generating an environmental parameter distribution map based on the environmental parameter values ​​at each location, and outputting zonal adjustment signals to the environmental coupling module based on the environmental parameter distribution map.

[0015] Furthermore, it also includes coordinated scheduling steps: In response to the positioning signal and mission command of the engineering vehicle, the collaborative controller sequentially controls the mechanical coupling module to perform platform leveling, controls the mechanical coupling module to perform nest deployment, and controls the electrical coupling module and the environmental coupling module to collaboratively support the take-off of the UAV; During task execution, the collaborative controller continuously monitors the electrical parameters of the electrical coupling module and the environmental parameters of the environmental coupling module; When the battery level is detected to be below the first threshold or the wind speed is detected to be above the second threshold, the collaborative controller automatically triggers the drone to return to its home location and controls the mechanical coupling module to execute the recovery procedure.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are: 1. This invention systematically solves the problem of vehicle-cabin-machine collaborative operation under three severe conditions: voltage fluctuation, random vibration, and harsh environment, by constructing three closed loops: electric-control collaboration, machine-control collaboration, and environmental-control collaboration. In terms of electric-control collaboration, by monitoring the vehicle power supply voltage, voltage change rate, and engine status signals, a multi-signal fusion decision model is used to predict voltage drop events. Before the voltage drop occurs, the transient power buffer unit is controlled to enter a pre-synchronization state, so that its output voltage is in the same frequency, phase, and amplitude as the main converter. When the voltage drop occurs, the transient power buffer unit is switched from voltage control mode to current control mode, and the current command value is output with the goal of compensating for the power deficit, so as to realize uninterrupted power supply under voltage fluctuation and ensure the stable operation of the UAV charging system.

[0017] 2. In terms of machine-control coordination, by collecting vibration acceleration signals of engineering vehicles and actual locking force signals of locking mechanisms, the vibration signals are subjected to spectrum analysis to identify the dominant frequency and amplitude of vibration. The identification results are input into the vibration-force attenuation model to calculate the feedforward compensation amount. At the same time, the deviation between the actual locking force and the target locking force is calculated and the feedback compensation amount is calculated through the feedback control algorithm. The locking mechanism is driven by the superposition of the feedforward and feedback values, so that the steady-state error of the locking force under random vibration environment is controlled within 5%, which solves the problem of locking loosening and equipment fatigue failure caused by vibration.

[0018] 3. In terms of environmental-control coordination, by collecting temperature values ​​from multiple locations within the sealed cabin, the temperature field distribution is reconstructed using inverse distance weighted interpolation or radial basis function interpolation. Areas where the temperature gradient exceeds a preset threshold are identified as hotspots. Based on the location coordinates of the hotspots, the angle of the adjustable guide vanes and the speed of the cooling fans are independently adjusted to prioritize the flow of cool air to the hotspots. In low-temperature environments, the PTC heating unit is activated, and the fan speed is adjusted according to the temperature field distribution to direct hot air to the low-temperature region. This achieves differentiated temperature field control within the cabin, solving the temperature adaptability problem of UAVs and batteries in harsh environments. On this basis, the status of each coupled module is monitored by a collaborative controller. When the status of any module changes, the working status of other modules is adjusted synchronously, forming a cross-module collaborative control closed loop, breaking the traditional architecture of independent mechanical, electrical, and environmental subsystems. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0020] Figure 1 This is a schematic diagram of the structure of the unmanned aerial vehicle nesting integration system based on engineering vehicles according to the present invention; Figure 2This is a schematic diagram of the steps of the unmanned aerial vehicle nesting integration method based on engineering vehicles of the present invention; Figure 3 This is a flowchart of the collaborative scheduling steps of the unmanned aerial vehicle nesting integration method based on engineering vehicles according to the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1: Please see Figure 1 This embodiment details a drone nesting integration system based on an engineering vehicle provided by the present invention.

[0023] In this embodiment, in order to address the impact of three severe conditions—voltage fluctuations, random vibrations, and harsh environments—on the stable operation of the unmanned aerial vehicle (UAV) nest during the driving and operation of the engineering vehicle, the present invention constructs a mechanical coupling module, an electrical coupling module, an environmental coupling module, and a collaborative controller. The collaborative controller enables a cross-module collaborative control closed loop for the three modules.

[0024] Specifically, the mechanical coupling module is installed on the engineering vehicle to achieve mechanical connection and dynamic isolation between the UAV nest and the engineering vehicle; the electrical coupling module is electrically connected to the on-board power supply of the engineering vehicle to convert the on-board power supply into the working power required by the UAV nest; the environmental coupling module is installed on the engineering vehicle and includes a sealed cabin to provide sealing protection and temperature and humidity regulation for the UAV; the collaborative controller is communicatively connected to the mechanical coupling module, electrical coupling module, and environmental coupling module respectively, and monitors the status of each coupling module in real time. When the status of any coupling module changes, the collaborative controller synchronously adjusts the working status of other coupling modules, thereby forming a cross-module collaborative control closed loop. Through this architecture design, the present invention deeply integrates the originally independent mechanical, electrical, and environmental subsystems, laying the foundation for the subsequent implementation of the three collaborative closed loops.

[0025] In this embodiment, to achieve electric-control coordination, an electric-control coordination unit is integrated within the coordination controller. This electric-control coordination unit monitors the electrical parameters of the vehicle power supply and the operating status parameters of the engineering vehicle. Based on the monitored electrical parameters and operating status parameters, it generates a prediction signal for voltage fluctuation events and outputs the prediction signal to the electrical coupling module, triggering the electrical coupling module to switch its operating mode.

[0026] In this preferred embodiment, the electrical coupling module includes a main power conversion unit and a transient power buffer unit connected in parallel with the main power conversion unit. The main power conversion unit adopts a high-frequency isolated DC / DC conversion topology, such as an LLC resonant converter or a phase-shifted full-bridge converter, to convert the on-board power supply of the engineering vehicle into the 48V operating power supply required by the unmanned aerial vehicle (UAV) pod. The typical value of its on-board power supply is 24V DC, which can fluctuate within the range of 21V to 28V under conditions such as engine start-up and sudden load changes.

[0027] In this preferred embodiment, the transient power buffer unit includes a supercapacitor array and a bidirectional power conversion circuit. One end of the supercapacitor array is electrically connected to one end of the bidirectional power conversion circuit, and the other end of the bidirectional power conversion circuit is connected in parallel to the output of the main power conversion unit. The bidirectional power conversion circuit adopts an isolated bidirectional buck-boost topology based on silicon carbide MOSFETs. Its control terminal is connected to the electrical-control coordination unit. The silicon carbide devices allow the converter to operate at higher frequencies, typically greater than 500kHz, thereby significantly reducing the size of passive components and improving dynamic response speed.

[0028] The electronic-control coordination unit first monitors the vehicle power supply voltage, voltage change rate, and engine status signal of the engineering vehicle; the voltage change rate is calculated through high-speed ADC sampling and hardware differentiating circuitry to characterize the severity of voltage drop; then, the electronic-control coordination unit inputs the monitoring data into the fusion decision model to calculate the warning confidence level of the voltage drop event, which is calculated according to the following formula: In the formula: , , For the preset weighting coefficients, and = 0.5、 = 0.3、 = 0.2; Assess the confidence level for the engine start command when an engine start message is captured. = 1.0, otherwise = 0; For the confidence level of the rate of change of voltage, and ,in Preset calibration coefficients; dV / dt represents the rate of change of voltage, that is, the derivative of voltage with respect to time, which is used to characterize the severity of voltage drop; The load change confidence level is set when the load change rate exceeds a preset threshold. Increase.

[0029] When the warning confidence level exceeds the first threshold or the voltage falls below the second threshold, the electronic-control coordination unit determines that a voltage drop event is about to occur and controls the transient power buffer unit to enter a pre-synchronization state before the actual voltage drop event occurs. It should be noted that the pre-synchronization state refers to the state where the output voltage of the transient power buffer unit is in sync with the output voltage of the main power conversion unit in terms of frequency, phase, and amplitude. In the pre-synchronization state, the bidirectional power conversion circuit operates in voltage control mode, using a phase-locked loop algorithm to estimate the instantaneous phase angle of the main power conversion unit's output voltage in real time and adjusts its own output voltage to match the main power conversion unit's output voltage in terms of frequency, phase, and amplitude. When the output voltage difference is less than a preset value, such as 0.5V, pre-synchronization is considered complete.

[0030] When a voltage dip event actually occurs, the electrical-control coordination unit switches the bidirectional power conversion circuit from voltage control mode to current control mode within milliseconds, for example, within 1 millisecond. It should be noted that the electrical coupling module operates in both voltage control and current control modes. Voltage control mode refers to the mode that uses the output voltage as the control target and stabilizes it at a preset value through closed-loop regulation. Current control mode refers to the mode that uses the output current as the control target and makes the output current track a preset current command value. During normal operation, the main power conversion unit operates in voltage control mode. When a voltage dip event occurs, the electrical-control coordination unit switches the transient power buffer unit from voltage control mode to current control mode, causing it to output compensation current according to the current command value.

[0031] At this time, the electronic-control coordination unit generates a current command value by looking up a table through feedforward based on the warning confidence level and the input voltage drop depth. The bidirectional power conversion circuit controls the output current in peak current mode, so that the energy stored in the supercapacitor array is released to the load end through the bidirectional power conversion circuit to compensate for the power deficit of the main power conversion unit.

[0032] After the voltage drop event ends, when the on-board power supply voltage is detected to have recovered and stabilized above 23V, and the main power conversion unit is confirmed to be able to carry the load again, the electric-control coordination unit controls the bidirectional power conversion circuit to smoothly reduce the output current, transfer the load power back to the main power conversion unit, and then switch to charging mode to charge the supercapacitor array with a multi-stage adaptive charging strategy. The multi-stage adaptive charging strategy includes a constant current pre-charging stage, a constant current fast charging stage, and a constant voltage trickle charging stage. When the supercapacitor voltage is below the safety threshold, such as 70% of the rated voltage, a small current constant current pre-charging is used. When the voltage reaches the safety threshold, the maximum allowable charging current is used for constant current fast charging, and this charging current value is dynamically adjusted according to the current load capacity of the main power conversion unit. When the voltage is close to the rated voltage, such as 95%, the system switches to constant voltage charging mode, and the charging current automatically and gradually decreases until it falls below the threshold, at which point charging is considered complete.

[0033] Through the aforementioned power-control coordination mechanism, this invention upgrades the power supply system from a passive voltage converter to an energy regulator capable of actively predicting and mitigating disturbances, thereby achieving uninterrupted power supply under voltage fluctuations.

[0034] In this embodiment, to achieve machine-control coordination, a machine-control coordination unit is integrated within the coordination controller. This machine-control coordination unit monitors the vibration parameters of the engineering vehicle and the locking state parameters of the mechanical coupling module, performs spectral analysis on the vibration parameters to obtain the vibration spectrum, and generates a locking force adjustment signal based on the vibration spectrum and locking state parameters. This signal is then output to the mechanical coupling module to drive the mechanical coupling module to adjust the locking force.

[0035] Specifically, in this embodiment, the mechanical coupling module includes a base, a shock absorber, a platform, and at least three locking mechanisms. The base is fixedly installed on the cargo box floor or the longitudinal beam of the vehicle frame using high-strength bolts, providing the mounting foundation for the entire mechanical coupling module. The shock absorber is mounted on the base and adopts a two-stage series structure: the first stage is an air spring, with its lower end fixed to the base and its upper end connected to the platform, used to absorb low-frequency, large-amplitude vibrations caused by uneven road surfaces; the second stage is a combination of silicone damping pads and metal wire vibration isolators, located between the platform and the UAV nest mounting frame, used to filter high-frequency, small-amplitude vibrations generated by the engine and transmission system.

[0036] The two-stage series structure described above effectively attenuates vibration energy across the entire 1-100Hz frequency band, enhancing the overall vibration reduction effect. The platform is mounted on the vibration reduction device to support the drone nest; the locking mechanism is located between the platform and the base. In this embodiment, three hydraulic locking mechanisms are arranged in a triangle between the base and the platform, and each locking mechanism includes an electro-hydraulic servo valve, a displacement sensor, and a pressure sensor.

[0037] The machine-control collaborative unit first acquires the vibration acceleration signal of the engineering vehicle and the actual locking force signal of the locking mechanism. The vibration acceleration signal is acquired through an IMU sensor installed on the base or platform, and the locking force signal is acquired through the pressure sensor built into each locking mechanism. Then, the machine-control collaborative unit performs spectral analysis on the vibration signal to identify the dominant frequency and amplitude of the vibration, which can be achieved using a fast Fourier transform algorithm.

[0038] Next, the machine-control coordination unit inputs the identification results into the vibration-force attenuation model to calculate the feedforward compensation amount.

[0039] The vibration-force attenuation model is as follows: in, The Laplace transform of the predicted locking force attenuation. This represents the Laplace transform of the vibration acceleration amplitude, where K1 is the gain coefficient. Let ζ be the system's natural frequency, ζ be the damping ratio, and s be the Laplace operator; The gain coefficient K and the system natural frequency The damping ratio ζ is pre-calibrated through bench testing. The calibration process includes: applying vibration excitation of different frequencies and amplitudes on a standard vibration table, collecting pressure attenuation data of the locking mechanism, and fitting the value of ζ through a system identification algorithm.

[0040] Meanwhile, the machine-control coordination unit calculates the deviation between the actual locking force and the target locking force, calculates the feedback compensation amount through the PID feedback control algorithm, and finally, the machine-control coordination unit drives the electro-hydraulic servo valve of the locking mechanism with the superposition value of the feedforward compensation amount and the feedback compensation amount to dynamically adjust the locking force and keep the locking force within the preset range. The actual test shows that when the locking force is dynamically adjusted, the steady-state error of the locking force relative to the target locking force is controlled within 5%.

[0041] Based on this, once the engineering vehicle has come to a complete stop, the machine-control coordination unit first executes the platform leveling procedure. Using the pitch and roll angles measured by the dual-axis tilt sensors, and combining this with the platform's geometric model, the machine-control coordination unit calculates the target extension and retraction of the three hydraulic locking mechanisms, ensuring that the normal vector of the platform plane is parallel to the direction of gravity.

[0042] The specific calculation formula is as follows: in, For the first The target extension / retraction amount of the locking mechanism. The proportional coefficient is pre-calibrated based on the platform's geometric dimensions and control accuracy requirements. , ) is the first The coordinates of each locking mechanism within the platform plane. The machine-control coordination unit uses the feedback value from the displacement sensor as the control basis, and controls each electro-hydraulic servo valve through displacement closed-loop control to ensure that the platform levelness is within ±1°.

[0043] After balancing, the machine-control coordination unit switches to force closed-loop control mode. It's important to note that force closed-loop control mode uses the locking force as the control target. The actual locking force is fed back in real-time by pressure sensors and compared with the target locking force. The opening of the electro-hydraulic servo valve is adjusted based on the deviation to bring the actual locking force close to and maintain it near the target locking force. In this mode, the machine-control coordination unit continuously monitors the pressure sensor feedback values ​​of each locking mechanism and compares them with the preset target locking force. Simultaneously, based on the vibration spectrum collected by vibration sensors, a vibration-force attenuation model is used to calculate the feedforward compensation in real-time. The feedforward compensation and the PID feedback control are superimposed to form a dynamic pressure compensation signal, driving the electro-hydraulic servo valve to dynamically adjust the oil pressure, ensuring that the locking force remains within the preset range even under random vibration conditions.

[0044] Through the aforementioned machine-control collaborative mechanism, this invention upgrades the mechanical fixing device from static locking to an active anti-vibration servo system, solving the problems of loosening of the locking mechanism and equipment fatigue failure caused by vibration.

[0045] In this embodiment, to achieve environmental-control coordination, an environmental-control coordination unit is integrated within the coordination controller. This environmental-control coordination unit monitors environmental parameters inside the UAV nest, collects environmental parameter values ​​from multiple locations within the sealed cabin, generates an environmental parameter distribution map based on the environmental parameter values ​​at each location, and outputs zonal adjustment signals to the environmental coupling module according to the distribution map.

[0046] Specifically, in this embodiment, the environmental coupling module includes a sealed chamber, multiple temperature sensors distributed at different locations within the sealed chamber, multiple adjustable guide vanes installed in the airflow channels within the sealed chamber, at least two independently controlled cooling fans, and a PTC heating unit. The sealed chamber is constructed from an aluminum alloy frame welded to composite panels, achieving an overall sealing rating of IP67, allowing for short-term immersion in water up to 1 meter deep without leakage. The chamber is equipped with a micro-positive pressure system, continuously injecting filtered clean air into the chamber via a small air pump, maintaining a slightly higher internal air pressure than the external pressure to prevent external dust and moisture from seeping in through gaps in doors and other areas. Temperature sensors are distributed at different locations within the sealed chamber. In this embodiment, six temperature sensors are arranged within the sealed chamber, with spatial coordinates of (0,0,0), (0,1,0), (1,0,0), (1,1,0), (0,0,0.5), and (1,1,0.5), respectively (unit: meters). Adjustable baffles are installed in the airflow channels within the sealed chamber, and their angle can be independently adjusted by the environmental control unit. The cooling fans consist of at least two independently controlled fans, whose speeds can be independently adjusted under the control of the environmental control unit. The PTC heating unit uses PTC ceramic heating elements, which have self-limiting temperature characteristics, are safe and reliable, and have a maximum power consumption of 300W.

[0047] The environmental control coordination unit first collects the measured temperature values ​​of each temperature sensor at a preset sampling frequency, such as 1Hz, and constructs discrete temperature sample points using the spatial coordinates of each temperature sensor and the corresponding measured temperature values. Then, the environmental control coordination unit reconstructs the temperature field distribution inside the sealed chamber using inverse distance weighted interpolation or radial basis function interpolation.

[0048] This embodiment uses the inverse distance weighted interpolation method, with a power exponent of 2, and the weighting coefficients are calculated using the following formula: in, For the first The weighting coefficients of each temperature sensor, For the point to be requested The Euclidean distance between the temperature sensors and the temperature field distribution function are calculated using the following formula: in, Point to be sought The estimated temperature value at that location, For the first The actual temperature value measured by each temperature sensor This represents the total number of temperature sensors.

[0049] If radial basis function interpolation is used, then the Gaussian function or multiple quadratic functions are used as basis functions, and their expressions are as follows: in, For radial basis functions, Let be the radial distance from the point to be determined to the known sample point. These are shape parameters, calibrated experimentally.

[0050] Next, the environmental control unit calculates the temperature gradient of each region based on the reconstructed temperature field distribution, identifies regions with temperature gradients exceeding a preset threshold, such as 5℃ / m, as hotspot regions, and records the center coordinates of the hotspot regions. Then, based on the location coordinates of the hotspot regions, the environmental control unit calculates the target deflection angle of each adjustable guide vane and the target speed of each cooling fan. The deflection angle of the guide vane is calculated based on spatial geometric relationships, ensuring that the airflow direction points towards the hotspot region after the guide vane deflects. The fan speed is calculated based on the deviation between the temperature of the hotspot region and the target temperature, using a PID algorithm.

[0051] Finally, the environmental control coordination unit outputs the calculation results to each adjustable guide vane and cooling fan, causing each adjustable guide vane to deflect to the target angle to guide the cold air to the hot spot area, and causing each cooling fan to operate at the target speed to provide the corresponding air volume.

[0052] Under low-temperature conditions, when the environmental control unit detects that the temperature in any area within the sealed chamber is below a preset low-temperature threshold, such as 5°C, it activates the PTC heating unit to heat the chamber and adjusts the speed of each cooling fan according to the temperature field distribution to direct hot air to the low-temperature area. For example, when the lowest temperature inside the chamber is below 5°C, the environmental control unit activates the PTC heating unit and sets the fan speed to a low setting to ensure uniform circulation of hot air within the chamber, preventing localized overheating. Actual measurements show that, in an external ambient temperature of -30°C, the system can quickly raise the temperature of the area where the drone battery is located from -30°C to above 5°C.

[0053] Through the aforementioned environmental-control collaborative mechanism, this invention upgrades cabin thermal management from overall ventilation to precise targeted thermal management, achieving zoned differentiated airflow distribution and solving the problem of temperature adaptability of drones and batteries in harsh environments.

[0054] Example 2: Please see Figure 2 and Figure 3 This embodiment is based on Embodiment 1. In order to achieve fully automated deployment and recovery, it specifically describes a method for integrating unmanned aerial vehicle nests based on engineering vehicles.

[0055] The method first includes a status monitoring step: monitoring the operating status parameters of the engineering vehicle, the mechanical status parameters, electrical status parameters, and environmental status parameters of the unmanned aerial vehicle (UAV) nest. Specifically, the electric-control coordination unit monitors the electrical parameters of the on-board power supply, including voltage, current, and voltage change rate, and the operating status parameters of the engineering vehicle, including engine status and vehicle speed; the mechanical-control coordination unit monitors the vibration parameters of the engineering vehicle, such as acceleration, frequency, and amplitude, and the locking status parameters of the mechanical coupling module, including locking force and displacement; the environmental-control coordination unit monitors environmental parameters at multiple locations within the sealed chamber, including temperature and humidity.

[0056] Secondly, it includes a collaborative control step: when at least one state parameter is detected to have changed, the collaborative controller synchronously adjusts the control parameters of at least two coupled modules, forming a cross-module collaborative control closed loop. Specifically, the electric-control collaborative closed loop refers to the electric-control collaborative unit generating a predicted signal for voltage fluctuation events based on the electrical parameters of the vehicle power supply and the operating state parameters of the engineering vehicle, and outputting this signal to the electric coupling module to trigger the electric coupling module to switch its operating mode. The mechanical-control collaborative closed loop refers to the mechanical-control collaborative unit performing spectral analysis on the vibration parameters of the engineering vehicle to obtain the vibration spectrum, generating a locking force adjustment signal based on the vibration spectrum and the locking state parameters of the mechanical coupling module, and outputting this signal to the mechanical coupling module to drive the mechanical coupling module to adjust the locking force.

[0057] The closed-loop environmental-control coordination refers to the environmental-control coordination unit collecting environmental parameter values ​​from multiple locations within the sealed chamber, generating an environmental parameter distribution map based on the environmental parameter values ​​at each location, and outputting zonal adjustment signals to the environmental coupling module based on the distribution map.

[0058] Finally, the collaborative scheduling steps are included: in response to the positioning signal and mission instructions of the engineering vehicle, the collaborative controller sequentially controls the mechanical coupling module to perform platform leveling, controls the mechanical coupling module to perform nest deployment, and controls the electrical coupling module and environmental coupling module to collaboratively support the UAV takeoff.

[0059] Specifically, once the vehicle comes to a complete stop, the machine-control coordination unit controls the locking mechanism to perform automatic leveling, ensuring the platform's levelness is within ±1°. After leveling, the machine-control coordination unit controls the electromagnetic catapult slide rail mechanism to smoothly launch the unmanned aerial vehicle (UAV) nest. Simultaneously, the electrical-control coordination unit ensures that the electrical coupling module outputs a stable power supply, and the environmental-control coordination unit ensures that the environmental coupling module provides a suitable temperature environment.

[0060] During mission execution, the collaborative controller continuously monitors the power parameters of the electrical coupling module and the environmental parameters of the environmental coupling module. When the power level is detected to be below a first threshold (e.g., the drone's battery level is below 25%) or the wind speed is detected to be above a second threshold (e.g., the wind speed is greater than 15 m / s), the collaborative controller automatically triggers the drone to return to base and controls the mechanical coupling module to execute the recovery procedure, including retracting the slide rail and closing the hatch.

[0061] Through the above-mentioned collaborative scheduling method, this invention upgrades the deployment mode of manual intervention to a fully automated process, which can be completed quickly from parking to takeoff, realizing the "stop and use" operation capability and solving the problems of emergency response timeliness requirements and human dependence.

[0062] After integrating the above modules into the engineering vehicle, the system operates according to the following complete process: During the preparation and readiness phase, the engineering vehicle drives towards the target area, and the system continuously receives high-precision positioning signals. After the vehicle comes to a stop, the mechanical coupling module automatically initiates the platform leveling procedure. The tilt sensor reads the vehicle's attitude, and the three-point hydraulic locking mechanism activates to automatically level the drone's platform until it reaches a horizontal position. Simultaneously, the environmental coupling module begins operation, preheating or dissipating heat to create a suitable internal environment for the drone.

[0063] During the deployment phase, after the platform is leveled, the collaborative controller confirms the "ready" status and sends a "deploy" command. The electromagnetic catapult slide mechanism is activated, smoothly pushing the UAV nest to the predetermined working position with a preset acceleration curve. The hatch opens automatically, the UAV powers on for self-testing, and establishes a communication link with the flight control platform and the nest.

[0064] During the mission execution phase, the drone takes off autonomously and performs tasks such as inspection and photography along a preset route. A high-speed communication network transmits high-definition video streams back to the backend in real time. The collaborative controller monitors the drone's battery level, location, attitude, and external weather data in real time.

[0065] During the recovery and charging phases, in planned recovery, the drone automatically returns to base after the mission is completed or the battery level drops to a preset threshold; in emergency recovery, the system automatically executes an emergency recovery procedure when the airborne or vehicle-mounted weather sensors detect severe weather signals; the drone uses a visual-assisted landing system and an infrared guidance beacon on top of the nest to accurately locate itself and land at the designated position; after landing, the wireless charging system automatically aligns and starts charging; after charging is complete, the slide rail automatically retracts, the hatch closes, and the system enters standby mode.

[0066] Through the implementation of the above technical solutions, this invention has achieved significant technical effects compared to existing technologies: In terms of power supply stability, addressing the problem of severe voltage fluctuations under conditions such as engine start-up and sudden load changes in engineering vehicles, this invention achieves uninterrupted power supply under voltage fluctuations through a multi-signal fusion prediction and virtual synchronization seamless switching mechanism, ensuring the efficient and stable operation of the UAV charging system; In terms of mechanical reliability, addressing the problem of high-intensity random vibrations during the driving and operation of engineering vehicles, this invention upgrades static locking to an active anti-vibration servo system through a composite control strategy of vibration spectrum identification feedforward and force-position hybrid feedback, effectively solving the problem of vibration-induced locking loosening and equipment fatigue failure; In terms of environmental adaptability, addressing harsh environments such as rain, snow, sandstorms, and high and low temperatures, this invention achieves refined and intelligent cabin thermal management through sealed protection and differentiated temperature field zoning, expanding the spatiotemporal boundaries of UAV operations; In terms of deployment efficiency, this invention upgrades the traditional cumbersome deployment mode that relies on manual intervention to a fast and seamless automated operation capability through a fully automatic collaborative scheduling process, solving the problems of emergency response timeliness requirements and human dependence.

[0067] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An integrated unmanned aerial vehicle (UAV) nesting system based on engineering vehicles, characterized in that, include: The mechanical coupling module, installed on the engineering vehicle, is used to achieve mechanical connection and dynamic isolation between the drone nest and the engineering vehicle; The electrical coupling module is electrically connected to the on-board power supply of the engineering vehicle and is used to convert the on-board power supply into the working power required by the drone nest. An environmental coupling module, installed on an engineering vehicle and containing a sealed cabin, is used to provide sealed protection and temperature and humidity regulation for the drone. The collaborative controller is communicatively connected to the mechanical coupling module, the electrical coupling module, and the environmental coupling module, respectively. The collaborative controller monitors the status of each coupled module. When the status of any coupled module changes, the collaborative controller synchronously adjusts the working status of other coupled modules to form a cross-module collaborative control closed loop.

2. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 1, characterized in that, The collaborative controller integrates an electrical-control collaborative unit, a machine-control collaborative unit, and an environmental-control collaborative unit, wherein: The electric-control coordination unit monitors the electrical parameters of the vehicle power supply and the operating status parameters of the engineering vehicle, generates a prediction signal for voltage fluctuation events based on the monitored electrical parameters and operating status parameters, and outputs the prediction signal to the electrical coupling module to trigger the electrical coupling module to switch its working mode. The machine-control coordination unit monitors the vibration parameters of the engineering vehicle and the locking state parameters of the mechanical coupling module, performs spectral analysis on the vibration parameters to obtain the vibration spectrum, and generates a locking force adjustment signal based on the vibration spectrum and locking state parameters. The locking force adjustment signal is then output to the mechanical coupling module to drive the mechanical coupling module to adjust the locking force. The environmental-control collaborative unit monitors the environmental parameters inside the UAV nest, collects environmental parameter values ​​at multiple locations within the sealed cabin, generates an environmental parameter distribution map based on the environmental parameter values ​​at each location, and outputs a zonal adjustment signal to the environmental coupling module based on the environmental parameter distribution map.

3. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 2, characterized in that, The electrical coupling module includes a main power conversion unit and a transient power buffer unit connected in parallel with the main power conversion unit; The electronic-control coordination unit monitors the vehicle's power supply voltage, voltage change rate, and engine status signals, and inputs the monitoring data into a fusion decision model to calculate the warning confidence level for voltage drop events. The warning confidence level is calculated according to the following formula: In the formula: , , For the preset weighting coefficients, and = 0.5、 = 0.3、 = 0.2; Assess the confidence level for the engine start command when an engine start message is captured. = 1.0, otherwise =0; For the confidence level of the rate of change of voltage, and ,in Preset calibration coefficients; The load change confidence level is set when the load change rate exceeds a preset threshold. Increase; When the warning confidence exceeds the first threshold or the voltage is lower than the second threshold, the electronic-control coordination unit controls the transient power buffer unit to enter the pre-synchronization state before the voltage drop event actually occurs, so that its output voltage is in the same frequency, phase and amplitude as the output voltage of the main power conversion unit. When a voltage drop event actually occurs, the electrical-control coordination unit switches the transient power buffer unit from voltage control mode to current control mode, and outputs a current command value with the goal of compensating for the power deficit of the main power conversion unit.

4. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 3, characterized in that, The transient power buffer unit includes a supercapacitor array and a bidirectional power conversion circuit. The supercapacitor array is electrically connected to one end of the bidirectional power conversion circuit, and the other end of the bidirectional power conversion circuit is connected in parallel to the output of the main power conversion unit. When a voltage drop event occurs, the electronic-control coordination unit controls the bidirectional power conversion circuit to switch to current control mode, so that the supercapacitor array outputs current to the load through the bidirectional power conversion circuit; After the voltage drop event ends, the electronic-control cooperative unit controls the bidirectional power conversion circuit to charge the supercapacitor array using a multi-stage adaptive charging strategy; The multi-stage adaptive charging strategy includes: constant current pre-charging stage, constant current fast charging stage, and constant voltage trickle charging stage, wherein the charging current value of the constant current fast charging stage is dynamically adjusted according to the current load capacity of the main power conversion unit.

5. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 2, characterized in that, The mechanical coupling module includes: The base is fixedly installed on the engineering vehicle; A shock-absorbing device is installed on the base; The platform, mounted on the shock-absorbing device, is used to support the drone nest; At least three locking mechanisms are disposed between the platform and the base, each locking mechanism including a drive element and a force sensor; The machine-control collaborative unit collects the vibration acceleration signal of the engineering vehicle and the actual locking force signal of the locking mechanism, and performs spectrum analysis on the vibration signal to identify the dominant frequency and amplitude of the vibration; The machine-control collaborative unit inputs the identification results into the vibration-force attenuation model to calculate the feedforward compensation amount. At the same time, it calculates the deviation between the actual locking force and the target locking force and calculates the feedback compensation amount through the feedback control algorithm. Then, it drives the locking mechanism with the superposition value of the feedforward compensation amount and the feedback compensation amount to dynamically adjust the locking force.

6. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 5, characterized in that, The vibration-force attenuation model is as follows: in, The Laplace transform of the predicted locking force attenuation. This represents the Laplace transform of the vibration acceleration amplitude, where K is the gain coefficient. Let ζ be the system's natural frequency, ζ be the damping ratio, and s be the Laplace operator; The gain coefficient K and the system natural frequency The damping ratio ζ is pre-calibrated through bench testing. The calibration process includes: applying vibration excitation of different frequencies and amplitudes on a standard vibration table, collecting pressure attenuation data of the locking mechanism, and fitting the value of ζ through a system identification algorithm.

7. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 6, characterized in that, The locking mechanism is a hydraulic locking mechanism, which includes an electro-hydraulic servo valve, a displacement sensor, and a pressure sensor; Once the engineering vehicle has come to a stop, the machine-control coordination unit controls the extension and retraction of each hydraulic locking mechanism based on the vehicle body attitude angle measured by the tilt sensor, and uses the feedback value of the displacement sensor as the control basis to perform closed-loop displacement control on the unmanned aerial vehicle nest platform. After leveling, the machine-control coordination unit switches to force closed-loop control mode, using the deviation between the pressure sensor feedback value and the target locking force as the control basis, and generates a dynamic pressure compensation signal in combination with the feedforward compensation amount. The dynamic pressure compensation signal is then output to the electro-hydraulic servo valve of each hydraulic locking mechanism to adjust the output pressure of each hydraulic locking mechanism.

8. The unmanned aerial vehicle (UAV) nesting integration system based on engineering vehicles according to claim 2, characterized in that, The environmental coupling module includes a sealed chamber, multiple temperature sensors distributed at different locations within the sealed chamber, multiple adjustable guide vanes installed in the airflow channel within the sealed chamber, and at least two independently controlled cooling fans. The ring-control collaborative unit collects the measured temperature values ​​of each temperature sensor at a preset sampling frequency, constructs discrete temperature sample points with the spatial coordinates of each temperature sensor and the corresponding measured temperature values, and reconstructs the temperature field distribution inside the sealed chamber using inverse distance weighted interpolation or radial basis function interpolation. In the inverse distance weighted interpolation method, the weight of each temperature sensor is inversely proportional to the distance from the sensor to the target point, and the radial basis function interpolation method uses Gaussian function or multiple quadratic function as basis functions. The ring-control collaborative unit calculates the temperature gradient of each region based on the reconstructed temperature field distribution, identifies regions with temperature gradients exceeding a preset threshold as hot spots, and calculates the target deflection angle of each adjustable guide vane and the target speed of each cooling fan based on the position coordinates of the hot spots within the sealed chamber. This causes each adjustable guide vane to deflect to the target angle to guide cold air to the hot spots, and causes each cooling fan to operate at the target speed to provide the corresponding airflow. The environmental coupling module also includes a PTC heating unit. When the environmental-control coordination unit detects that the temperature in any area of ​​the sealed chamber is lower than a preset low temperature threshold, the PTC heating unit is activated to heat the chamber and the speed of each cooling fan is adjusted according to the temperature field distribution to guide the hot air to the low temperature area.

9. A method for integrating unmanned aerial vehicles (UAVs) based on engineering vehicles, applied to the UAV integration system based on engineering vehicles as described in any one of claims 1-8, characterized in that, Includes the following steps: Monitor the operating status parameters of engineering vehicles, and the mechanical, electrical, and environmental status parameters of unmanned aerial vehicle (UAV) nests; When at least one state parameter is detected to have changed, the collaborative controller synchronously adjusts the control parameters of at least two coupled modules to form a cross-module collaborative control closed loop. The collaborative control closed loop includes at least one of the following: The electric-control collaborative closed loop generates a predicted signal for voltage fluctuation events based on the electrical parameters of the vehicle power supply and the operating status parameters of the engineering vehicle, and outputs the predicted signal to the electrical coupling module to trigger the electrical coupling module to switch its working mode. The machine-control collaborative closed loop involves the machine-control collaborative unit performing spectral analysis on the vibration parameters of the engineering vehicle to obtain the vibration spectrum, generating a locking force adjustment signal based on the vibration spectrum and the locking state parameters of the mechanical coupling module, and outputting the locking force adjustment signal to the mechanical coupling module to drive the mechanical coupling module to adjust the locking force. The environmental-control collaborative closed loop involves the environmental-control collaborative unit collecting environmental parameter values ​​from multiple locations within the sealed chamber, generating an environmental parameter distribution map based on the environmental parameter values ​​at each location, and outputting zonal adjustment signals to the environmental coupling module based on the environmental parameter distribution map.

10. The method for integrating unmanned aerial vehicle (UAV) nests based on engineering vehicles according to claim 9, characterized in that, It also includes the coordinated scheduling step: In response to the positioning signal and mission command of the engineering vehicle, the collaborative controller sequentially controls the mechanical coupling module to perform platform leveling, controls the mechanical coupling module to perform nest deployment, and controls the electrical coupling module and the environmental coupling module to collaboratively support the take-off of the UAV; During task execution, the collaborative controller continuously monitors the electrical parameters of the electrical coupling module and the environmental parameters of the environmental coupling module; When the battery level is detected to be below the first threshold or the wind speed is detected to be above the second threshold, the collaborative controller automatically triggers the drone to return to its home location and controls the mechanical coupling module to execute the recovery procedure.

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