Intelligent control system and method for window and skylight of amphibious vehicle

Abstract

The invention discloses an intelligent control system and method for windows and skylights of an amphibious vehicle, and relates to the technical field of intelligent control of automobiles. Receiving vehicle state and environment information, performing fusion analysis and decision, and outputting a control instruction; the central intelligent decision and control module comprises a data fusion and risk calculation sub-module, an intelligent decision logic sub-module and a control sub-module; the data fusion and risk calculation sub-module adopts a multi-sensor data fusion algorithm to comprehensively evaluate the vehicle state and environment information to obtain a comprehensive risk index; the intelligent decision logic sub-module performs logic judgment according to the comprehensive risk index and triggers a safety response; the control submodule generates a corresponding control instruction according to the safety response; and the execution and driving module is used for receiving the control instruction and driving a corresponding mechanical structure to act. When the water depth exceeds a safety threshold value, a vehicle window closing program is automatically triggered, and the sealing performance of the compartment is ensured.

Description

Technical Field

[0001] This invention relates to the field of automotive intelligent control technology, and in particular to an intelligent control system and method for the windows and sunroof of an amphibious vehicle. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] Amphibious vehicles face multiple risks when wading through water or encountering sudden flooding. For example, external water can easily enter the vehicle if the windows are not closed in time, causing the vehicle to sink rapidly, short-circuit the electrical system, and cause occupants to drown. If the vehicle malfunctions, gets stuck in a pit, or overturns, the doors may not be able to be opened normally, trapping occupants in a confined space. In emergencies, occupants may be unable to quickly and effectively operate the windows and sunroofs for escape or ventilation due to panic or environmental limitations.

[0004] Current automotive systems lack intelligent, proactive safety redundancy designs in terms of control. Most vehicles rely on manual control of windows, sunroofs, and other opening and closing components by the driver to improve their sealing. However, in water-related scenarios, human operation is generally prone to delays and misjudgments, potentially causing water to enter the vehicle, leading to electrical short circuits, interior damage, or even safety accidents.

[0005] Some high-end models have also introduced basic wading sensing functions, which use sensors to monitor water level and vehicle status in real time and automatically trigger some sealing measures. However, there is no corresponding backup control strategy or redundancy design in case of sensor failure or signal interruption. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, this invention provides an intelligent control system and method for the windows and sunroof of an amphibious vehicle. The system uses wading radar to monitor the vehicle's wading depth in real time. When the water depth exceeds a safety threshold, the system automatically triggers a window closing procedure to ensure the vehicle's airtightness. If the wading radar system malfunctions, the system automatically switches to a redundant control mode and actively opens the sunroof as an emergency escape route.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: In a first aspect, the present invention provides an intelligent control system for the windows and sunroof of an amphibious vehicle, comprising: A multi-source information sensing module is used to collect vehicle status and environmental information in real time; The central intelligent decision-making and control module receives vehicle status and environmental information, performs fusion analysis and decision-making, and outputs control commands. The central intelligent decision-making and control module includes a data fusion and risk calculation submodule, an intelligent decision-making logic submodule, and a control submodule. The data fusion and risk calculation submodule uses a multi-sensor data fusion algorithm to comprehensively evaluate vehicle status and environmental information to obtain a comprehensive risk index. The intelligent decision-making logic submodule performs logical judgments based on the comprehensive risk index and triggers a safety response. The control submodule generates corresponding control commands based on the safety response. The execution and drive module is used to receive control commands and drive the corresponding mechanical structure actions.

[0008] A further technical solution is that the vehicle status and environmental information includes vehicle tilt angle data, power system fault level data, wading radar communication link status data, and real-time water depth data.

[0009] In a further technical solution, the multi-sensor data fusion algorithm adopts the DS evidence theory and calculates a comprehensive risk index based on the DS evidence theory.

[0010] A further technical solution involves making logical judgments based on the comprehensive risk index to trigger a safety response. Specifically, when the comprehensive risk index is greater than or equal to a preset wading threshold, the vehicle is determined to be facing a wading risk, and a window closing command is triggered. When the comprehensive risk index is greater than or equal to a preset emergency threshold, the vehicle is determined to be in a high-risk emergency state, and a window closing and sunroof opening command is triggered.

[0011] Further technical solutions stipulate that a vehicle entering a high-risk emergency state includes at least one of the following risk events: The communication of the wading radar unit has been continuously interrupted for more than the set time. The power system monitoring subunit reported a serious power system fault; The vehicle attitude monitoring subunit detected that the vehicle tilt angle exceeded the preset tilt threshold.

[0012] A further technical solution is that the execution and drive module includes a window control unit and a sunroof control unit. The window control unit is connected to the window motors of each door and integrates an anti-pinch function.

[0013] In a further technical solution, the sunroof control unit is connected to the sunroof motor and combines thermal management resources and air pressure sensor data to achieve dynamic adaptive sunroof control based on thermal management and air pressure sensing.

[0014] Secondly, the present invention provides an intelligent control method for the windows and sunroof of an amphibious vehicle, comprising: Real-time collection of vehicle status and environmental information; The system receives vehicle status and environmental information, performs fusion analysis and decision-making, and outputs control commands. Specifically, it uses a multi-sensor data fusion algorithm to comprehensively evaluate vehicle status and environmental information to obtain a comprehensive risk index; it makes logical judgments based on the comprehensive risk index to trigger a safety response; and it generates corresponding control commands based on the safety response. It receives control commands and drives the corresponding mechanical structures to perform actions.

[0015] Thirdly, the present invention provides a vehicle including an intelligent control system for the windows and sunroof of an amphibious vehicle as described in the first aspect.

[0016] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when executed by a processor, the program implements the steps of the intelligent control method for the windows and sunroof of an amphibious vehicle as described in the second aspect.

[0017] The above one or more technical solutions have the following beneficial effects: This invention integrates and analyzes collected vehicle status and environmental perception signals in real time through an integrated intelligent decision-making center, enabling accurate and dynamic assessment of water-related risks and automatically triggering graded and collaborative proactive safety control.

[0018] This invention integrates multi-dimensional information such as wading radar data, vehicle attitude monitoring, power system status monitoring, and communication status monitoring through a multi-source information sensing module to construct a complementary sensing network. Furthermore, it employs a data fusion algorithm based on DS evidence theory or Bayesian networks to effectively handle uncertainties in multi-source information, dynamically calculate the comprehensive risk index, and overcome the shortcomings of single sensors being prone to failure and false alarms.

[0019] This invention features a central intelligent decision-making and control module that, based on a dynamically calculated comprehensive risk index, presets tiered decision thresholds to achieve adaptive responses ranging from low-risk monitoring and water wading warnings with window closure to high-risk emergency escape. This tiered logic avoids overreaction or underreaction. Simultaneously, the system employs an "OR" logic in emergency escape determination; if any high-risk event occurs—abnormal water depth, communication interruption, severe power failure, or severe vehicle tilting—the highest-level response is decisively activated, ensuring priority is given to establishing escape routes in the worst-case scenario, significantly increasing the probability of survival.

[0020] The execution and drive module of this invention also integrates a backup power management unit, ensuring that critical window closing and sunroof opening actions can still be reliably executed in extreme cases of main power failure, thus solving the defect of system paralysis caused by vehicle power failure in emergencies. Furthermore, sunroof control is not limited to opening to a fixed position, but can be dynamically fine-tuned based on in-vehicle thermal management data or air pressure sensor data. This not only optimizes ventilation and improves the cabin environment, but also acts as a "pressure relief valve" during deep water wading, actively balancing the pressure difference between the inside and outside of the vehicle, protecting the vehicle body structure and glass, and creating more effective air convection, further enhancing safety redundancy and system functionality.

[0021] In this invention, the alarm module can promptly and strongly remind vehicle occupants of risks through various means. When the remote distress unit triggers an emergency state, it can automatically send information such as the vehicle's precise location and the type of risk to the rescue platform, realizing the transformation from passively waiting for rescue to actively seeking help, thus buying valuable time for external rescue. Attached Figure Description

[0022] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0023] Figure 1 This is a block diagram of an intelligent control system for the windows and sunroof of an amphibious vehicle according to an embodiment of the present invention; Figure 2 This is a control flowchart of an embodiment of the present invention. Detailed Implementation

[0024] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0025] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0026] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0027] Example 1 like Figure 1As shown, this embodiment discloses an intelligent control system for the windows and sunroof of an amphibious vehicle, including: The multi-source information sensing module is used to collect vehicle status and environmental information in real time as input for intelligent decision-making.

[0028] In this embodiment, the multi-source information sensing module includes a wading radar unit, a vehicle status monitoring unit, and a communication status monitoring unit.

[0029] The wading radar unit employs millimeter-wave wading radar deployed at the front, rear, or side bumpers of the vehicle. It is used for high-frequency, high-precision real-time detection of the water depth surrounding the vehicle, acquiring real-time water depth data. The wading radar has a sampling frequency of no less than 10Hz, a measurement range of 0-10000mm, and high accuracy. The 10mm wading radar unit transmits real-time water depth data to the central intelligent decision-making and control module via a dual-channel transmission system using a high-speed CAN bus and wireless communication technology. As the primary source of water depth data, the wading radar unit employs dual-channel transmission to reduce the risk of single-point failures.

[0030] The vehicle status monitoring unit monitors the health of the vehicle's core systems, including a powertrain monitoring subunit and a vehicle attitude monitoring subunit. The powertrain monitoring subunit monitors the operating status of the power battery, range extender, propulsion system, and electronic control unit (ECU), identifying and reporting serious faults such as high battery temperature, insufficient propulsion torque, and ECU short circuits. An ECU short circuit indicates that voltage is not detected in certain battery areas or that current is excessively high. Insufficient propulsion torque means that the motor speed and propulsion torque do not meet expectations. The vehicle attitude monitoring subunit is the chassis system's attitude monitoring system, including an inertial measurement unit (IMU) for real-time monitoring of vehicle attitude angles (roll, pitch, and yaw). It also includes a six-axis gyroscope, inclinometer, and accelerometer, enabling high-frequency monitoring and feedback of real-time vehicle tilt angles (defined as ≥30° as "severe tilt") to identify whether the vehicle is experiencing severe tilting or rollover risk.

[0031] The communication status monitoring unit is used to monitor the communication link status between the water-penetrating radar unit and the central intelligent decision-making and control module in real time, and to determine whether communication failures such as data timeouts or interruptions have occurred. In this embodiment, if the central intelligent decision-making and control module does not receive data for 30 consecutive seconds, it is determined as "communication loss".

[0032] In some implementations, the wading radar unit is used as the main sensor, but the intelligent control system also receives data from the power system monitoring subunit and the vehicle attitude monitoring subunit as backup trigger conditions for safety redundancy design.

[0033] Through the above technical features, a multi-layered and highly reliable sensing network is constructed, providing a comprehensive and trustworthy raw data foundation for the central intelligent decision-making and control module, fundamentally overcoming the fatal defects of single sensor systems that are prone to failure and misjudgment in complex water environments.

[0034] The wading radar unit, serving as the main sensor, employs millimeter-wave radar (which is highly resistant to environmental interference) and combines high-speed CAN with dual-channel wireless communication transmission. Redundancy is achieved from the physical layer to the data link layer, ensuring that even if a communication path is interrupted due to flooding, short circuits, or interference, critical water depth data can still be delivered through the backup channel. This significantly reduces the risk of the system "going blind" due to a single link failure and guarantees the continuity of core sensing functions.

[0035] The perception module not only focuses on the external environment (water depth), but also deeply monitors the health of the internal core systems (power failure) and the physical attitude of the vehicle itself (severe tilt) through the vehicle condition monitoring unit. This design enables the system to capture different types of high-risk events with equivalent consequences: for example, the vehicle may not be submerged in deep water, but may experience severe tilting due to getting stuck in a pothole (attitude risk); or the power system may experience a sudden and severe failure in shallow water, causing the vehicle to lose its mobility (failure risk). This internal condition data and water depth data form valuable cross-validation and information complementarity, allowing the system to define "danger" no longer limited to water depth, but to any complex hazard that could trap the occupants inside the cabin.

[0036] A dedicated communication status monitoring unit is specifically designed to monitor the integrity of the main sensor's data stream. Once communication is determined to be lost, it becomes strong evidence of risk in itself. This means the system can make decisions not only based on "what data was received," but also on "whether the expected data was received." This self-reflective capability regarding the health of the sensing link allows the system to promptly detect and trigger the highest level of emergency response when the main sensor silently fails due to physical damage (the most dangerous failure mode), avoiding missed opportunities for escape due to "false safety" (misjudging nothing has happened due to no data updates).

[0037] By explicitly using wading radar as the primary sensor and simultaneously employing dynamic and attitude data as backup trigger conditions, a safety redundancy design is employed. Under normal circumstances, the system relies on high-precision, high-frequency water depth data for refined risk assessment and early warning. In the event of primary sensor failure or specific hazardous situations (such as vehicle tilting causing radar readings to fail), the backup conditions can immediately take over, serving as a reliable basis for directly triggering emergency escape. This design balances precise control under normal conditions with a safety net in extreme situations, significantly enhancing the overall robustness of the system.

[0038] The central intelligent decision-making and control module is used to receive vehicle status and environmental information, perform fusion analysis and decision-making, and output control commands.

[0039] In this embodiment, the central intelligent decision-making and control module serves as the core of the system. It receives real-time vehicle status and environmental information, performs comprehensive evaluation through data fusion algorithms, and makes hierarchical decisions based on the evaluation results.

[0040] The central intelligent decision-making and control module includes a data fusion and risk calculation submodule, an intelligent decision-making logic submodule, and a control submodule.

[0041] The data fusion and risk calculation submodule uses multi-sensor data fusion algorithms, such as DS evidence theory and Bayesian networks, to comprehensively evaluate real-time water depth data, vehicle fault status, vehicle attitude and communication status, and finally outputs a comprehensive risk index as the basis for whether to trigger a safety action.

[0042] Dempster's evidence theory is applicable to scenarios with uncertainty and incomplete information, and can effectively handle conflicts and complementarities between multi-source data. The system assigns a basic probability assignment (BPA) to each type of sensor data and synthesizes evidence using Dempster's combination rules.

[0043] For example: Real-time water depth data (depth ≥ 500 mm) is assigned a high confidence value (e.g., 0.6); communication loss or severe system failure (communication status) is assigned an even higher confidence value (0.7-0.8) because it directly affects the control link; vehicle attitude is assigned a medium confidence value (0.5) because it may indirectly reflect the vehicle status. By synthesizing this evidence, the system calculates the global confidence and uncertainty, and then determines whether the risk threshold has been reached. This transforms diverse, uncertain, and potentially conflicting raw sensor information into a unified, quantifiable, and comparable comprehensive risk index, thereby achieving an intelligent leap in decision-making from discrete signal judgment to continuous situation assessment.

[0044] The final comprehensive risk index integrates multi-dimensional and heterogeneous risk evidence into a one-dimensional scalar, enabling precise comparison and measurement of risk status at different times and under different circumstances. Furthermore, through mathematical evidence synthesis and normalization, it effectively smooths out instantaneous noise or jumps in single sensor data, making the output results more stable and reliable, and avoiding false triggering of commands due to jitter of a single signal.

[0045] In some implementations, Bayesian networks are used as an alternative system. Network nodes include variables such as water depth, communication status, powertrain status, and vehicle attitude. Their conditional probability tables (CPTs) are based on historical data or experimental calibration. The system receives real-time sensor observations and calculates the posterior probability of "needing to trigger a safety action" through Bayesian inference. The weights of various sensor data are set based on the reliability and urgency of each data point and can be adjusted through calibration. Ultimately, whether the risk index exceeds a threshold determines whether a safety action is executed.

[0046] The intelligent decision-making logic submodule makes logical judgments based on the comprehensive risk index and presets two decision thresholds to trigger different levels of security responses. The triggering conditions are as follows: When the comprehensive risk index is greater than or equal to the preset wading threshold (first decision threshold), the vehicle is determined to face a wading risk, triggering a window closing command. In this embodiment, the preset wading threshold is set to 500mm, but it can be set according to the vehicle model and usage environment; no specific limitation is made here.

[0047] When the comprehensive risk index is greater than or equal to the preset emergency threshold (second decision threshold), the vehicle is determined to have entered a high-risk emergency state, triggering commands to close the windows and open the sunroof. Entering a high-risk emergency state means the occurrence of any one of the following risk events, or a combination of multiple risk events: (1) Communication interruption of the wading radar unit for more than the set time. If the water depth data collected by the wading radar is not updated within the set time, it is determined to be a communication interruption, which may be due to short circuit or signal interference caused by flooding.

[0048] (2) The power system monitoring subunit reports serious power system faults. The power system monitoring subunit reports serious faults, including engine shutdown, battery pack short circuit or high voltage power failure, which significantly increase the risk of the vehicle being trapped.

[0049] (3) The vehicle body attitude monitoring subunit detects that the vehicle body tilt angle exceeds a preset tilt threshold. If the detected vehicle body tilt angle exceeds the tilt threshold, in this embodiment, the tilt threshold is set to... This indicates that the vehicle may have overturned or gotten stuck in a pothole, which could easily lead to water ingress.

[0050] If the vehicle is determined to be in a high-risk emergency state, immediately activate the emergency escape procedure, close the windows, and open the sunroof.

[0051] The intelligent decision-making process is as follows: receive data from multiple sensor sources, calculate the comprehensive risk index through a data fusion algorithm, and determine whether the comprehensive risk index is greater than or equal to the preset emergency threshold. If so, execute "close the windows and open the sunroof". If not, determine whether the comprehensive risk index is greater than the preset wading threshold. If so, execute "close the windows". If not, return to continuous monitoring status.

[0052] The above technical solution transforms the calculated comprehensive risk index into clear, hierarchical, discrete execution instructions, thereby constructing a precise decision-making mechanism.

[0053] By setting two tiered thresholds—a wading threshold and an emergency threshold—this module maps a continuous, comprehensive risk index to three distinct action instructions: "No Action," "Close Windows," and "Close Windows and Open Sunroof." This achieves precise control. It avoids the overreaction (e.g., opening the sunroof after only minor wading, causing unnecessary panic or water ingress) or underreaction (e.g., only closing windows but failing to open the escape route if the vehicle is trapped) that can occur with a single-threshold system. This tiered logic ensures that the system's behavior closely matches the actual risk level assessed by multiple factors, enhancing the effectiveness of safety measures and the user experience.

[0054] The most critical design feature of this module is its rapid triggering channel based on OR logic for emergency escape commands. Whether it's due to extremely deep water, communication interruption, severe power failure, or significant vehicle tilting—any independent high-risk event—as long as it's identified by the front-end fusion algorithm and raises the overall risk index, the system will bypass conventional judgment and directly execute the highest level of safety response: closing the windows and opening the sunroof. Especially when sensors may fail (e.g., a communication interruption might mean the main radar is submerged) or the vehicle undergoes drastic changes in attitude, this logic ensures the system doesn't delay the escape window by waiting for further confirmation, making the most decisive and expeditious decision for the occupants' survival.

[0055] This module follows a sequence of first assessing emergency situations, then issuing warnings, and otherwise monitoring – a stable and efficient decision-making mechanism. This process ensures that the trigger path for the highest priority commands is minimized. Furthermore, it uses a smoothed and synthesized comprehensive risk index output from the front-end data fusion and risk calculation submodule as the sole criterion for judgment, rather than directly relying on a potentially volatile raw sensor signal. This effectively filters data noise, prevents command jitter caused by momentary sensor interference, and ensures a stable and reliable final decision output.

[0056] In summary, the intelligent decision-making logic submodule transforms the comprehensive risk index of complex situations by intelligent algorithms into clear, explicit, and hierarchical action commands. This ensures that in critical emergency situations, the system can skip all complex intermediate states and directly target the core safety objective of ensuring the escape of occupants, thereby enabling the entire intelligent control system to possess decision-making reliability and safety authority.

[0057] The control submodule generates corresponding control commands based on the decisions made by the intelligent logic decision-making submodule, including closing all windows and opening the sunroof to a preset position. This module translates the logical decisions into specific control command frames with timing and parameters, and sends them to the corresponding actuators via the CAN bus.

[0058] The execution and drive module is used to receive control commands and drive the corresponding mechanical structure actions.

[0059] In this embodiment, the execution and drive module receives control commands from the central intelligent decision-making and control module and drives the corresponding mechanical mechanisms to operate. This module includes a window control unit, a sunroof control unit, and a backup power management unit.

[0060] The window control unit connects to the window motors of each door. Upon receiving a closing command, it quickly drives all windows to rise until they are fully closed. The task of the window control unit is to quickly (… 2s) Raise the windows to prevent a large influx of water into the cabin. Upon receiving the closing command, the window control unit should immediately activate each window to raise or lower, ensuring closure even in the event of a power outage using backup power. Simultaneously, the window control unit sends a "windows are fully closed" status signal to the central intelligent decision-making and control module and the sunroof control unit.

[0061] Furthermore, the window control unit integrates an anti-pinch function. During the upward movement, it detects obstacles by monitoring the motor current or Hall sensor signals. If an obstacle is encountered, it automatically reverses and descends a certain distance. The anti-pinch function is a crucial safety feature. During the window's upward movement, the control unit continuously monitors the motor current or monitors position parameters via the Hall sensor. If a sudden increase in current or a very small change in position is detected (indicating an obstacle, such as a occupant's hand or head), the motor reverses its direction and descends a certain height (usually 15-20 centimeters) to prevent injury to the occupant.

[0062] Furthermore, the control unit needs to obtain the absolute position information of the windows through the Hall sensor to achieve closed-loop control. That is, the windows can be accurately closed to the top and reported even when they are at any opening value.

[0063] The sunroof control unit connects to the sunroof motor. Upon receiving an opening command, it drives the sunroof to open to a preset safe opening degree (e.g., 70%-85% fully open). This unit can dynamically fine-tune the sunroof opening degree based on data subsequently obtained from other vehicle systems (such as air conditioning and air pressure sensors) to optimize ventilation or balance internal and external air pressure.

[0064] After receiving a "all windows closed" signal from the window control unit, the sunroof control unit activates the sunroof function to create an emergency escape and ventilation passage. Preset position: Generally 70%. This value is an engineering compromise based on multiple considerations; fully opening (100%) might weaken the overall structural rigidity of the roof to some extent. Ventilation: A sufficiently large sunroof opening ensures airflow between the vehicle interior and the outside, preventing risks to occupants due to oxygen deficiency or excessive carbon dioxide concentration in a confined space. Emergency escape: The size is sufficient for most adults to climb out and also provides a clear rescue entrance for external assistance.

[0065] Furthermore, while the current strategy of opening the sunroof to a fixed preset position is conservative and effective, it is not optimal. Through data linkage between the central intelligent decision-making and control module and other vehicle systems, dynamic adaptive sunroof control based on thermal management and air pressure sensing can be achieved. Combining thermal management resources: The sunroof control unit can obtain data such as interior temperature and humidity from the vehicle's air conditioning system (HVAC). If, after system triggering, the interior environment tends towards high temperature and humidity (potentially leading to heatstroke or suffocation for occupants), the algorithm can decide to appropriately increase the sunroof opening (e.g., from 70% to 85%) to accelerate air circulation and improve the microenvironment. Introducing air pressure sensor data: This is the most promising area for optimization. When the vehicle is wading through deep water, the external water pressure exerts enormous pressure on the vehicle body, causing the interior air pressure to rise. There is a risk that the pressure difference could prevent the windows from opening or even cause them to shatter. The control system will dynamically and precisely fine-tune the sunroof opening based on the pressure difference. When the system detects a continuous increase in air pressure inside the vehicle, it gradually expands the sunroof opening angle from 70% to 100%, acting as a "pressure relief valve" to actively balance the pressure difference between the inside and outside of the vehicle. This not only protects the windows and vehicle structure from pressure damage but also more effectively expels stale air and introduces fresh air through the directional airflow, greatly enhancing the system's safety redundancy and functionality.

[0066] Through the above technical solutions, the skylight is upgraded from a preset, static emergency exit into an intelligent terminal that can intelligently sense the internal environment and external pressure and actively make dynamic adjustments for life support and safety structure protection. This achieves a qualitative leap in emergency safety from ensuring the existence of the passage to optimizing the passage function and the internal environment.

[0067] A fixed opening strategy only ensures the availability of one physical exit. However, by introducing thermal management (HVAC) data linkage, the system can monitor critical life-sustaining parameters such as temperature and humidity inside the cabin in real time. When the environment is determined to be deteriorating (high temperature and high humidity), the skylight opening is proactively increased to improve ventilation efficiency. This effectively mitigates secondary risks such as heatstroke, suffocation, or carbon dioxide poisoning that occupants may face in enclosed or semi-enclosed spaces, buying valuable time for rescue. The skylight's function is thus expanded from an escape opening to an active regulator for maintaining the cabin's survival environment.

[0068] When a vehicle is submerged in water, especially rapidly, the enormous pressure difference between the inside and outside of the vehicle poses a fatal threat that traditional emergency designs have overlooked. This invention introduces a pressure sensor and establishes closed-loop control, enabling the sunroof to act as an intelligent, gradual pressure relief valve in deep water pressure environments. The system dynamically adjusts its opening to balance the pressure difference, fundamentally preventing the occurrence of the two extreme situations mentioned above. This not only protects the integrity of the windows and vehicle structure but also ensures the operability of the escape route under any pressure condition.

[0069] The backup power management unit automatically switches to the vehicle's backup power source (such as a supercapacitor or independent battery) when it detects an anomaly or power failure in the vehicle's main power supply, ensuring that the windows and sunroof can still perform critical functions in emergencies. The backup power management unit continuously monitors the vehicle's main battery voltage, and when the voltage reaches the operating threshold or a main power failure signal is received, it automatically and seamlessly switches to the backup power source composed of supercapacitor banks, ensuring that the windows and sunroof can complete critical actions that are being performed or about to be triggered.

[0070] The alarm module is used to transmit alarm information to occupants inside the vehicle and to the outside world.

[0071] In this embodiment, the alarm module is triggered synchronously with the actuator, with the aim of awakening the attention of occupants and external personnel through multiple senses.

[0072] The alarm module includes an audible and visual alarm unit and a remote distress signal unit.

[0073] The audible and visual alarm unit controls the vehicle's audio system to emit alarm sounds at specific frequencies, controls the instrument panel and central control screen to display red warning information, and controls the interior lights to flash. When the comprehensive risk index is greater than or equal to the preset water wading threshold or the preset emergency threshold, it triggers the commands to close the windows and open the sunroof, activating the audible and visual alarm. Acoustic alarm: A high-frequency, intermittent buzzing sound is emitted through the vehicle's audio system (even if the entertainment system is off, the alarm priority can be forcibly switched). The tone and rhythm are specially designed to be easily identifiable in noisy environments and can effectively penetrate water, alerting occupants who may be too nervous or unconscious to notice the danger in time. Optical alarm: The vehicle's instrument panel and central control screen display a red warning icon and simple text prompts (such as "Water wading risk! Windows closed, sunroof open!") at maximum brightness. Simultaneously, interior reading lights and ambient lights enter a flashing mode to enhance the visual warning effect. It can also control the hazard warning lights to flash continuously at a high frequency, transmitting a distress signal to the outside world.

[0074] The remote distress unit works in conjunction with the onboard telematics unit to automatically send a distress signal containing the vehicle's location and risk type to a pre-set rescue platform when emergency escape conditions are triggered. The alarm module can also link with the onboard TBOX (such as e-Call or OnStar) to automatically send the vehicle's precise location, current status, and hazard status (water depth, power failure, abnormal posture, etc.) to the rescue center when an alarm is triggered.

[0075] Example 2 This embodiment discloses an intelligent control method for the windows and sunroof of an amphibious vehicle, including: Real-time collection of vehicle status and environmental information; The system receives vehicle status and environmental information, performs fusion analysis and decision-making, and outputs control commands. Specifically, it uses a multi-sensor data fusion algorithm to comprehensively evaluate vehicle status and environmental information to obtain a comprehensive risk index; it makes logical judgments based on the comprehensive risk index to trigger a safety response; and it generates corresponding control commands based on the safety response. It receives control commands and drives the corresponding mechanical structures to perform actions.

[0076] In this embodiment, multi-sensor data fusion algorithms, such as DS evidence theory and Bayesian networks, comprehensively evaluate real-time water depth data, vehicle fault status, vehicle posture, and communication status, and finally output a comprehensive risk index as the basis for whether to trigger a safety action.

[0077] Dempster's evidence theory is applicable to scenarios with uncertainty and incomplete information, and can effectively handle conflicts and complementarities between multi-source data. The system assigns a basic probability assignment (BPA) to each type of sensor data and synthesizes evidence using Dempster's combination rules.

[0078] For example: Real-time water depth data (depth ≥ 500 mm) is assigned a high confidence value (e.g., 0.6); communication loss or severe system failure (communication status) is assigned an even higher confidence value (0.7-0.8) because it directly affects the control link; vehicle attitude is assigned a medium confidence value (0.5) because it may indirectly reflect the vehicle status. By synthesizing this evidence, the system calculates the global confidence and uncertainty, and then determines whether the risk threshold has been reached. This transforms diverse, uncertain, and potentially conflicting raw sensor information into a unified, quantifiable, and comparable comprehensive risk index, thereby achieving an intelligent leap in decision-making from discrete signal judgment to continuous situation assessment.

[0079] The final comprehensive risk index integrates multi-dimensional and heterogeneous risk evidence into a one-dimensional scalar, enabling precise comparison and measurement of risk status at different times and under different circumstances. Furthermore, through mathematical evidence synthesis and normalization, it effectively smooths out instantaneous noise or jumps in single sensor data, making the output results more stable and reliable, and avoiding false triggering of commands due to jitter of a single signal.

[0080] In some implementations, Bayesian networks are used as an alternative system. Network nodes include variables such as water depth, communication status, powertrain status, and vehicle attitude. Their conditional probability tables (CPTs) are based on historical data or experimental calibration. The system receives real-time sensor observations and calculates the posterior probability of "needing to trigger a safety action" through Bayesian inference. The weights of various sensor data are set based on the reliability and urgency of each data point and can be adjusted through calibration. Ultimately, whether the risk index exceeds a threshold determines whether a safety action is executed.

[0081] In this embodiment, logical judgment is made based on the comprehensive risk index, and two decision thresholds are preset to trigger different levels of security response. The triggering conditions are as follows: When the comprehensive risk index is greater than or equal to the preset wading threshold (first decision threshold), the vehicle is determined to face a wading risk, triggering a window closing command. In this embodiment, the preset wading threshold is set to 500mm, but it can be set according to the vehicle model and usage environment; no specific limitation is made here.

[0082] When the comprehensive risk index is greater than or equal to the preset emergency threshold (second decision threshold), the vehicle is determined to enter a high-risk emergency state, triggering the commands to close the windows and open the sunroof.

[0083] Example 3 The purpose of this embodiment is to provide a vehicle, including an intelligent control system for the windows and sunroof of an amphibious vehicle as described in Embodiment 1.

[0084] Example 4 The purpose of this embodiment is to provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the method of Embodiment 2.

[0085] The steps and methods involved in the apparatus of Embodiment 4 above correspond to those in Embodiment 2. For specific implementation details, please refer to the relevant description section of Embodiment 2. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0086] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0087] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0088] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. An intelligent control system for the windows and sunroof of an amphibious vehicle, characterized in that, include: A multi-source information sensing module is used to collect vehicle status and environmental information in real time; The central intelligent decision-making and control module is used to receive vehicle status and environmental information, perform fusion analysis and decision-making, and output control commands; the central intelligent decision-making and control module includes a data fusion and risk calculation submodule, an intelligent decision-making logic submodule, and a control submodule; The data fusion and risk calculation submodule uses a multi-sensor data fusion algorithm to comprehensively evaluate vehicle status and environmental information, and obtain a comprehensive risk index. The intelligent decision-making logic submodule makes logical judgments based on the comprehensive risk index and triggers a security response. The control submodule generates corresponding control commands based on the security response; The execution and drive module is used to receive control commands and drive the corresponding mechanical structure actions.

2. The intelligent control system for the windows and sunroof of an amphibious vehicle as described in claim 1, characterized in that, The vehicle status and environmental information includes vehicle tilt angle data, power system fault level data, wading radar communication link status data, and real-time water depth data.

3. The intelligent control system for the windows and sunroof of an amphibious vehicle as described in claim 1, characterized in that, The multi-sensor data fusion algorithm adopts the DS evidence theory and calculates the comprehensive risk index based on the DS evidence theory.

4. The intelligent control system for the windows and sunroof of an amphibious vehicle as described in claim 1, characterized in that, Based on the comprehensive risk index, a logical judgment is made to trigger a safety response. Specifically, when the comprehensive risk index is greater than or equal to the preset water wading threshold, it is determined that the vehicle is facing a water wading risk, and a window closing command is triggered. When the comprehensive risk index is greater than or equal to the preset emergency threshold, it is determined that the vehicle has entered a high-risk emergency state, and a window closing and sunroof opening command is triggered.

5. The intelligent control system for the windows and sunroof of an amphibious vehicle as described in claim 4, characterized in that, A vehicle entering a high-risk emergency state is defined by the occurrence of at least one of the following risk events: The communication of the wading radar unit has been continuously interrupted for more than the set time. The power system monitoring subunit reported a serious power system fault; The vehicle attitude monitoring subunit detected that the vehicle tilt angle exceeded the preset tilt threshold.

6. The intelligent control system for the windows and sunroof of an amphibious vehicle as described in claim 1, characterized in that, The execution and drive module includes a window control unit and a sunroof control unit. The window control unit is connected to the window motors of each door and integrates an anti-pinch function.

7. The intelligent control system for the windows and sunroof of an amphibious vehicle as described in claim 6, characterized in that, The sunroof control unit is connected to the sunroof motor and combines thermal management resources and air pressure sensor data to achieve dynamic adaptive sunroof control based on thermal management and air pressure sensing.

8. A method for intelligent control of windows and sunroof of an amphibious vehicle, characterized in that, include: Real-time collection of vehicle status and environmental information; It receives vehicle status and environmental information, performs fusion analysis and decision-making, and outputs control commands; Specifically, a multi-sensor data fusion algorithm is used to comprehensively evaluate the vehicle status and environmental information to obtain a comprehensive risk index; logical judgment is made based on the comprehensive risk index to trigger a safety response; and corresponding control commands are generated based on the safety response. It receives control commands and drives the corresponding mechanical structures to perform actions.

9. A vehicle, characterized in that, The invention includes an intelligent control system for the windows and sunroof of an amphibious vehicle as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the intelligent control method for the windows and sunroof of an amphibious vehicle as described in claim 8.

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