Intelligent helmet with internal environment regulation function

Abstract

The application discloses a kind of intelligent helmet with internal environment regulation function, it is related to helmet technical field, for the single internal microenvironment regulation function of existing helmet, low intelligent degree, fixed uncontrollable ventilation volume, including helmet body, environmental perception module, user state monitoring module, main control processing module, environment active adjustment module and wireless communication module are integrally installed in helmet body inside, environmental perception module is evenly laid out with three SHT30 temperature and humidity sensors in forehead, head, back of head area and ZE08-VOC sensor, user state monitoring module includes MAX30102 photoelectric heart rate sensor and MPU6050 motion posture sensor, main control processing module uses the built-in data fusion algorithm and adaptive control strategy of STM32F103 single-chip microcomputer, environment active adjustment module includes double air duct micro brushless DC fan, TEC1-12706 semiconductor refrigeration heating component and nanometer silver antibacterial odor removal module, the application is used for the intelligent helmet environment regulation of riding and industrial operation etc. Scene.

Description

Technical Field

[0001] This invention relates to the field of helmet technology, and more particularly to a smart helmet with internal environment regulation function. Background Technology

[0002] As an important personal protective equipment in scenarios such as cycling and industrial operations, smart helmets have gradually evolved from simple physical protective tools to comprehensive intelligent equipment with functions such as sensing, communication, and interaction in recent years with the development of intelligent technology. During daily cycling or work, a relatively closed microenvironment is formed inside the helmet. The water vapor and heat exhaled by the user, as well as volatile organic compounds from the outside, continuously accumulate inside the helmet, leading to increased temperature, excessive humidity, and decreased air quality inside the helmet, which seriously affects wearing comfort and may even cause safety hazards such as dizziness and decreased attention. Currently, although smart helmets on the market have made some progress in communication, navigation, and lighting, they still have significant shortcomings in the active regulation of the internal microenvironment. Traditional helmets mostly adopt a passive ventilation structure, which means that several fixed ventilation holes are opened on the helmet and rely on the natural wind pressure difference during riding to achieve limited air circulation. This method cannot actively adjust according to the actual temperature, humidity and air quality inside the helmet. The ventilation volume is fixed and uncontrollable. Although some high-end helmets are equipped with small fans, they mostly run at a constant speed. They cannot adaptively adjust according to the user's exercise status and physiological needs, nor do they have temperature regulation and deodorization and antibacterial functions. The overall environmental regulation capability is simple and the level of intelligence is low. To address the aforementioned issues, this technical solution proposes an intelligent helmet with internal environment regulation capabilities. Summary of the Invention

[0003] The purpose of this invention is to solve the problems of existing helmets having limited internal microenvironment control functions, low intelligence levels, and fixed and uncontrollable ventilation, and to propose an intelligent helmet with internal environment control functions.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A smart helmet with internal environment regulation function includes a helmet body, and also includes an environment sensing module, a user status monitoring module, a main control processing module, an environment active adjustment module and a wireless communication module integrated and installed inside the helmet body. The signal output terminals of the environmental sensing module and the user status monitoring module are electrically connected to the signal input terminal of the main control processing module. The control signal output terminal of the main control processing module is electrically connected to the controlled terminal of the active environmental adjustment module. The communication terminal of the main control processing module is bidirectionally connected to the wireless communication module. The environmental sensing module uses a combination of temperature and humidity sensors and volatile organic compound sensors to collect real-time temperature, humidity and air quality data inside the helmet. The user status monitoring module collects data on the intensity of the user's exercise activities and physiological state. The main control processing module has a built-in environmental comfort prediction algorithm and adaptive control strategy to receive monitoring data and output control commands. The active environmental adjustment module performs ventilation, temperature regulation, deodorization and antibacterial operations inside the helmet according to the control commands.

[0005] In one possible design, the user status monitoring module includes a photoelectric heart rate sensor and a motion posture sensor. The photoelectric heart rate sensor is used to collect the user's heart rate physiological data, and the motion posture sensor is used to collect the user's cycling speed and motion amplitude data, which together calculate the user's real-time activity intensity.

[0006] In one possible design, the active environmental regulation module includes a dual-duct micro brushless DC fan, a semiconductor cooling and heating component, and a nano-silver antibacterial and deodorizing module. The dual-duct micro brushless DC fan is provided with independent air intake and exhaust ducts. The semiconductor cooling and heating component is fitted to the inner wall of the helmet liner. The nano-silver antibacterial and deodorizing module is embedded inside the helmet vent.

[0007] In one possible design, the main control processing module adopts a microcontroller, which has a built-in data fusion algorithm to perform multi-dimensional fusion of helmet internal environment data, user heart rate data, and motion posture data to predict the trend of changes in helmet internal environment comfort.

[0008] In one possible design, the dual-duct micro brushless DC fan is a low-noise, high-speed micro fan that supports stepless speed adjustment and can switch between three working modes—low-speed ventilation, high-speed air exchange, and silent resistance reduction—according to instructions from the main control processing module.

[0009] In one possible design, the wireless communication module adopts a Bluetooth communication module, which establishes a two-way wireless connection with the mobile APP to upload helmet environmental monitoring data and user movement data, while receiving personalized control parameters sent by the mobile APP.

[0010] In one possible design, the microcontroller incorporates an adaptive ventilation control strategy that switches operating modes according to the user's movement status. During low-speed cruising, it activates a full-speed cooling and ventilation mode, while during high-speed riding, it automatically reduces fan speed and optimizes airflow resistance to achieve noise and resistance reduction.

[0011] In one possible design, the semiconductor cooling and heating component is equipped with a miniature thermally conductive silicone pad and a heat insulation cotton layer. The thermally conductive silicone pad is attached to the heat exchange surface of the semiconductor cooling and heating component, and the heat insulation cotton layer isolates the component from the helmet shell, thereby achieving precise thermal management and avoiding heat loss in extreme environments.

[0012] In one possible design, the mobile app has built-in data statistics and visualization functions, which can generate daily or weekly reports on the helmet's internal environment data, and support users to customize temperature thresholds, humidity thresholds, and ventilation speed thresholds to achieve personalized environmental control settings.

[0013] In one possible design, the temperature and humidity sensors are evenly distributed in three areas: the forehead, the top of the head, and the back of the head of the helmet, to achieve full-area temperature and humidity collection inside the helmet, avoiding the problem of data deviation from single-point monitoring and ensuring the accuracy of environmental monitoring.

[0014] In this application, after the helmet is worn and the power is turned on, the temperature and humidity sensors in the environmental sensing module, located in the forehead, top of the head, and back of the head, begin to collect real-time temperature and humidity data throughout the helmet's interior. Simultaneously, the ZE08-VOC volatile organic compound sensor collects air quality data inside the helmet. The photoelectric heart rate sensor in the user status monitoring module collects the wearer's heart rate physiological data, and the motion posture sensor collects cycling speed and amplitude data. Both are used to calculate the wearer's real-time activity intensity. All the aforementioned environmental and user status data are transmitted to the microcontroller in the main control processing module. The microcontroller's built-in data fusion algorithm performs multi-dimensional fusion of the helmet's internal environmental data, user heart rate data, and motion posture data, and combines this with a built-in environmental comfort prediction algorithm to predict the trend of changes in the helmet's internal environmental comfort. It then outputs adaptive control commands. Upon receiving the control commands, the environmental active adjustment module switches between three working modes—low-speed ventilation, high-speed air exchange, and silent drag reduction—based on the commands. It also supports stepless speed adjustment, activating full-speed cooling and ventilation during low-speed cruising. The system features full-speed cooling and ventilation, automatically reducing fan speed and optimizing airflow resistance during high-speed riding to achieve noise and drag reduction. Independent intake and exhaust ducts handle air intake and exhaust respectively. The semiconductor cooling and heating components, in conjunction with thermally conductive silicone pads and insulation layers, adhere to the inner wall of the helmet liner for precise thermal management, adjusting the internal cooling or heating as needed to avoid heat loss in extreme environments. A nano-silver antibacterial and deodorizing module is embedded inside the ventilation openings to simultaneously perform deodorization and antibacterial operations. The Bluetooth communication module in the wireless communication module establishes a two-way wireless connection with the mobile app, uploading real-time helmet environmental monitoring data and user activity data to the app, while also receiving personalized control parameters from the app. The app's built-in data statistics and visualization functions can generate daily or weekly reports on the helmet's internal environment. Users can customize temperature, humidity, and ventilation speed thresholds through the app to achieve personalized environmental control settings. A barometric pressure sensor detects the internal air pressure of the helmet in real time and displays it on the screen, allowing the wearer to monitor the internal environment and ensure stable operation of the helmet under suitable conditions.

[0015] Beneficial effects: 1. The SHT30 temperature and humidity sensor is evenly distributed in three areas of the helmet: the forehead, the top of the head, and the back of the head, to achieve full-area temperature and humidity collection inside the helmet. This avoids the problem of data deviation from single-point monitoring and ensures the accuracy of environmental monitoring. At the same time, it integrates the helmet's internal environmental data, user heart rate data, and movement posture data in multiple dimensions. Combined with the built-in environmental comfort prediction algorithm, it predicts the trend of changes in the comfort of the helmet's internal environment, realizing the transformation from passive response to active prediction, and making the control more precise and timely. 2. Through the microcontroller's built-in adaptive ventilation control strategy, the working mode is automatically switched according to the user's exercise status. In low-speed cruising mode, the full-speed cooling and ventilation mode is activated, and in high-speed riding mode, the fan speed is automatically reduced and the air duct resistance is optimized to achieve noise reduction and resistance reduction. This effectively solves the problem of excessive wind noise and high wind resistance caused by the constant speed operation of traditional helmet fans when riding at high speeds, and takes into account both wearing comfort and riding safety. 3. The dual-channel miniature brushless DC fan, semiconductor cooling and heating components, and nano-silver antibacterial and deodorizing module are integrated into the helmet. Combined with the miniature thermal conductive silicone sheet and heat insulation cotton layer, it achieves precise thermal management, avoids heat loss in extreme environments, and can simultaneously complete ventilation, temperature regulation, deodorization and antibacterial operations according to the control command. It effectively solves the problems of the existing helmet's single environmental control function and low level of intelligence. 4. A two-way wireless connection is established with the mobile APP via the BLE5.0 Bluetooth communication module to upload helmet environmental monitoring data and user movement data in real time. At the same time, it receives personalized control parameters sent by the APP. The APP has built-in data statistics and visualization functions to generate daily or weekly environmental data reports. It supports users to customize temperature threshold, humidity threshold, and ventilation speed threshold, realizing remote management and personalized settings of the helmet's internal environment and improving the user experience. This invention achieves accurate monitoring of the entire area through multi-point temperature and humidity sensors, combines user heart rate and exercise data to predict environmental changes in a multi-dimensional manner, adaptively switches ventilation modes while taking into account noise reduction and drag reduction, and integrates semiconductor cooling and heating and nano-silver antibacterial and deodorizing modules to complete active regulation, and supports remote personalized settings via APP, effectively solving the problems of traditional helmet environmental regulation functions being limited and lacking in intelligence. Attached Figure Description

[0016] Figure 1 This is a block diagram of the electrical connection structure of an intelligent helmet with internal environment regulation function proposed in this invention.

[0017] Figure 2 This is a top-view three-dimensional schematic diagram of the intelligent helmet with internal environment regulation function proposed in this invention.

[0018] Figure 3 This is a three-dimensional diagram of the upward-looking structure of an intelligent helmet with internal environment regulation function proposed in this invention.

[0019] Figure 4 This is a three-dimensional schematic diagram of the internal structure of a smart helmet with internal environment regulation function proposed in this invention.

[0020] In the diagram: 1. Helmet body; 2. Environmental sensing module; 21. Temperature and humidity sensor; 3. User status monitoring module; 4. Main control processing module; 5. Active environmental adjustment module; 6. Wireless communication module; 7. Surrounding ring; 8. Elastic mesh cover. Detailed Implementation

[0021] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0022] In one embodiment: Refer to Figure 1-4 A helmet includes a helmet body 1, an environmental perception module 2, a user status monitoring module 3, a main control processing module 4, an environmental active adjustment module 5, and a wireless communication module 6.

[0023] The helmet body 1 is constructed with a safety-standard ABS engineering plastic shell and an internal cushioning EPS foam layer to form the basic protective structure. The environmental sensing module 2, user status monitoring module 3, main control processing module 4, environmental active adjustment module 5, and wireless communication module 6 are integrated and installed in the internal cavity and inner lining of the helmet body 1 through structural brackets and cables.

[0024] The signal output terminal of the environmental sensing module 2 is electrically connected to the corresponding pin of the main control processing module 4 via an I2C digital interface. The signal output terminal of the user status monitoring module 3 is electrically connected to the main control processing module 4 via its respective GPIO general-purpose input / output interface. The control signal output terminal of the main control processing module 4 is electrically connected to the controlled terminal of the corresponding component in the environmental active adjustment module 5 via a PWM pulse width modulation interface and a relay drive circuit. The serial communication terminal USART of the main control processing module 4 is bidirectionally connected to the wireless communication module 6. All modules are powered by a single 3.7V, 2000mAh lithium polymer battery, which provides the required operating voltage to each module via a DC-DC step-down circuit.

[0025] The environmental sensing module 2 specifically employs three SHT30 temperature and humidity sensors 21 and one ZE08-VOC electrochemical volatile organic compound sensor. The three SHT30 temperature and humidity sensors 21 are respectively attached to the inner surface of the helmet liner corresponding to the forehead, top of the head, and back of the head areas using thermally conductive adhesive, for collecting temperature and relative humidity data in these three areas. The ZE08-VOC sensor is installed at the top of the helmet cavity near the user's mouth and nose area, for detecting the concentration of volatile organic compounds such as formaldehyde, benzene, and alcohol.

[0026] User status monitoring module 3 includes a MAX30102 photoelectric heart rate and blood oxygen sensor and an MPU6050 six-axis motion sensor. The six-axis motion sensor integrates a three-axis accelerometer and a three-axis gyroscope. The MAX30102 sensor is fixed to the inside of the forehead padding of the helmet liner via a flexible FPC cable. Its LED and photodetector need to be close to the skin to collect heart rate signals. The MPU6050 sensor is fixed to the inside of the top of the helmet shell with screws. It is used to collect acceleration and angular velocity data of the helmet in the X, Y, and Z axes. Through algorithm calculation, the user's movement speed changes and head posture amplitude can be obtained.

[0027] The core of the main control processing module 4 is an STM32F103C8T6 ARM Cortex-M3 core microcontroller. This microcontroller is responsible for receiving and processing data from various sensors. The active environmental adjustment module 5 includes a dual-duct micro brushless DC fan (model AFB0612VH), two TEC1-12706 semiconductor cooling and heating components, and a porous ceramic deodorizing sheet with a nano-silver coating. The dual-duct fan is mounted in a pre-reserved cavity at the rear of the helmet via shock-absorbing rubber pads. Its independent air intake opening faces the lower inner side of the helmet, and its exhaust opening leads to the outside of the helmet. The fan supports stepless speed adjustment within the range of 2000RPM to 8000RPM via PWM signal. The TEC1-12706 semiconductor cooling and heating components are respectively attached and fixed to the padding layers in the temple areas on the left and right sides of the helmet liner. Each TEC component's hot side (cold side during cooling) is in contact with the inner liner pad through a 1mm thick thermally conductive silicone sheet with a thermal conductivity of 3W / (m·K); the cold side (hot side during cooling) is isolated from the helmet's ABS shell through a 5mm thick glass fiber insulation layer. The use of this insulation layer structure in this embodiment is based on engineering considerations for practical use. Without this insulation layer, thermal simulation analysis shows that during cooling in summer conditions with ambient temperatures above 35℃, the heat generated by the TEC component's hot side will be rapidly conducted to the helmet shell, not only reducing cooling efficiency but also potentially causing the local shell temperature to rise above 50℃, affecting wearing comfort and possibly accelerating the aging of the shell material. The nano-silver antibacterial and deodorizing module is embedded in the inner grille of the front air intake duct of the helmet. The wireless communication module 6 consists of a TI CC2640R2F Bluetooth 5.0 low-power chip and its peripheral circuitry, and is soldered to one side of the main control board through a stamp-hole package.

[0028] During operation, after the user puts on the helmet and starts the system, the sensors continuously collect data. Three SHT30 temperature and humidity sensors collect data on the temperature and humidity of three areas inside the helmet every 2 seconds, and the microcontroller takes the average of the three data points as the current internal temperature and humidity value. The ZE08-VOC sensor outputs a volatile organic compound concentration reading every 10 seconds. The MAX30102 sensor collects photoplethysmography (PPG) signals in real time, and the microcontroller processes these signals using its built-in algorithm to obtain the heart rate value (beats / minute). The MPU6050 sensor collects acceleration data at a frequency of 100Hz, and the microcontroller estimates the instantaneous velocity through integration calculations and determines the intensity of the movement based on the magnitude of the acceleration change.

[0029] The STM32F103 microcontroller's built-in data fusion algorithm normalizes and weights the aforementioned temperature, humidity, VOC concentration, heart rate, and movement speed data, and then calls a pre-stored environmental comfort prediction model. This model, built on a large amount of experimental data, is used to predict the probability that a user may experience stuffiness or discomfort within the next 1-2 minutes under the current environmental and user state combination.

[0030] For example, when the system detects a temperature above 28°C, humidity above 70%, and a user's heart rate consistently above 100 beats per minute while in a low-speed exercise state, the model will output a high probability value.

[0031] Based on the prediction results, the microcontroller executes an adaptive control strategy to adjust the speed of the dual-channel fan through the PWM interface.

[0032] For example, when a decrease in comfort is anticipated, the fan speed is increased from the standby 2500 RPM to a high-speed ventilation mode of 5000 RPM. Simultaneously, a relay controls the TEC1-12706 component to power on and set it to cooling mode, actively cooling the contact area of ​​the lining. The nano-silver deodorizing sheet, when the VOC concentration exceeds a set threshold (e.g., 0.1 ppm), is controlled by a microcontroller to intermittently activate its internal micro-heater (e.g., working for 30 seconds, stopping for 5 minutes) to enhance its ability to adsorb and decompose organic matter. The Bluetooth module packages key monitoring data (such as average temperature, heart rate, and VOC alarms) and sends it to the paired user's mobile app every 30 seconds.

[0033] As an optional implementation, the MPU6050 motion attitude sensor can be replaced with a discrete combination of an ADXL345 three-axis accelerometer and an L3G4200D three-axis gyroscope. This replacement is feasible in situations requiring lower cost or more flexible layout, but it necessitates the main control processing module 4 allocating more I / O interfaces for communication and implementing more complex sensor data fusion algorithms in software. Its integration and power consumption control may not be as good as the integrated MPU6050 solution.

[0034] A retaining ring 7 is also fixedly installed inside the helmet body 1, and an elastic mesh cover 8 is fixedly installed through the retaining ring 7. The elastic mesh cover 8 is fitted over the user's head, so that there is a certain gap between the environmental perception module 2, the user status monitoring module 3, the main control processing module 4, the environmental active adjustment module 5, and the wireless communication module 6 and the user's head, which facilitates ventilation and environmental detection.

[0035] This application can be used in the field of helmet technology, or in other fields applicable to this application.

[0036] In another embodiment: Based on the above embodiment, an improvement is made: a smart helmet with internal environment regulation function is applied to the field of helmet technology. The structure of this embodiment is basically the same as the previous embodiment. The difference is that the regulation strategy of the main control processing module 4 and the collaborative working process of the environmental active adjustment module 5 are further refined, and the interaction details of the mobile APP are clarified.

[0037] Within the STM32F103 microcontroller of the main control processing module 4, in addition to basic data fusion and comfort prediction algorithms, an adaptive ventilation control strategy for cycling scenarios is also implemented. This strategy does not simply control the switching based on a single parameter threshold, but introduces a state machine mechanism. When the motion posture sensor MPU6050 data indicates that the user is in a low-speed cruising state, such as an estimated speed between 5km / h and 15km / h, and this continues for more than 30 seconds, the system determines it to be a "low-speed cruising state." In this state, if the environmental sensing module 2 detects that the temperature inside the helmet exceeds 26℃ or the humidity exceeds 65%, the main control processing module 4 will output a command to switch the dual-duct micro brushless DC fan in the environmental active adjustment module 5 to "full-speed cooling and ventilation mode." In this mode, the fan speed is set in the high-speed range of 7000RPM to 8000RPM, and at the same time, the TEC1-12706 semiconductor cooling and heating component starts the cooling mode, aiming to reduce the surface temperature of the padding in the contact area by 3℃ to 5℃. This mode is designed to quickly expel accumulated heat and moisture when the user's heat output is relatively stable but external wind speed assistance is insufficient.

[0038] When motion posture sensor data indicates that the user has entered a high-speed riding state (e.g., the estimated speed consistently exceeds 25 km / h), the system switches to a high-speed drag-reduction mode. External wind pressure itself already provides a strong forced ventilation effect. The main control processing module 4 instructs the dual-duct fan to reduce its speed to a low range of 2000 RPM to 3000 RPM. Its main function shifts from forced airflow to maintaining airflow guidance within the ducts, preventing external turbulence from directly impacting the ears, and significantly reducing fan noise by approximately 15 dBA. Simultaneously, the cooling power of the TEC components may also be reduced or paused accordingly to save energy. This adaptive switching of operating modes based on motion status stems from a problem discovered during engineering testing: maintaining a high fan speed at high speeds not only contributes little to cooling but also generates annoying, continuous high-frequency noise and increases unnecessary wind resistance and power consumption. Without this adaptation, user experience and battery life would be affected during long-distance high-speed riding.

[0039] After establishing a stable connection between the BLE 5.0 Bluetooth communication module of wireless communication module 6 and the user's mobile device, such as a dedicated APP pre-installed on a mobile phone, two-way data interaction is achieved. The APP not only displays the core environmental data transmitted back by the helmet in real time, such as in numerical and graph form, but also provides a parameter setting interface. Users can customize the adjustment thresholds on this interface. For example, they can change the temperature threshold for activating active cooling from the default 26℃ to 24℃, or change the trigger speed threshold for "high-speed drag reduction mode" from 25km / h to 20km / h. These personalized parameters are sent to the main control processing module 4 via Bluetooth and stored in its FLASH memory. Subsequent adjustment strategies will be executed based on the new thresholds.

[0040] In addition, the mobile app's built-in data statistics function summarizes and analyzes data received daily or weekly, including average temperature inside the helmet, maximum humidity, number of VOC exceedances, and average user heart rate, generating visual reports and charts. Users can review historical reports to understand the patterns of physiological and environmental data changes under different seasons and exercise intensities, allowing for more scientific adjustments to personalized control parameters.

[0041] In this embodiment, the environmental sensing module 2 uses three SHT30 temperature and humidity sensors, the placement of which has been verified through finite element thermal simulation and actual measurement. The forehead sensor is located approximately 2 cm above the brow bone, the top of the head sensor is located in the center of the top of the head, and the back of the head sensor is located above the occipital protuberance. The plane formed by these three points roughly covers the main contact and heat-generating area between the head and the helmet liner. This placement method is to avoid data deviations that may occur due to localized sweating, sensor obstruction by hair, or poor fit during single-point monitoring.

[0042] 1. Formula for calculating the intensity of real-time user exercise activity: Real-time activity intensity of the user, dimensionless, ranging from [0,1]. A larger value indicates higher activity intensity. Real-time heart rate monitoring (collected by MAX30102 sensor), unit: beats / minute; User's resting baseline heart rate, in beats per minute, is the user's initial heart rate value at rest. User's maximum tolerable heart rate, unit: beats / minute, calculated using the general formula Hmax=220-age; Real-time cycling speed (collected and calculated by the MPU6050 sensor), unit: km / h; The device's preset maximum compatible riding speed is in km / h. Real-time motion attitude amplitude, unit: m / s 2 ; : Preset maximum motion amplitude threshold, unit: m / s 2 ; , , : These are the weighting coefficients for heart rate, speed, and posture amplitude, respectively, satisfying + + =1, default value =0.5、 =0.3、 =0.2.

[0043] 2. Formula for fusing multidimensional environmental and physiological data inside the helmet: Multidimensional fusion feature values ​​serve as the core input to the main control algorithm, comprehensively reflecting the helmet environment and user status. The helmet's average temperature, in °C, is calculated from the average data of three SHT30 temperature and humidity sensors located on the forehead, top of the head, and back of the head. : Average humidity over the entire helmet area, unit: %RH, average humidity data from three temperature and humidity sensors; VOC concentration inside the helmet, unit: mg / m³ 3 Data is collected in real time by the ZE08-VOC sensor; The user's real-time exercise intensity calculated above; The fusion weighting coefficients for temperature, humidity, VOC concentration, and exercise intensity satisfy... .

[0044] 3. Fan adaptive stepless speed control formula: Fan real-time operating speed, unit: r / min, supports stepless adjustment; : Minimum fan speed for silent operation, corresponding to silent resistance reduction mode; : Fan maximum speed at high speed, corresponding to high-speed air exchange mode; Real-time environmental comfort rating; Motion state correction factor, low-speed cruising High-speed cycling .

[0045] 4. Formula for calculating semiconductor thermal management efficiency: Actual heat exchange efficiency of TEC1-12706 module, with a value range of [0,1]. The component's real-time heat exchange capacity is measured in W, calculated from the thermal conductivity of the thermally conductive silicone sheet. TEC1-12706 Theoretical maximum heat exchange, unit: W, is an inherent parameter of the hardware; The heat insulation loss correction factor is determined by the insulation effect of the insulation layer under normal operating conditions. .

[0046] The accompanying drawings in this application are for illustrative purposes only. The dimensions and shapes of the components shown are not actual limitations but are merely schematic representations. In actual implementation, the components can be reasonably configured and adjusted according to specific needs and actual conditions.

[0047] 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. A smart helmet with internal environment regulation function, comprising a helmet body (1), characterized in that, It also includes an environment perception module (2), a user status monitoring module (3), a main control processing module (4), an environment active adjustment module (5), and a wireless communication module (6) integrated and installed inside the helmet body (1). The signal output terminals of the environmental perception module (2) and the user status monitoring module (3) are electrically connected to the signal input terminal of the main control processing module (4). The control signal output terminal of the main control processing module (4) is electrically connected to the controlled terminal of the environmental active adjustment module (5). The communication terminal of the main control processing module (4) is bidirectionally connected to the wireless communication module (6). The environmental sensing module (2) uses a combination of a temperature and humidity sensor (21) and a volatile organic compound sensor to collect real-time temperature and humidity data and air quality data inside the helmet. The user status monitoring module (3) is used to collect data on the intensity of user exercise activities and physiological status. The main control processing module (4) has a built-in environmental comfort prediction algorithm and adaptive control strategy to receive monitoring data and output control instructions. The environmental active adjustment module (5) is used to complete the ventilation, temperature adjustment, deodorization and antibacterial operations inside the helmet according to the control instructions.

2. The smart helmet with internal environment regulation function according to claim 1, characterized in that, The user status monitoring module (3) includes a photoelectric heart rate sensor and a motion posture sensor. The photoelectric heart rate sensor is used to collect the user's heart rate physiological data, and the motion posture sensor is used to collect the user's cycling speed and motion amplitude data, and together calculate the user's real-time activity intensity.

3. The smart helmet with internal environment regulation function according to claim 1, characterized in that, The active environmental adjustment module (5) includes a dual-channel miniature brushless DC fan, a semiconductor cooling and heating component, and a nano-silver antibacterial and deodorizing module. The dual-channel miniature brushless DC fan is equipped with an independent air intake channel and an exhaust channel. The semiconductor cooling and heating component is fitted to the inner wall of the helmet liner. The nano-silver antibacterial and deodorizing module is embedded inside the helmet vent.

4. The smart helmet with internal environment regulation function according to claim 2, characterized in that, The main control processing module (4) adopts a microcontroller. The microcontroller has a built-in data fusion algorithm to perform multi-dimensional fusion of helmet internal environment data, user heart rate data, and motion posture data to predict the trend of changes in helmet internal environment comfort.

5. The smart helmet with internal environment regulation function according to claim 3, characterized in that, The dual-duct micro brushless DC fan is a low-noise, high-speed micro fan that supports stepless speed adjustment and can switch between three working modes—low-speed ventilation, high-speed air exchange, and silent resistance reduction—according to the instructions of the main control processing module (4).

6. The smart helmet with internal environment regulation function according to claim 1, characterized in that, The wireless communication module (6) adopts a Bluetooth communication module. The Bluetooth communication module establishes a two-way wireless connection with the mobile APP to upload helmet environmental monitoring data and user movement data, and at the same time receive personalized control parameters sent by the mobile APP.

7. The smart helmet with internal environment regulation function according to claim 4, characterized in that, The microcontroller has a built-in adaptive ventilation control strategy that switches the working mode according to the user's movement status. In low-speed cruising mode, it starts the full-speed cooling and ventilation mode, and in high-speed riding mode, it automatically reduces the fan speed and optimizes the air duct resistance to achieve noise reduction and resistance reduction adaptation.

8. The smart helmet with internal environment regulation function according to claim 5, characterized in that, The semiconductor cooling and heating component is equipped with a miniature thermally conductive silicone pad and a heat insulation cotton layer. The thermally conductive silicone pad is attached to the heat exchange surface of the semiconductor cooling and heating component, and the heat insulation cotton layer isolates the component from the helmet shell, thereby achieving precise thermal management and avoiding heat loss in extreme environments.

9. The smart helmet with internal environment regulation function according to claim 6, characterized in that, The mobile app has built-in data statistics and visualization functions, which can generate daily or weekly reports on the helmet's internal environment. It also supports users to customize temperature thresholds, humidity thresholds, and ventilation speed thresholds to achieve personalized environmental control settings.

10. The smart helmet with internal environment regulation function according to claim 1, characterized in that, The temperature and humidity sensor (21) is evenly distributed in three areas: the forehead, the top of the head, and the back of the head of the helmet, so as to realize the full-area temperature and humidity collection inside the helmet, avoid the problem of single-point monitoring data deviation, and ensure the accuracy of environmental monitoring.

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