A three-dimensional frame-based automobile cabin adaptive temperature control system

Abstract

The application relates to a three-dimensional frame-based adaptive temperature regulating system for a vehicle cabin, which comprises a multi-dimensional data acquisition module for collecting environmental parameters inside and outside the cabin and physiological state data of a driver; an adaptive temperature regulating calculation module for obtaining optimal temperature for the thermal comfort of the driver and performing real-time temperature regulation based on an improved PMV adaptive temperature regulating algorithm and the environmental parameters and the driver state data obtained from the multi-dimensional data acquisition module; and a temperature difference energy collection module for generating and collecting energy through the Seebeck effect by using the temperature difference between the inside and the outside of the cabin. Compared with the prior art, the application combines subjective dimensions, objective dimensions and historical dimensions, establishes the adaptive temperature regulating system for the cabin environment based on the improved PMV thermal comfort model, shortens the time for repeatedly regulating temperature in the traditional simple subjective mode under the premise of ensuring the comfort, and generates and collects energy based on the temperature difference effect by using the temperature difference between the inside and the outside of the cabin.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control of vehicle air conditioning, and in particular to a three-dimensional adaptive temperature control system for a cabin of a new energy vehicle. Background Art

[0002] With the advent of the new energy vehicle era, the automobile product structure is transforming towards "green, low-carbon, intelligent and connected", the industrial value chain is "increasing in total volume and shifting its center of gravity backward", and the industrial ecosystem is "open source innovation and open integration".

[0003] The traditional cabin air conditioning temperature control method mainly relies on people's subjective feelings. This subjective temperature control method has problems such as blind temperature control range, poor ambient temperature adaptability, and long temperature control transition time, resulting in unnecessary energy waste.

[0004] Chinese patent application CN114801649A discloses a vehicle air conditioning air supply control scheme based on user thermal demand. This scheme primarily calculates thermal demand based on a PMV model and sequentially adjusts the cabin temperature. However, it ignores the impact of internal and external cabin temperatures and fails to consider passengers' subjective adjustment preferences and needs. Consequently, the temperature adjustment lacks personalization and real-time performance. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a car cabin adaptive temperature control system based on a three-dimensional framework.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] An automobile cabin adaptive temperature control system, characterized in that the system comprises:

[0008] Multi-dimensional data acquisition module, used to collect environmental parameters inside and outside the cabin and the driver's physiological status data;

[0009] The adaptive temperature adjustment calculation module uses the environmental parameters and driver status data obtained by the multi-dimensional data acquisition module and the improved PMV adaptive temperature adjustment algorithm to obtain the optimal temperature for the driver's thermal comfort and perform real-time temperature adjustment;

[0010] The temperature difference energy harvesting module uses the temperature difference between the inside and outside of the cabin to generate and harvest energy through the Seebeck effect.

[0011] As a preferred technical solution, the multi-dimensional data acquisition module includes:

[0012] Environmental parameter sensors: used to measure temperature, humidity, wind speed, radiation temperature and air pressure inside and outside the cabin;

[0013] Driver state sensors: to monitor the physiological state of the driver, including body temperature and heart rate;

[0014] Clothing thermal resistance monitoring: to assess the thermal resistance of the driver's clothing;

[0015] Health status monitoring: to identify the health status of the driver.

[0016] As a preferred technical solution, the input component of the multi-modal data acquisition module includes:

[0017] Touch operation identifier: including physical buttons and touch screen inputs, for temperature adjustment and cabin control functions;

[0018] Voice recognition subsystem: using a microphone array to receive the driver's voice instructions and perform recognition and analysis, converting to temperature adjustment operations;

[0019] Gesture recognition subsystem: capturing and recognizing the driver's gestures through on-board cameras or sensors, converting specific gestures to temperature adjustment instructions;

[0020] Face recognition subsystem: to identify the driver's identity and monitor signs of fatigue, including yawning and drooping eyelids;

[0021] Eye movement recognition subsystem: to track the driver's gaze and pupil activity, assess the degree of concentration, and assist in fatigue monitoring.

[0022] As a preferred technical solution, the adaptive temperature regulation calculation module is based on an improved PMV adaptive temperature regulation algorithm

[0023] Initialize environmental and physiological parameters;

[0024] Obtain environmental data inside and outside the cabin, physiological data of the driver, and temperature adjustment instructions read by the multi-dimensional data acquisition module;

[0025] Based on the thermal comfort temperature adjustment value calculated by the improved PMV;

[0026] Adjust the cabin temperature according to the thermal comfort temperature adjustment value;

[0027] Enter a feedback loop, continuously monitor and adjust the collected data to ensure the comfort of the driver.

[0028] As a preferred technical solution, the improved PMV is as follows:

[0029] PMV adjusted = PMV base + α × (DriverInput - PMV base ) + β × (EnviroAdjustment)

[0030] Among them: PMV base is the baseline PMV value calculated according to the standard PMV formula; α is the first adjustment coefficient, which is used to quantify the impact of the driver's temperature control command on PMV; DriverInput is the quantified value of the temperature control command input by the driver through voice, gesture, touch, facial recognition, or eye tracking; β is the second adjustment coefficient, which is used to quantify the impact of environmental parameter adjustments on PMV; EnviroAdjustment is the comprehensive adjustment factor for the environmental parameters inside and outside the cabin:

[0031] EnviroAdjustment=w1×(t a，in -t a，out )+w2×(φ in -φ out )+w3×(v in -v out )+w4×(T rad，in -T rad，ovt )+w5×(p in -p out )

[0032] Among them: W1, w2, w3, W4, w5 are weight coefficients used to adjust the impact of different environmental parameters on comfort; t a，in 、φ in 、v in 、T rad，in 、p in Respectively represents the cabin air temperature, humidity, wind speed, mean radiant temperature and air pressure; t a，out 、φ out 、v out 、T rad，out 、p out They represent the cabin external air temperature, humidity, wind speed, mean radiant temperature and air pressure respectively.

[0033] As a preferred technical solution, the improved PMV is based on the driver's personal parameters including body temperature, heart rate, clothing type and thickness to adjust metabolic rate M and clothing thermal resistance I cl :

[0034] M adjusted =M+δM

[0035] I cl，adjusted =I cl +δI cl

[0036] Among them, 6M and δI cl They are the changes in metabolic rate and clothing thermal resistance adjusted according to the driver's body temperature, heart rate and clothing.

[0037] As a preferred technical solution, the temperature difference energy harvesting module adopts high-performance thermoelectric materials, including bismuth telluride Bi2Te3 and lead telluride PbTe;

[0038] The thermoelectric materials are arranged inside and outside the cabin, including at the edges of windows, near door seals, or on the partition between the cabin and the engine compartment.

[0039] As an optimal technical solution, the electric energy generated by the thermoelectric power generation unit in the thermoelectric energy collection module is used to provide electric energy for the information collection sensor and temperature control part, or to supply the vehicle's 12V electrical system or to charge the battery.

[0040] As an optimal technical solution, when adjusting the cabin temperature, the electricity generated by the temperature difference energy harvesting module is used as the preferred energy source. The electricity from the main battery is only used when the electricity generated by the temperature difference energy harvesting module is insufficient to meet the demand.

[0041] As a preferred technical solution, the temperature difference energy harvesting module solution also includes:

[0042] User interface integration: Displays the energy generation status of the thermoelectric energy harvesting module in real time on the vehicle information display, including the current energy generated, cumulative energy production, and energy conversion efficiency. Energy consumption impact feedback: Provides feedback to the driver on how temperature adjustment behavior affects the energy recovery efficiency of the thermoelectric energy harvesting module.

[0043] Prediction and Maintenance: The system uses data collected by the multi-dimensional data acquisition module to conduct real-time monitoring and predictive analysis of the operating status of the temperature difference energy harvesting module to predict maintenance needs. When it is predicted that the temperature difference energy harvesting module requires maintenance, the user interface will issue a reminder to the driver.

[0044] Energy efficiency evaluation: Based on the energy generation of the temperature difference energy harvesting module, the overall energy efficiency is evaluated and the system operation strategy is adjusted to improve the overall energy efficiency ratio;

[0045] Personalized energy-saving mode: Provides personalized energy-saving mode options, allowing the driver to select different temperature regulation strategies based on the energy generation of the temperature difference energy harvesting module;

[0046] Intelligent learning: By learning the driver's temperature adjustment habits and the energy generation pattern of the temperature difference energy harvesting module, it automatically adjusts the strategy to optimize energy use;

[0047] Safety and monitoring integration: Ensure that the operation of the temperature-differential energy harvesting module does not affect the vehicle's safety performance, and integrate the monitoring of the temperature-differential energy harvesting module into the vehicle's central monitoring system. Based on the environmental data collected by the multi-dimensional data acquisition module, the operating status of the temperature-differential energy harvesting module is adjusted to adapt to different driving environments.

[0048] Energy utilization feedback loop: Establish a feedback mechanism to feed back the energy generation of the temperature difference energy harvesting module to the adaptive temperature regulation calculation module for further optimization of the temperature regulation algorithm; through continuous monitoring and optimization, ensure that the collaborative operation of the temperature difference energy harvesting module and the adaptive temperature regulation calculation module always operates at the highest efficiency.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1) The present invention combines subjective, objective and historical dimensions, based on the PMV thermal comfort model, and utilizes the Internet of Things and big data technologies to establish an adaptive temperature control system for the cabin environment, thereby achieving intelligent and green temperature control.

[0051] 2) While ensuring comfort, this solution shortens the time required for traditional, purely subjective, repeated temperature adjustments, thereby reducing energy consumption. Energy is generated and collected based on the temperature difference effect, and the temperature difference between inside and outside the cabin is used to generate electricity, enhancing energy-saving design.

[0052] 3) Energy recovery: The thermoelectric energy harvesting system (TEHS) designed in this invention provides an energy recovery method that effectively utilizes the temperature difference between the inside and outside of the cabin, thereby improving the energy efficiency of the vehicle.

[0053] 4) System Integration: The temperature difference energy harvesting system (TEHS) is integrated with other systems such as the vehicle's heating, ventilation, and air conditioning (HVAC) and battery management system to achieve cross-system collaborative optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of an automobile cabin adaptive temperature control system based on a three-dimensional framework according to the present invention;

[0055] Figure 2 Schematic diagram of the multi-dimensional data acquisition module of the present invention;

[0056] Figure 3 This is a flow chart of the adaptive temperature adjustment algorithm of the present invention;

[0057] Figure 4The figure is a schematic diagram of the working process of a three-dimensional framework-based automobile cabin adaptive temperature control system of the present invention. DETAILED DESCRIPTION

[0058] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0059] Example 1

[0060] As one embodiment of the present invention, this embodiment provides a car cabin adaptive temperature control system based on a three-dimensional framework, such as Figure 1 As shown in the figure, the system architecture is as follows:

[0061] Multidimensional Data Acquisition Module (MDAM): responsible for collecting environmental parameters inside and outside the cabin and the driver's physiological status data.

[0062] Adaptive Temperature Regulation Algorithm (ATRA): Based on the Predicted Mean Vote (PMV) thermal comfort model and combined with data collected by MDAM, it performs real-time temperature regulation.

[0063] Thermoelectric Energy Harvesting System (TEHS): Utilizes the Seebeck effect to harvest temperature energy from inside and outside the cabin through thermoelectric power generation technology.

[0064] The system's workflow is as follows:

[0065] When the driver enters the cockpit, the multi-dimensional data acquisition module (MDAM) starts to collect environmental parameters inside and outside the cabin, such as temperature, humidity, wind speed, radiant temperature and air pressure, as well as the driver's physiological state, such as heart rate, skin temperature and eye movements.

[0066] The adaptive temperature control algorithm (ATRA) processes data collected by the multi-dimensional data acquisition module (MDAM) to calculate the optimal temperature setting for the driver's thermal comfort. It then automatically adjusts the cabin temperature via the heating, ventilation, and air conditioning (HVAC) control unit.

[0067] The temperature difference energy harvesting system TEHS operates under the temperature difference between the inside and outside of the cabin, generating electricity through thermoelectric materials. This electricity can be used to supplement the 12V electrical system in the car or stored in the on-board battery.

[0068] Collaboration between functional modules

[0069] Close collaboration between MDAM, ATRA and TEHS ensures thermal comfort and energy efficiency in the cabin environment.

[0070] ATRA adjusts temperature settings in real time based on MDAM data, while also taking into account TEHS's energy recovery to optimize overall energy efficiency.

[0071] 1. Multidimensional Data Acquisition Module (MDAM): This module collects environmental parameters inside and outside the cabin and the driver's physiological status data. It mainly includes:

[0072] Environmental parameter sensors: measure temperature, humidity, wind speed, radiant temperature and air pressure inside and outside the cabin.

[0073] Driver status sensor: monitors the driver's physiological status, such as body temperature, heart rate, etc.

[0074] Clothing Thermal Resistance Monitoring: Evaluates the thermal resistance of the driver's clothing to influence temperature regulation calculations.

[0075] Health status monitoring: Identifying the driver's health status, such as a cold, which may affect their perception of temperature.

[0076] The input components of the multimodal data acquisition module include:

[0077] Touch action recognizers: Physical buttons and touchscreen inputs for traditional climate control and other cabin control functions.

[0078] Voice Recognition System (VRS): Utilizes a microphone array to receive the driver's voice commands, which are then recognized and analyzed by the VRS and converted into temperature control operations.

[0079] Gesture Recognition System (GRS): Captures and recognizes the driver's gestures through on-board cameras or sensors, and converts specific gestures into temperature adjustment instructions.

[0080] Facial Recognition System (FRS): Used to identify the driver and monitor signs of fatigue, such as yawning and drooping eyelids.

[0081] Eye Tracking System (ETS): Track the driver's gaze and pupil activity, assess the degree of concentration, assist fatigue monitoring.

[0082] The multi-modal data input component information parameters are as follows: touch operation data: input data collected directly from physical buttons or touch screens; voice instructions: temperature adjustment instructions obtained by VRS analysis; gesture data: gestures and their corresponding temperature adjustment operations identified by GRS; facial feature data: facial expressions and features collected by FRS for fatigue monitoring; eye movement data: eye movement information tracked by ETS to assist in assessing the driver's state.

[0083] The obtained information parameters include: outside air temperature, humidity, wind speed, mean radiant temperature, air pressure in the cabin; inside air temperature, humidity, wind speed, mean radiant temperature, air pressure in the cabin; driver body temperature, heart rate, clothing type and thickness; driver temperature adjustment instructions: voice, gesture, touch, facial recognition, eye tracking, etc.

[0084] Among them, the environmental parameters are used to evaluate the thermal load and comfort inside and outside the cabin; the driver's physiological state data are used for individualized temperature adjustment.

[0085] 2、Adaptive Temperature Regulation Algorithm (ATRA): According to the PMV thermal comfort model, combined with the data collected by MDAM, real-time temperature regulation is carried out, which specifically includes:

[0086] PMV model implementation: Calculate the ideal cabin temperature according to the PMV formula.

[0087] Data processing: Integrate the environmental parameters and driver state provided by MDAM to calculate the temperature adjustment.

[0088] PMV (Predicted Mean Vote) thermal comfort evaluation model is a calculation model for evaluating human thermal comfort, which is adopted and standardized by the International Organization for Standardization (ISO) as ISO 7730 standard. PMV model considers factors such as human metabolic rate (M), environmental temperature (ta), mean radiant temperature (tr), relative humidity (rh), air flow rate (v), and clothing thermal resistance (Icl).

[0089] The standard PMV formula is as follows

[0090] PMV = [0.303 × exp (-0.036 × M) + 0.0275] × TL

[0091] Where: M is the human metabolic rate (unit: met); TL is the abbreviation of thermal load, which represents the difference between the heat produced by the human body and the heat dissipated to the outside world.

[0092] Furthermore, TL can be calculated according to the following formula:

[0093]

[0094] Where: M0 and W0 are the values ​​of human metabolic rate and external mechanical work in a comfortable thermal equilibrium state, respectively; P a is the partial pressure of water vapor (unit: kPa); t a is the air temperature (unit: ℃); f cl is the clothing area coefficient; T cl is the outer surface temperature of the garment (unit: °C); T r is the mean radiation temperature (unit: °C); h c Is the convective heat transfer coefficient (unit: W / (m 2 ·K)).

[0095] The present invention comprehensively considers the environmental parameters inside and outside the cabin and the driver's personal parameters into the PMV model, and improves the standard PMV formula. The improved PMV formula is:

[0096] PMV adjusted =PMV base +α×(DriverInput-PMV base )+β×(EnviroAdjustment)

[0097] Among them: PMV base It is the baseline PMV value calculated according to the standard PMV formula; α is an adjustment coefficient used to quantify the impact of the driver's temperature control command on PMV; DriverInput is the quantified value of the temperature control command input by the driver through voice, gesture, touch, facial recognition, eye tracking, etc.; β is another adjustment coefficient used to quantify the impact of environmental parameter adjustment on PMV; EnviroAdjustment is a comprehensive adjustment factor for the environmental parameters inside and outside the cabin, which can be adjusted according to the differences between the internal and external environments.

[0098] EnviroAdjustment=w1×(t a，in -t a，out )+w2×(φ in -φ out )+w3×(v in -v out )+w4×(T rad，in -T rad，out )+w5×(pin -p out )

[0099] In EnviroAdjustment: w1, w2, w3, w4, w5 are weight coefficients used to adjust the impact of different environmental parameters on comfort; t a，in ,φ in , v in , T rad，in , p in Respectively represents the cabin air temperature, humidity, wind speed, mean radiant temperature and air pressure; t a，out ,φ out , v out , T rad，out , p out They represent the cabin external air temperature, humidity, wind speed, mean radiant temperature and air pressure respectively.

[0100] In addition, the driver's personal parameters, such as body temperature, heart rate, clothing type and thickness, can be adjusted by adjusting the metabolic rate M and clothing thermal resistance I cl To be reflected in the PMV formula:

[0101] M adjusted =M+δM

[0102] I cl，adjusted =I cl +δI cl

[0103] Among them, δM and δI cl They are the changes in metabolic rate and clothing thermal resistance adjusted according to the driver's body temperature, heart rate and clothing.

[0104] Based on the improved PMV (Predicted Mean Vote) thermal comfort evaluation model, such as Figure 3 As shown in the figure, the process and algorithm of the Adaptive Temperature Regulation Algorithm (ATRA) are as follows:

[0105] First, initialize the environmental and physiological parameters;

[0106] Then, it collects environmental data inside and outside the cabin, as well as the driver's physiological data, and reads the driver's temperature control instructions;

[0107] All data are taken into account to calculate PMV base and PMV adjusted ;

[0108] According to PMV adjustedThe value of PMV determines whether the HVAC system needs to be adjusted and how to adjust it to maintain thermal comfort in the cabin

[0109] When PMV adjusted is close to 0, it indicates that the temperature is suitable and no adjustment is needed, the HVAC system maintains the current temperature;

[0110] When PMV adjusted is less than 0, it indicates that the temperature is too low, the cabin temperature is adjusted higher by the HVAC system;

[0111] When PMV adjusted is greater than 0, it indicates that the temperature is too high, the cabin temperature is adjusted lower by the HVAC system;

[0112] Finally, the system enters a feedback loop, continuously monitoring and adjusting to ensure the comfort of the driver.

[0113] 3. Thermoelectric Energy Harvesting System (TEHS): The Thermoelectric Energy Harvesting System (TEHS) is an innovative energy recovery technology designed to generate electricity through the Seebeck effect using the temperature difference between the inside and outside of the cabin. This system not only improves the energy utilization efficiency of the car, but also provides additional energy supply for the electrical system of the vehicle. The system composition includes:

[0114] Thermoelectric materials: Select high-performance thermoelectric materials such as bismuth telluride (Bi2Te3) or lead telluride (PbTe), which have high Seebeck coefficients and good thermoelectric conversion efficiency.

[0115] Thermoelectric Generator (TEG): Design the Thermoelectric Generator (TEG), including the arrangement of thermoelectric materials, electrode connection and thermal management. Material arrangement: Arrange the thermoelectric materials in appropriate locations inside and outside the cabin, such as the edges of the windows, near the door seals or the partition between the cabin and the engine compartment. Thermal management: Ensure that the hot side (high temperature end) and cold side (low temperature end) of the thermoelectric material can effectively absorb and dissipate heat, which may require additional insulation or heat dissipation measures.

[0116] Design the Thermoelectric Generator (TEG) to adapt to the environment of the car cabin, including size, shape and installation method. Optimize the design of the Thermoelectric Generator (TEG) to maximize energy conversion efficiency, including the arrangement of thermoelectric materials, the selection of contact materials and the minimization of thermal resistance.

[0117] The Thermoelectric Energy Harvesting System (TEHS) monitors the temperature inside and outside the cabin in real time to obtain the actual temperature difference; according to the monitored temperature difference, adjust the working state of the Thermoelectric Generator (TEG) to optimize electricity generation.

[0118] The power management of the temperature difference energy harvesting system specifically includes:

[0119] Power harvesting: Collecting the electricity generated by the thermoelectric power generation unit.

[0120] Power distribution: Design an intelligent energy management system to automatically distribute and optimize the use of electrical energy, such as providing power to the information collection sensors and temperature control parts mentioned above, or supplying power to the vehicle's 12V electrical system or charging the battery.

[0121] Temperature Difference Energy Harvesting System TEHS Extension Description:

[0122] 1. Energy priority management

[0123] Priority setting: ATRA uses the electricity generated by TEHS as the preferred energy source when adjusting the cabin temperature. It only uses the electricity from the main battery when the electricity generated by TEHS is not enough to meet the demand.

[0124] 2. User Interface Integration

[0125] Real-time data display: The energy generation status of TEHS is displayed in real time on the vehicle information display screen, including the current energy generated, cumulative energy output and energy conversion efficiency.

[0126] Energy Consumption Impact Feedback: Provides feedback to the driver showing how their temperature regulation behavior affects the energy recovery efficiency of the TEHS.

[0127] 3. Intelligent prediction and maintenance

[0128] Predictive analysis: Leveraging data collected by MDAM and the algorithmic capabilities of ATRA, real-time monitoring and predictive analysis of the operating status of TEHS are performed to predict maintenance needs.

[0129] Maintenance reminder system: When the system predicts that the TEHS may need maintenance, it will send a reminder to the driver through the user interface, suggesting regular inspection or component replacement.

[0130] 4. System-level energy efficiency optimization

[0131] Energy efficiency assessment: ATRA evaluates the overall energy efficiency of the TEHS based on its energy generation and adjusts the HVAC system's operating strategy when necessary to improve the overall energy efficiency ratio.

[0132] 5. Personalized energy-saving mode

[0133] Energy-saving mode selection: Provides personalized energy-saving mode options, allowing the driver to select different temperature adjustment strategies based on the energy generation of TEHS.

[0134] Intelligent Learning: ATRA automatically adjusts strategies to optimize energy usage by learning the driver's temperature regulation habits and the energy generation patterns of the TEHS.

[0135] 6. Security and monitoring integration

[0136] Safety monitoring: Ensure that the operation of TEHS does not affect the safety performance of the vehicle, and integrate the monitoring of TEHS into the vehicle's central monitoring system.

[0137] Environmental adaptability: ATRA intelligently adjusts the working status of TEHS based on the environmental data collected by MDAM to adapt to different driving environments.

[0138] 7. Energy Utilization Feedback Loop

[0139] Feedback mechanism: Establish a feedback mechanism to feed back the energy generation of TEHS to ATRA for further optimization of the temperature regulation algorithm.

[0140] Continuous optimization: Through continuous monitoring and optimization, we ensure that the collaborative work of TEHS and ATRA always operates at the highest efficiency.

[0141] The workflow of the automobile cabin adaptive temperature control system based on the three-dimensional framework provided by the present invention is as follows: Figure 4 shown.

[0142] The present invention no longer relies solely on the traditional method of manually adjusting the cabin temperature multiple times to achieve a comfortable temperature by personal feeling, but instead achieves this through:

[0143] 1. Subjective temperature control information

[0144] The driver performs subjective temperature adjustment after entering the vehicle cabin, including temperature adjustment through voice recognition, manual button adjustment, and gestures to set some commonly used temperatures in advance.

[0145] 2. Objective temperature control information

[0146] Information on the environment parameters inside and outside the cabin, such as Figure 2 The displayed air temperature inside and outside the cabin, the air humidity inside and outside the cabin, the average radiant temperature inside and outside the cabin, the relative wind speed inside and outside the cabin, and the air pressure inside and outside the cabin;

[0147] Driver status parameter information, including clothing information (used to estimate thermal resistance) and health status, can be input through mobile phones / HMI terminals / wearable devices; and facial recognition in the cabin can be used to monitor the driver's fatigue status at any time.

[0148] 3. Historical data information

[0149] Including previous temperature settings, the comprehensive temperature that meets the driver's thermal comfort is obtained and real-time intelligent temperature adjustment is achieved.

[0150] Thermal comfort is measured using the PMV thermal comfort model constructed by PMV. The body's thermal sensation is primarily related to its thermal balance; thermal equilibrium occurs when the amount of heat generated within the body equals the amount of heat consumed in the environment. Factors influencing thermal balance include both human and environmental factors. The PMV thermal comfort model integrates both human and environmental variables that influence thermal comfort.

[0151] Energy saving: First, temperature control can shorten the time of traditional subjective repeated temperature control and reduce energy consumption while ensuring comfort; second, it can utilize the temperature difference between the inside and outside of the cabin to generate and collect energy based on the temperature difference effect.

[0152] This program provides solutions for suppliers of thermal management systems for new energy vehicle components. It brings a comfortable and worry-free driving experience to drivers and passengers through energy-saving and intelligent design, promotes energy conservation and emission reduction through scientific and technological means, and creates green value with a systematic concept and technology leadership.

[0153] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A car cabin adaptive temperature control system based on a three-dimensional framework, characterized in that: The system comprises: Multi-dimensional data acquisition module, used to collect environmental parameters inside and outside the cabin and the driver's physiological status data; The adaptive temperature adjustment calculation module uses the environmental parameters and driver status data obtained by the multi-dimensional data acquisition module and, based on the improved PMV adaptive temperature adjustment algorithm, obtains the optimal temperature for the driver's thermal comfort and performs real-time temperature adjustment. The process of the improved PMV adaptive temperature adjustment algorithm is as follows: Initialize environmental and physiological parameters; Acquire the environmental data inside and outside the cabin, the driver's physiological data, and the driver's temperature control instructions collected by the multi-dimensional data acquisition module; The thermal comfort temperature adjustment value is obtained based on the improved PMV calculation: in: is the baseline PMV value calculated according to the standard PMV formula; is the first adjustment coefficient, which is used to quantify the impact of the driver's temperature control command on PMV; It is the quantified value of the temperature control command input by the driver through voice, gesture, touch, facial recognition, and eye tracking; is the second adjustment coefficient, which is used to quantify the impact of environmental parameter adjustment on PMV; is the comprehensive adjustment factor of the environmental parameters inside and outside the cabin: in: is the weight coefficient, which is used to adjust the impact of different environmental parameters on comfort; 、 Respectively represent the cabin air temperature, humidity, wind speed, mean radiant temperature and air pressure; Represents the cabin's external air temperature, humidity, wind speed, mean radiant temperature, and air pressure respectively; the improved PMV is based on the driver's personal parameters including body temperature, heart rate, clothing type and thickness to adjust metabolic rate Thermal resistance of clothing : in, and They are the changes in metabolic rate and clothing thermal resistance adjusted according to the driver's body temperature, heart rate and clothing; Adjust the cabin temperature according to the thermal comfort temperature adjustment value; Entering a feedback loop to continuously monitor collected data and make adjustments to ensure driver comfort; The temperature difference energy harvesting module uses the temperature difference between the inside and outside of the cabin to generate and harvest energy through the Seebeck effect.

2. The automobile cabin adaptive temperature control system based on a three-dimensional framework according to claim 1, characterized in that: The multidimensional data acquisition module includes: Environmental parameter sensors: used to measure temperature, humidity, wind speed, radiation temperature and air pressure inside and outside the cabin; Driver status sensor: used to monitor the driver's physiological status, including body temperature and heart rate; Clothing thermal resistance monitoring: used to evaluate the thermal resistance of the driver's clothing; Health status monitoring: used to identify the driver's health status.

3. The automobile cabin adaptive temperature control system based on a three-dimensional framework according to claim 1, characterized in that: The input component of the multidimensional data acquisition module includes: Touch operation recognizers: including physical buttons and touch screen inputs for temperature adjustment and cabin control functions; Voice recognition subsystem: uses a microphone array to receive the driver's voice commands, identify and analyze them, and convert them into temperature control operations; Gesture recognition subsystem: Captures and recognizes the driver's gestures through on-board cameras or sensors, converting specific gestures into temperature adjustment instructions; Facial recognition subsystem: used to identify the driver and monitor signs of fatigue, including yawning and drooping eyelids; Eye movement recognition subsystem: used to track the driver's line of sight and pupil activity, assess the driver's concentration level, and assist in fatigue monitoring.

4. The automobile cabin adaptive temperature control system based on a three-dimensional framework according to claim 1, characterized in that: The temperature difference energy collection module uses high-performance thermoelectric materials, including bismuth telluride Bi2Te3 and lead telluride PbTe; The thermoelectric materials are arranged inside and outside the cabin, including at the edges of windows, near door seals, or on the partition between the cabin and the engine compartment.

5. The automobile cabin adaptive temperature control system based on a three-dimensional framework according to claim 4, characterized in that: The electric energy generated by the thermoelectric power generation unit in the thermoelectric energy collection module is used to provide electric energy for the information collection sensor and the temperature control part, or to supply the vehicle's 12V electrical system or to charge the battery.

6. The automobile cabin adaptive temperature control system based on a three-dimensional framework according to claim 4, characterized in that: When adjusting the cabin temperature, the electricity generated by the temperature difference energy harvesting module is used as the preferred energy source. The electricity from the main battery is only used when the electricity generated by the temperature difference energy harvesting module is not enough to meet the demand.

7. The automobile cabin adaptive temperature control system based on a three-dimensional framework according to claim 4, characterized in that: The temperature difference energy harvesting module solution also includes: User interface integration: Displays the energy generation status of the thermoelectric energy harvesting module in real time on the vehicle information display, including the current energy generated, cumulative energy production, and energy conversion efficiency. Energy consumption impact feedback: Provides feedback to the driver on how temperature adjustment behavior affects the energy recovery efficiency of the thermoelectric energy harvesting module. Prediction and Maintenance: The system uses data collected by the multi-dimensional data acquisition module to conduct real-time monitoring and predictive analysis of the operating status of the temperature difference energy harvesting module to predict maintenance needs. When it is predicted that the temperature difference energy harvesting module requires maintenance, the user interface will issue a reminder to the driver. Energy efficiency evaluation: Based on the energy generation of the temperature difference energy harvesting module, the overall energy efficiency is evaluated and the system operation strategy is adjusted to improve the overall energy efficiency ratio; Personalized energy-saving mode: Provides personalized energy-saving mode options, allowing the driver to select different temperature regulation strategies based on the energy generation of the temperature difference energy harvesting module; Intelligent learning: By learning the driver's temperature adjustment habits and the energy generation pattern of the temperature difference energy harvesting module, it automatically adjusts the strategy to optimize energy use; Safety and monitoring integration: Ensure that the operation of the temperature-differential energy harvesting module does not affect the vehicle's safety performance, and integrate the monitoring of the temperature-differential energy harvesting module into the vehicle's central monitoring system. Based on the environmental data collected by the multi-dimensional data acquisition module, the operating status of the temperature-differential energy harvesting module is adjusted to adapt to different driving environments. Energy utilization feedback loop: Establish a feedback mechanism to feed back the energy generation of the temperature difference energy harvesting module to the adaptive temperature regulation calculation module for further optimization of the temperature regulation algorithm; through continuous monitoring and optimization, ensure that the collaborative operation of the temperature difference energy harvesting module and the adaptive temperature regulation calculation module always operates at the highest efficiency.

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