A method for evaluating the thermal comfort of automotive air conditioning
By using a sensor array and an improved PMV model, combined with passenger information, the air conditioning mode is dynamically adjusted, solving the problem of incomplete monitoring of in-vehicle environmental parameters in existing automotive air conditioning systems. This enables personalized thermal comfort control and enhances the thermal comfort experience for passengers.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NORTHEAST GASOLINEEUM UNIV
- Filing Date
- 2026-03-27
- Publication Date
- 2026-05-26
AI Technical Summary
Existing automotive air conditioning systems do not monitor all parameters of the in-vehicle environment comprehensively enough, neglecting factors such as humidity, wind speed and passenger body temperature, resulting in insufficient thermal comfort experience for passengers and an inability to provide personalized thermal comfort control.
By collecting in-vehicle environmental parameters in real time through a sensor array and combining them with passenger personal information, the air conditioning operating mode is dynamically adjusted using an improved PMV model, providing a personalized thermal comfort evaluation method, including data collection, information input, index calculation, and mode adjustment.
It achieves comprehensive monitoring of in-vehicle environmental parameters, performs precise calculations based on individual passenger differences, ensures that each passenger enjoys the most suitable in-vehicle temperature, improves the passenger's thermal comfort experience, and can dynamically adjust the air conditioning mode according to vehicle status and external environment to provide the best thermal comfort.
Smart Images
Figure CN122078129A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of automotive air conditioning system technology, specifically to a method for evaluating the thermal comfort of automotive air conditioning systems. Background Technology
[0002] Currently, automotive air conditioning systems, as a key component for improving passenger comfort, are widely used in various types of vehicles.
[0003] However, existing automotive air conditioning systems have some limitations, mainly in their insufficient monitoring of in-vehicle environmental parameters and lack of attention to passengers' personalized needs. Most automotive air conditioning systems rely solely on simple temperature control logic, neglecting factors crucial to thermal comfort such as humidity, airflow, and even passenger body temperature. Furthermore, due to the lack of consideration for passengers' basic information, existing air conditioning systems struggle to provide a truly individualized thermal comfort experience. This means that although the air conditioning may be operating, passengers may feel too hot or too cold because the aforementioned details are not taken into account, thus reducing the comfort of the ride. Therefore, we propose a method for evaluating the thermal comfort of automotive air conditioning systems. Summary of the Invention
[0004] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a method for evaluating the thermal comfort of automotive air conditioning systems. By combining passenger personal information and in-vehicle environmental parameters, and utilizing an improved PMV model to dynamically adjust the air conditioning operating mode, it offers a more personalized and efficient method for evaluating automotive air conditioning thermal comfort. This addresses some limitations of existing automotive air conditioning systems, primarily their insufficient monitoring of in-vehicle environmental parameters and inadequate attention to passengers' personalized needs. Most automotive air conditioning systems rely solely on simple temperature control logic, neglecting crucial factors for thermal comfort such as humidity, wind speed, and even passenger body temperature. Furthermore, due to the lack of consideration for basic passenger information, existing air conditioning systems struggle to provide a truly individualized thermal comfort experience.
[0005] (II) Technical Solution To achieve the aforementioned goal of providing a more personalized and efficient method for evaluating automotive air conditioning thermal comfort by combining passenger personal information and in-vehicle environmental parameters and dynamically adjusting the air conditioning operating mode using an improved PMV model, this invention provides the following technical solution: A method for evaluating the thermal comfort of automotive air conditioning, comprising the following steps: S1. Data Acquisition: Real-time acquisition of in-vehicle environmental parameters through multiple sensors; S2. Information Input: Obtain passenger personal information, including age, gender, and weight; S3. Index Calculation: Input the collected data into the human thermal comfort model and evaluate the performance of the car air conditioner based on the thermal comfort index; S4. Mode Adjustment: Dynamically adjusts the air conditioner's operating mode based on calculation results; S5. Data Recording: Record passenger feedback and system operation data.
[0006] Preferably, the in-vehicle environmental parameters include the in-vehicle temperature. Ti Humidity inside the car Hi Wind speed Vi Passenger body temperature Tp .
[0007] Preferably, the thermal comfort index TCI The calculation formula is:
[0008] in This represents the specific functional relationship based on the PMV-PPD model, which comprehensively considers the human metabolic rate. Met thermal resistance of clothing Clo The influence of factors.
[0009] Preferably, the human thermal comfort model is an improvement upon the PMV model, and its calculation formula is as follows:
[0010] in, To predict the average vote count, Metabolic rate, Work done on the outside is the average radiation temperature, and is the air temperature.
[0011] Preferred thermal comfort index TCI The range is [-3, 3], and the evaluation standard for the performance of the automotive air conditioning is when... TCI When the value is in the range of [-1, 1], the air conditioning performance is considered good; when TCI A value less than -1 or greater than 1 indicates that the air conditioning performance needs improvement.
[0012] Preferably, the construction of a human thermal comfort model includes the following steps: H1. Input parameter: Receive vehicle interior temperature Ti Humidity inside the car Hi Wind speed Vi Passenger body temperature Tp and human metabolic rate Metthermal resistance of clothing Clo ; H2. Calculation of thermal sensation: Thermal sensation is calculated using the PMV-PPD model according to ISO 7730 standard; H3. Calculate the thermal comfort index TCI Based on the PMV-PPD model and combined with thermal sensation results, the following formula is used to calculate... TCI :
[0013] in, As a correction factor, it is dynamically adjusted based on the passenger's age, gender, and weight information using a pre-set mapping table. This mapping table determines the correction factor based on historical data and statistical analysis. ; This represents the percentage of those expected to be dissatisfied. H4. Output Results: Outputs the calculated thermal comfort index. TCI.
[0014] Preferably, the PMV model for calculating thermal sensation also involves the following parameters:
[0015]
[0016] in Wet-bulb temperature, This refers to the dry bulb temperature.
[0017] Preferably, the dynamic adjustment strategy includes: analyzing the vehicle's driving status, including stationary, low-speed driving, and high-speed driving; and dynamically adjusting the air conditioning operating mode in combination with external environmental conditions, including outside temperature and sunlight intensity.
[0018] An electronic device includes a sensor array, a control unit, and an in-vehicle display screen. The sensor array includes a temperature sensor, a humidity sensor, a wind speed sensor, and a passenger body temperature sensor installed inside the vehicle, as well as a speed sensor, a GPS locator, and a light intensity sensor installed around the vehicle body. The control unit includes a data processing module and a display driver module.
[0019] Preferably, the control unit further includes a functional module for dynamically adjusting the air conditioning operating mode according to the vehicle driving status and external environmental conditions, and a learning module for realizing intelligent learning functions.
[0020] Preferably, the passenger information collection unit includes a user interface, a pressure sensor installed inside the car seat, and a facial recognition camera installed on the back of the driver and front passenger seats. The user interface allows passengers to voluntarily input their personal information, the pressure sensor is used to detect the passenger's weight, and the facial recognition camera is used to perform facial recognition.
[0021] Preferably, the design process of the mapping table is as follows: H301. Data Collection: Collect a large amount of historical thermal comfort feedback data on passengers of different ages, genders, and weights under different environmental conditions; H302. Statistical Analysis: Analyze the data to identify differences in thermal comfort among individuals and quantify these differences as correction coefficients. ; H303. Mapping Rule Formulation: Based on the analysis results, a mapping table is formulated, which maps age, gender, and weight to correction factors. Connect them; H304. Correction factor Application: In the calculation of the Thermal Comfort Index (TCI), the corresponding correction factor is looked up from the mapping table based on the specific information of the passengers. And apply it to the calculation formula.
[0022] (III) Beneficial Effects Compared with the prior art, the present invention provides a method for evaluating the thermal comfort of automotive air conditioning, which has the following beneficial effects: 1. The thermal comfort evaluation method of this car air conditioner, by introducing a sensor array, realizes comprehensive monitoring of in-vehicle environmental parameters. The data processing module in the control unit can receive and process the data from these sensors in real time and input it into the improved PMV model. This not only avoids the problem of poor thermal comfort caused by single temperature control, but also makes accurate calculations based on individual differences of passengers, such as age, gender and weight, thereby ensuring that each passenger can enjoy the most suitable in-vehicle temperature and greatly improving the thermal comfort experience of passengers.
[0023] 2. The thermal comfort evaluation method for automotive air conditioning further includes a control unit that dynamically adjusts the air conditioning operating mode based on vehicle driving status, such as stationary, low-speed driving, and high-speed driving, and external environmental conditions, such as outside temperature and sunlight intensity. It also includes a learning module for achieving intelligent learning functionality. When the vehicle is driving under different conditions, the control unit analyzes the current driving status and external environment, and adjusts the air conditioning operating mode accordingly to ensure optimal thermal comfort is maintained under any circumstances. Furthermore, the intelligent learning module can record and learn passenger habits and preferences. Over time, the system automatically optimizes the air conditioning settings so that passengers can experience optimal thermal comfort every time they ride in the vehicle. Attached Figure Description
[0024] Figure 1 This is a schematic diagram of the thermal comfort evaluation method for automotive air conditioning according to the present invention; Figure 2 This is a schematic diagram illustrating the construction process of the human thermal comfort model of the present invention. Detailed Implementation
[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments and accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0026] Please see Figure 1-2 A method for evaluating the thermal comfort of an automotive air conditioner includes the following steps: S1. Data Acquisition: Real-time acquisition of in-vehicle environmental parameters through multiple sensors; S2. Information Input: Obtain passenger personal information, including age, gender, and weight; S3. Index Calculation: Input the collected data into the human thermal comfort model and evaluate the performance of the car air conditioner based on the thermal comfort index; S4. Mode Adjustment: Dynamically adjusts the air conditioner's operating mode based on calculation results; S5. Data Recording: Record passenger feedback and system operation data.
[0027] Specifically, the system collects in-vehicle environmental parameters in real time through a sensor array consisting of temperature sensors, humidity sensors, wind speed sensors, and passenger body temperature sensors. The sensor array is set to operate at a frequency of at least once per second, which ensures the real-time nature of data collection and allows the system to respond promptly to environmental changes. The temperature sensor needs to be accurate to within ±0.5°C to ensure accurate measurement even under slight temperature changes; the humidity sensor needs to be accurate to ±3%RH to provide stable and reliable humidity readings under various humidity conditions; the wind speed sensor needs to be accurate to ±0.1m / s to capture subtle airflow changes inside the vehicle; and the passenger body temperature sensor needs to be accurate to ±0.2°C, which is crucial for monitoring changes in passenger body temperature. Temperature sensors, humidity sensors, wind speed sensors, and passenger body temperature sensors are installed in key locations inside the vehicle, such as the back of the seats, headrests, both sides of the dashboard, and near the door handles, to cover all passenger areas and ensure comprehensive and accurate data collection. For example, the temperature and humidity sensors on the back of the seats can accurately reflect the thermal comfort of the passenger's back; the temperature sensor in the headrest is used to monitor temperature changes in the head and neck; the sensors on both sides of the dashboard are responsible for monitoring the air quality and temperature in front of the driver; and the sensors near the door handles are used to collect the initial body temperature data of passengers when they enter the vehicle, which will be used for subsequent thermal comfort assessments.
[0028] Specifically, the data processing module is a multi-layered architecture that includes front-end signal preprocessing, intermediate data fusion, and back-end data analysis. In the front-end signal preprocessing stage, the system first removes data points that exceed the normal range through the built-in outlier detection algorithm, and then uses digital filtering technology to smooth the original signal, remove noise interference, and retain effective information. The next step is data fusion, where the system integrates data from different sensors to form a unified set of environmental parameters. During this process, the time synchronization of data from each sensor needs to be considered to ensure the consistency of data on the timeline. Finally, in the backend data analysis stage, the processed data will be transmitted to the human thermal comfort model for further processing. The data processing module communicates with the human thermal comfort model via a high-speed CAN bus, ensuring data transmission is latency-free and secure, while also supporting the high bandwidth requirements for future system upgrades.
[0029] Specifically, in the human thermal comfort model, the range of the human metabolic rate (Met) is set to 1.0 to 3.0 metabolic equivalents (METs), which covers most daily scenarios from sitting to moderate-intensity activity; the range of the clothing thermal resistance (Clo) is 0.5 to 1.5clo, which can adapt to changes in different seasons and clothing thickness. In the calculation of the Thermal Comfort Index (TCI), the correction factor (ε) is dynamically adjusted according to the passenger's age, gender and weight to reflect the impact of individual physiological differences on thermal comfort perception. The percentage of dissatisfied passengers (Ppd) is predicted based on historical data and current environmental conditions. The degree of passenger satisfaction with the current thermal comfort status is estimated by analyzing the passenger's past behavioral habits and current environmental parameters. When calculating TCI, the system first calculates the passenger's thermal sensation value using the PMV-PPD model according to the ISO7730 standard. Then, it combines the thermal sensation results with the aforementioned correction coefficients to finally determine the TCI value, ensuring that the calculation process is transparent and traceable, while allowing the algorithm to be updated based on the latest research progress.
[0030] Specifically, in the dynamic adjustment strategy, the vehicle's driving status is monitored in real time through speed sensors and GPS positioning system. The speed sensor is used to detect the vehicle's current speed, while the GPS positioning system is used to determine the vehicle's position and direction of movement, thereby distinguishing between three situations: stationary, low-speed driving, and high-speed driving. External environmental conditions, such as outside temperature and sunlight intensity, are continuously monitored by external environmental sensors. For example, temperature sensors installed around the vehicle body can sense changes in outside temperature, while light intensity sensors installed on the roof or windshield are used to measure sunlight intensity. Based on this data, the air conditioning operating mode will automatically switch to energy-saving, comfort, or rapid cooling mode to meet the needs of different scenarios. When stationary, the air conditioner may switch to energy-saving mode to reduce energy consumption; when driving at low speeds, the air conditioner will prioritize the comfort of the occupants; while during high-speed driving, the system will adjust the cooling or heating power according to factors such as wind speed and outside temperature to ensure good thermal comfort even at high speeds.
[0031] Specifically, the intelligent learning module records passenger feedback and identifies passenger preference patterns through data analysis. For example, if the system finds that a passenger often chooses a higher temperature setting on their way to work in the morning, the system will automatically adjust to the passenger's preferred temperature during similar time periods in the future. The intelligent learning module has self-learning capabilities. After accumulating a certain amount of data, it regularly performs a self-calibration procedure to optimize the prediction model and gradually improve the accuracy of predicting passenger thermal comfort. As usage time increases, the intelligent learning module can more accurately adjust the air conditioning settings to anticipate passenger needs. In addition, the system supports remote updates, allowing the latest algorithm optimizations or feature enhancements to be pushed through OTA technology, ensuring that the system is always in optimal operating condition.
[0032] Specifically, the user interface is designed as an interactive interface integrated into the in-vehicle display screen. Passengers can choose whether to agree to the collection of information via the touch screen, or manually enter personal information, including age, gender, etc. Passengers can also choose whether to save personal information and the retention period of personal information through the user interface. Pressure sensors are embedded inside the car seat and distributed at key support points in the seat base and backrest to detect the passenger's weight. The pressure sensors are encapsulated with flexible materials to ensure that they do not affect the comfort of the seat, while accurately measuring the weight change of the passenger when seated. The sensor data is transmitted to the control unit in real time. If the passenger chooses to save personal information through the user interface, the sensor will not need to be tested again when the passenger rides the car again within 7-14 days. The facial recognition camera is fixedly installed above the back of the driver and front passenger seats. The camera is equipped with an infrared fill light, which can still perform accurate facial recognition at night or in low light conditions. On the one hand, it can match the data stored by the user in the database. If the passenger's personal information data exists in the database, it will be directly retrieved; if it does not exist, the information will be automatically collected after the passenger is informed and consents.
[0033] Specifically, the mapping table can be shown in the following table: ; The table above is just a simple example. 1. 2... represents different correction factor values, correction factor The specific values were obtained through statistical analysis to ensure that they could reflect the differences in thermal comfort perception among different individuals. The application process of the mapping table is as follows: Once the system obtains the passenger's specific information, it looks up the corresponding correction coefficient ε in the mapping table; The found correction coefficient ε is applied to the calculation formula of the Thermal Comfort Index (TCI); The calculation of the correction factor ε can be simply expressed as:
[0034] Here, f is the formula for calculating the Thermal Comfort Index (TCI), while ε is a correction factor obtained from the mapping table based on passenger information. In summary, this method for evaluating the thermal comfort of automotive air conditioning, by introducing a sensor array, achieves comprehensive monitoring of in-vehicle environmental parameters. The data processing module in the control unit can receive and process the data from these sensors in real time and input it into the improved PMV model. This not only avoids the problem of poor thermal comfort caused by single temperature control, but also allows for precise calculations based on individual passenger differences, such as age, gender, and weight, thereby ensuring that each passenger can enjoy the most suitable in-vehicle temperature and greatly improving the passenger's thermal comfort experience.
[0035] Furthermore, the thermal comfort evaluation method for automotive air conditioning further includes a control unit that dynamically adjusts the air conditioning operating mode based on vehicle driving status (e.g., stationary, low-speed, and high-speed driving) and external environmental conditions (e.g., ambient temperature and sunlight intensity), as well as a learning module for intelligent learning. When the vehicle is driving under different conditions, the control unit analyzes the current driving status and external environment and adjusts the air conditioning operating mode accordingly to ensure optimal thermal comfort under any circumstances. In addition, the intelligent learning module can record and learn passenger habits and preferences. Over time, the system automatically optimizes the air conditioning settings so that passengers can experience optimal thermal comfort every time they ride in the car. This addresses some limitations of existing automotive air conditioning systems, mainly in their insufficient monitoring of in-vehicle environmental parameters and lack of attention to passengers' personalized needs. Most automotive air conditioning systems rely solely on simple temperature control logic, neglecting factors crucial to thermal comfort such as humidity, wind speed, and even passenger body temperature. Moreover, due to the lack of consideration for basic passenger information, existing air conditioning systems struggle to provide a truly individualized thermal comfort experience.
[0036] The relevant modules involved in this system are all hardware system modules or functional modules that combine computer software programs or protocols with hardware in the prior art. The computer software programs or protocols involved in these functional modules are technologies known to those skilled in the art and are not improvements to this system. The improvement of this system lies in the interaction or connection between the modules, that is, in improving the overall structure of the system to solve the corresponding technical problems that this system aims to address.
[0037] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. A method for evaluating the thermal comfort of an automotive air conditioner, characterized in that, Includes the following steps: S1. Data Acquisition: Real-time acquisition of in-vehicle environmental parameters through multiple sensors; S2. Information Input: Obtain passenger personal information, including age, gender, and weight; S3. Index Calculation: Input the collected data into the human thermal comfort model and evaluate the performance of the car air conditioner based on the thermal comfort index; S4. Mode Adjustment: Dynamically adjusts the air conditioner's operating mode based on calculation results; S5. Data Recording: Record passenger feedback and system operation data.
2. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 1, characterized in that, S1, the in-vehicle environmental parameters include the in-vehicle temperature. Ti Humidity inside the car Hi Wind speed Vi Passenger body temperature Tp .
3. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 1, characterized in that, The thermal comfort index TCI The calculation formula is: in This represents the specific functional relationship based on the PMV-PPD model, which comprehensively considers the human metabolic rate. Met thermal resistance of clothing Clo The influence of factors.
4. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 1, characterized in that, The S3 human thermal comfort model is an improvement on the PMV model, and its calculation formula is as follows: in, To predict the average vote count, Metabolic rate, Work done on the outside is the average radiation temperature, and is the air temperature.
5. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 3, characterized in that, S3, thermal comfort index TCI The range is [-3, 3], and the evaluation standard for the performance of the automotive air conditioning is when... TCI When the value is in the range of [-1, 1], the air conditioning performance is considered good; when TCI A value less than -1 or greater than 1 indicates that the air conditioning performance needs improvement.
6. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 4, characterized in that, The construction of the human thermal comfort model, as described in S3, includes the following steps: H1. Input parameter: Receive vehicle interior temperature Ti Humidity inside the car Hi Wind speed Vi Passenger body temperature Tp and human metabolic rate Met thermal resistance of clothing Clo ; H2. Calculation of thermal sensation: Thermal sensation is calculated using the PMV-PPD model according to ISO 7730 standard; H3. Calculate the thermal comfort index TCI Based on the PMV-PPD model and combined with thermal sensation results, the following formula is used to calculate... TCI : in, As a correction factor, it is dynamically adjusted based on the passenger's age, gender, and weight information using a pre-set mapping table. This mapping table determines the correction factor based on historical data and statistical analysis. ; This represents the percentage of those expected to be dissatisfied. H4. Output Results: Outputs the calculated thermal comfort index. TCI.
7. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 6, characterized in that, The PMV model for calculating thermal sensation also involves the following parameters: in Wet-bulb temperature, This refers to the dry bulb temperature.
8. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 1, characterized in that, The S4 dynamic adjustment strategy includes: analyzing the vehicle's driving status, including stationary, low-speed driving, and high-speed driving; and dynamically adjusting the air conditioning operating mode in conjunction with external environmental conditions, including outside temperature and sunlight intensity.
9. An electronic device comprising a sensor array, a control unit, a passenger information collection unit, and an in-vehicle display screen, characterized in that, The sensor array includes temperature sensors, humidity sensors, wind speed sensors, and passenger body temperature sensors installed inside the vehicle, as well as speed sensors, GPS locators, and light intensity sensors installed around the vehicle body. The control unit includes a data processing module and a display driver module.
10. An electronic device according to claim 9, characterized in that, The control unit further includes a functional module for dynamically adjusting the air conditioning operating mode according to the vehicle's driving status and external environmental conditions, and a learning module for realizing intelligent learning functions.
11. An electronic device according to claim 9, characterized in that, The passenger information collection unit includes a user interface, a pressure sensor installed inside the car seat, and a facial recognition camera installed on the back of the driver and front passenger seats. The user interface allows passengers to voluntarily input their personal information, the pressure sensor is used to detect the passenger's weight, and the facial recognition camera is used for facial recognition.
12. The method for evaluating the thermal comfort of an automotive air conditioner according to claim 6, characterized in that, The design process of the mapping table is as follows: H301. Data Collection: Collect a large amount of historical thermal comfort feedback data on passengers of different ages, genders, and weights under different environmental conditions; H302. Statistical Analysis: Analyze the data to identify differences in thermal comfort among individuals and quantify these differences as correction coefficients. ; H303. Mapping Rule Formulation: Based on the analysis results, a mapping table is formulated, which maps age, gender, and weight to correction factors. Connect them; H304. Correction factor Application: In the calculation of the Thermal Comfort Index (TCI), the corresponding correction factor is looked up from the mapping table based on the specific information of the passengers. And apply it to the calculation formula.