Method for adjusting air conditioning system

Abstract

The invention relates to a method for adjusting an air conditioning system. In this case, data of the air-conditioning installation is collected, and a comfort model matching the user is trained using these data. Adjustment for adjusting the air conditioning facility is predicted based on the comfort model. In this case, the data comprise user physiological data (4) of the user (5), which are ascertained by means of the evaluation system (3). The invention also relates to a control architecture (2) for implementing the method (1).

Description

Technical Field

[0001] The invention relates to a method for user-adapting an air conditioning system of a vehicle by means of a control architecture according to the preamble of claim 1. The invention also relates to a control architecture for carrying out the method. Background Art

[0002] The user of an air-conditioning system can adjust the air-conditioning system by changing a number of parameters, depending on his thermal perception. The air-conditioning control based on a comprehensive characteristic curve can save the user from this adjustment and thus simplify the operation of the air-conditioning system. However, the thermal comfort of each user is very individual. Disadvantageously, conventional air-conditioning control based on a comprehensive characteristic curve is designed for "ordinary" people and cannot be automatically adapted to each user. If a user feels uncomfortable with the air-conditioning control based on a comprehensive characteristic curve, the user must laboriously readjust the air-conditioning system manually.

[0003] Another solution offers AI (AI: Artificial Intelligence)-assisted comfort models, which can be adapted to the personal preferences of the individual user. The adjustments made by the user to the air conditioning system are linked to environmental data (e.g., outside or inside temperature) and used to train the comfort model. The trained comfort model can then predict the optimal adjustment of the air conditioning system for the individual user at a predetermined time based on the environmental data. Unfortunately, the thermal comfort of the user depends not only on the thermal environmental data, but also on the physiological state of the user.

[0004] Similar solutions are known, for example, from DE 11 2013 003 595 T5, DE 11 2019 000 315 T5 and DE 10 2014 102 827 A1. Summary of the invention

[0005] The object of the present invention is therefore to specify an improved or at least alternative embodiment for a generic method in which the described disadvantages are overcome. It is also an object of the present invention to provide a corresponding control architecture for implementing the method.

[0006] This object is achieved according to the invention by the subject matter of the independent claim. Advantageous embodiments are the subject matter of the dependent claims.

[0007] The general idea underlying the present invention is to obtain the user's physiological state with minimal requirement for additional sensor means and to train an AI-based comfort model based on these physiological states.

[0008] The method is configured to adjust the air conditioning system of a vehicle to match the user with the help of a control architecture. Here, with the help of the control architecture, data related to the adjustment of the air conditioning system are collected, and a comfort model of the air conditioning system to match the user is trained in the AI ​​unit using the collected data. In the context of the present invention, data related to the adjustment should be understood as data or parameter values ​​that are important for the adjustment of the air conditioning system and / or can be taken into account in the comfort model when predicting the adjustment to match the user. Then, based on the trained comfort model, the adjustment to match the user is predicted for the adjustment of the air conditioning system to match the user. According to the present invention, the data related to the adjustment include user physiological data of the user, wherein these user physiological data are obtained with the help of an evaluation system of the control architecture and transmitted to the AI ​​unit.

[0009] In the method according to the invention, a comfort model is trained based on thermal environmental data and user physiological data of the user, whereby the vehicle's air conditioning system is set individually and adapted to the user. In particular, the user's physiological state can be taken into account, and the air conditioning system can thus be optimally set. This can also advantageously reduce the number of manual instructions for the air conditioning system that must be made by the user.

[0010] It is conceivable that the adjustment-related data of the air conditioning installation are transmitted to the cloud and that a comfort model matching the user is trained based on the adjustment-related data of the air conditioning installation. In this case, the cloud is a network that provides computer resources such as servers and / or data storage and / or applications. Thus, a comfort model matching the user can be created, which then predicts the adjustment for the matching user of the air conditioning installation based on the adjustment-related data of the air conditioning installation. It should be understood that multiple comfort models can also be trained for multiple users in the cloud.

[0011] The evaluation system may include a camera device arranged in the interior space of the vehicle, wherein image data are obtained by means of the camera device and user physiological data of the user are obtained from these image data. Advantageously, the camera device may include a camera and / or a thermal imaging camera and these image data are obtained by means of the camera and / or the thermal imaging camera. As a result, the evaluation system can obtain the user physiological data in a particularly simplified manner. Here, the user physiological data can be obtained from the image data obtained by means of at least one AI-based measure and / or extraction. Here, user physiological data of the user, such as skin surface temperature and / or heart rate and / or breathing rate and / or clothing condition and / or positioning of limbs and / or age and / or gender and / or height and / or weight and / or emotional state and / or fatigue level, can be obtained from these image data. It should be understood that this list is not exhaustive.

[0012] Advantageously, the evaluation system may include a sensor device arranged in the interior of the vehicle. Sensor data may then be acquired by means of the sensor device and user physiological data of the user may be determined from these sensor data. User physiological data such as skin surface temperature and / or heart rate and / or breathing rate and / or weight may be determined from these sensor data.

[0013] In addition, it can be provided that the control-related data of the air conditioning system include environmental data of the vehicle. In this case, the environmental data can be acquired with the aid of a sensor system of the control architecture. The environmental data can be, for example, the interior temperature and / or the exterior temperature and / or the air humidity and / or the position of the sun and / or the light intensity or the sunlight illumination and / or the air pressure. The acquired environmental data can be used to train a comfort model in the AI ​​unit.

[0014] Furthermore, the adjustment-related data of the air conditioning system may also include adjustment data. These adjustment data may be predetermined by the user and may include the temperature to be adjusted and / or the fan level to be adjusted and / or the seat heating to be adjusted and / or the heating surface to be adjusted and / or the heating intensity and / or the cooling intensity to be adjusted. The adjustment data entered by the user may be used to train the comfort model in the AI ​​unit.

[0015] The present invention also relates to a control architecture for implementing the above method. Here, the control architecture is designed to implement the method. Specifically, the control architecture is designed to: collect adjustment-related data of the air-conditioning facility; use the collected data to train the comfort model of the matching user of the air-conditioning facility in the AI ​​unit; predict the adjustment of the matching user for adjusting the air-conditioning facility to match the user based on the trained comfort model; and obtain the user's physiological data of the user's adjustment-related data by means of an evaluation system and transmit these user physiological data to the AI ​​unit. It should be understood that the control architecture may include the hardware required for implementing the method and the software required for implementing the method. In order to avoid repetition, the above statements are quoted here.

[0016] Further important features and advantages of the invention emerge from the dependent claims, the drawings and the associated description of the figures based on the drawings.

[0017] It goes without saying that the features mentioned above and yet to be explained below can be used not only in the respectively specified combination but also in other combinations or alone, without departing from the scope of protection of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The preferred embodiment of the present invention is Figure 1 and are explained in more detail in the following description. DETAILED DESCRIPTION

[0019] Figure 1 The data structures in the method 1 according to the invention or in the control architecture 2 are schematically shown. Here, the control architecture 2 comprises an evaluation system 3 which obtains user physiological data 4 of a user 5. For this purpose, the evaluation system 3 has a camera device 6 with a camera 7 and with a thermal imaging camera 8.

[0020] Here, the camera 7 obtains image data used to obtain the user's physiological data 4, such as the clothing status and body posture. In addition, with the help of facial recognition, the user's physiological data 4, such as the age, gender, height, weight and emotions of the user 5, are obtained from these image data. In addition, with the help of additional frequency analysis, the heart rate and breathing rate of the user 5 can be determined.

[0021] The thermal imaging camera 8 obtains image data that is used to obtain the user's physiological data 4, such as the skin surface temperature. In order to obtain the skin surface temperature, the coordinates obtained by means of the image data of the camera 7 can also be used.

[0022] The user physiological data 4 can be determined from the determined image data by means of at least one AI-based measure and / or extraction. The determined user physiological data 4 are then used as scalars for training a comfort model in the AI ​​unit.

Claims

1. A method (1) for user (5)-specific adjustment of an air conditioning system of a vehicle adapted to the user, wherein: With the help of control architecture (2): - Collection of data relevant to the adjustment of said air conditioning installations; - Using the collected data, a comfort model matching the user of the air conditioning facility is trained in the AI ​​unit; - predicting user-adapted adjustments for adjusting the air conditioning system to the user based on the trained comfort model, It is characterized in that The adjustment-relevant data include user physiological data (4) of a user (5), wherein the user physiological data (4) are determined by means of an evaluation system (3) of the control architecture (2) and transmitted to the AI ​​unit.

2. The method according to claim 1, It is characterized in that The evaluation system (3) comprises a camera device (6) arranged in the interior of the vehicle, wherein image data are acquired by means of the camera device (6) and user physiological data (4) of a user are determined from the image data.

3. The method according to claim 2, It is characterized in that The user physiological data (4) are determined from the determined image data by means of at least one AI-based measure and / or extraction.

4. The method according to claim 2 or 3, It is characterized in that The camera device (6) comprises a camera (7) and / or a thermal imaging camera (8), wherein the image data used to obtain the user's physiological data (4) are obtained with the aid of the camera (7) and / or the thermal imaging camera (8).

5. The method according to any one of claims 2 to 4, It is characterized in that The user's (5) physiological data (4) are obtained from the image data, such as skin surface temperature and / or heart rate and / or breathing rate and / or clothing condition and / or limb positioning and / or age and / or gender and / or height and / or weight and / or emotional state and / or fatigue level.

6. The method according to any one of the preceding claims, It is characterized in that The evaluation system (3) comprises a sensor device arranged in the interior of the vehicle, wherein sensor data are acquired by means of the sensor device and user physiological data (4) of a user (5) are determined from the sensor data.

7. The method according to claim 6, It is characterized in that The user physiological data (4) of the user (5), such as skin surface temperature and / or heart rate and / or breathing rate and / or weight, are obtained from the sensor data.

8. The method according to any one of the preceding claims, It is characterized in that - the data relevant for setting the air conditioning system include environmental data of the vehicle, wherein the environmental data are determined by means of a sensor system of the control architecture (2), and - The environmental data include the internal temperature and / or the external temperature and / or the air humidity and / or the sun position and / or the light intensity and / or the air pressure.

9. The method according to any one of the preceding claims, It is characterized in that - the adjustment-related data of the air conditioning installation include adjustment data, wherein the adjustment data are predetermined by a user (5), and The adjustment data include the temperature to be adjusted and / or the fan level to be adjusted and / or the seat heating to be adjusted and / or the heating surface to be adjusted and / or the heating intensity and / or the cooling intensity to be adjusted.

10. A control architecture (2) for implementing the method (1) according to any one of the preceding claims, wherein: The control architecture (2) is designed to: - Collecting data related to the adjustment of air conditioning facilities; - Using the collected data to train a user-matched comfort model of the air conditioning facility in the AI ​​unit; - predicting user-matched adjustments for adjusting the air conditioning system to the user based on the trained comfort model; and - determining user physiological data (4) of the user (5) that are relevant for the adjustment by means of the evaluation system (3) and transmitting the user physiological data (4) to the AI ​​unit.

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