FORM 2
THE PATENTS ACT, 1970
[39 OF 1970]
&
The Patents Rules, 2003
COMPLETE SPECIFICATION
[See Section 10 and Rule 13]
TITLE: “METHOD AND SYSTEM FOR AUTOMATIC COMFORT CONTROL IN A VEHICLE”
NAME AND ADDRESS OF THE APPLICANT:
TATA MOTORS PASSENGER VEHICLES LIMITED - Floor 3, 4, Plot-18, Nanavati Mahalaya, Mudhana Shetty Marg, BSE, Fort, Mumbai, Mumbai City, Maharashtra, 400001 India
Nationality: Indian
The following specification particularly describes the invention and the manner in which it is to be performed.

TECHNICAL FIELD
[001] The present disclosure generally relates to vehicle climate control system and more particularly to a method and a system for automatic comfort control in a vehicle using Heating Ventilating and Air Conditioning (HVAC) system.
BACKGROUND
[002] A conventional system for thermal and ventilation control in a vehicle utilizes a forced-air central HVAC system. The existing conventional system controls the temperature and ventilation inside the vehicle using the HVAC system based on a preset given by a user. The preset is a manual setting of temperature and the air flow rate set of the HVAC system, the user wishes to experience. Due to time to time change in climate around the vehicle the user might need to adjust the temperature and air flow rate setting of the HVAC system many times to experience comfort inside the vehicle.
[003] To overcome the shortcomings of the conventional system there is a need for development of an advanced and efficient comfort control system.
[004] The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
SUMMARY
[005] Disclosed herein is a method for automatic comfort control in a vehicle using Heating, Ventilating and Air Conditioning (HVAC) system. The method comprises receiving a user input indicating a thermal comfort level from one or more thermal comfort levels or nomenclatures. Upon receiving the user input, determining the real-time values of the one or more cabin parameters and one or more environment

parameters of the vehicle using one or more sensors. Predicting the desired values of one or more cabin parameters based on the user input indicating the thermal comfort level, the real-time values of the one or more cabin parameters and the one or more environment parameters. Finally, controlling the one or more cabin parameters of the vehicle based on the desired values of the one or more cabin parameters using a HVAC system.
[006] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[007] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of the system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which:
[008] FIG. 1 illustrates a vehicle comprising a system for automatic comfort control using a HVAC system, in accordance with some embodiments of the present disclosure.
[009] FIG. 2 illustrates a detailed block diagram of an apparatus configured to automatically control climate inside a vehicle, in accordance with some embodiments of the present disclosure.

[010] FIG. 3 illustrates a block diagram of automatic comfort control system in a vehicle using HVAC system, in accordance with some embodiments of the present disclosure.
[011] FIG. 4 is a flowchart illustrating a method for automatic comfort control in a vehicle using (HVAC system, in accordance with some embodiments of the present disclosure.
[012] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.
DETAILED DESCRIPTION
[013] In the present document, the word “exemplary” is used herein to mean “serving as an example, instance, or illustration”. Any embodiment or implementation of the present subject matter described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.
[014] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the spirit and the scope of the disclosure.

[015] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device, or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a device or system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the device or system or apparatus.
[016] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
[017] FIG. 1 illustrates a vehicle (100) comprising a system for automatic comfort control using HVAC system (104), in accordance with some embodiments of the present disclosure.
[018] In an embodiment, the exemplary arrangement of the present disclosure in a vehicle (100) comprises an input device (101) mounted inside the vehicle (100) to receive user input, a one or more sensors (102) to sense one or more real-time cabin parameters and one or more environment parameters. An HVAC system (104) to control the cabin climate of the vehicle (100) based on the user input, one or more cabin parameters and one or more environment parameters. An apparatus (103) to control the cabin climate of the vehicle (100) based on the user input, the one or more real-time

cabin parameters and the one or more environment parameters, by using the HVAC system (104).
[019] In an implementation, the apparatus (103) is, without limitation, an Electronic Control Unit (ECU) implemented in the vehicle (100) to control all the electronic features of the vehicle (100).
[020] In an embodiment the apparatus (103) can be implemented, without limitation, software, a firmware or a combination of software and firmware. The apparatus (103) may comprise, without limitation, a memory and a processor to perform one or more actions.
[021] In an embodiment, the processor of the apparatus (103) may be embodied as a multi-core processor, a single core processor, or a combination of one or more multi-core processors and one or more single core processors. For example, the processor may be embodied as one or more of various processing devices, such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuitry with or without an accompanying DSP, or various other processing devices including, a Microcontroller Unit (MCU), a hardware accelerator, or the like. [022] In an embodiment, the one or more sensors (102) may include, without limitation, a temperature sensor to sense the temperature of the cabin of the vehicle (100), a hygrometer to sense humidity of the cabin of the vehicle (100) and a mass air flow rate sensor to sense the air flow rate inside the cabin of the vehicle (100).
[023] In an embodiment, the processor of the apparatus (103) is configured to: (1) receive a real-time user input (205) from a user indicating the thermal comfort level from a plurality of preset thermal comfort levels or nomenclatures; (2) determine real-time values of one or more cabin parameters and one or more environment parameters using one or more sensors (102); (3) predict desired values of one or more cabin parameters based on real-time values of the one or more cabin parameters, the one or

more environment parameters and the user input indicating thermal comfort level; and (4) control the one or more cabin parameters using HVAC system (104) according to the desired values of the one or more cabin parameters.
[024] FIG. 2 illustrates a detailed block diagram of an apparatus (103) configured to automatically control climate inside a vehicle (100), in accordance with some embodiments of the present disclosure.
[025] In an embodiment, the apparatus (103) comprises I/O interface module (201), a processor (203), a memory (202), data (204) and modules (210). The modules (210) further comprises a receiving module (211), a determining module (212), a prediction module (213), and controlling Module (214) which will be explained in detail later.
[026] In an embodiment, the data (204) stored in the memory (202) may include, without limitation, the real-time user input (205) indicating the thermal comfort level from the plurality of thermal comfort levels or nomenclature, real-time values of one or more cabin parameters (206), the one or more environment parameters (207) and the desired values of one or more cabin parameters (208). In one implementation, the data (204) may be stored within the memory (202) in the form of various data structures. Additionally, the data (204) may be organized using data models, such as relational or hierarchical data models. In an embodiment, other data may be stored in the memory (202). The other data may include, but not limited to, alarm data.
[027] In an embodiment, the real-time values of the one or more cabin parameters (206) received from the one or more sensors (102) may include, without limitation, at least one of a temperature level, a humidity level and an air flow rate of the vehicle (100), wherein the air flow rate is of a blower of the HVAC system (104).
[028] In an implementation, the one or more environment parameters (207) received from the one or more sensors (102) may include, without limitation, at least one of an

air temperature level, a radiant temperature level, an air flow speed, and a humidity level outside the vehicle(100).
[029] In an embodiment, the I/O interface module (201) of apparatus (103) may include, without limitation, enabling communication of the apparatus (103) with one or more sensors (102). In another embodiment, the I/O interface module (201) may be a communication port such as, without limitation, Controller Area Network (CAN) controller, Local Interconnect Network (LIN) controller, Serial port, parallel port, infrared port, PS-2 port, Bluetooth port, FireWire port Universal Serial Bus (USB)/ C-type port .
[030] In an embodiment, the user input (205) is received from the user, the real-time user input (205) indicates the thermal comfort level of the user among plurality of preset thermal comfort levels. Upon receiving the user input (205) the processor determines the real-time one or more cabin parameters (206) and the one or more environment parameters (207) using the one or more sensors (102). Determining the desired values of the one or more cabin parameters (208) based on the real-time values of the one or more cabin parameters (206), the one or more environment parameters (207) and the real-time user input (205) indicating the thermal comfort level using one or more Machine Learning (ML) model. Finally controlling the HVAC system (104) to control the one or more cabin parameters (206) according to the desired values of the one or more cabin parameters (208).
[031] In an embodiment, the one or more ML model is trained to predict the desired values of the one or more cabin parameters (208), wherein training the one or more ML model comprises providing training data set to the one or more ML model, a plurality of desired values of a temperature level, a humidity level and an air flow rate for the plurality of thermal comfort levels to the one or more ML model, and predicting the desired values of the one or more cabin parameters (208).

[032] In an embodiment, the training data set comprises, without limitation, training values of, the one or more cabin parameters, the one or more environment parameters and the plurality of thermal comfort levels.
[033] In an embodiment, the user input (205) is received by an electronic device such as, without limitation an infotainment system of a vehicle (100), where in the infotainment system displays the user with range of thermal comfort levels the user wants to experience. The range of thermal comfort levels comprises, without limitation, cold, cool, slightly cool, neutral, slightly warm, warm and hot.
[034] In an implementation, the user input (205) indicates the thermal comfort level the user wishes to experience. The thermal comfort level is a setting which is set by the user, processor (203) of the apparatus (103) predicts desired values of one or more cabin parameters (208) based on thermal comfort level the user wishes to experience based on the one or more real-time values of the one or more cabin parameters, and the one or more environment parameters.
[035] In an embodiment, the receiving module (211) of the modules (210) may comprise, without limitation, the processor (203) along with an infotainment system of the vehicle (100) to receive the user input (205) from the user.
[036] In an embodiment, the determining module (212) of the modules (210) may comprise, without limitation, the processor (203) along with one or more sensors (102) to determine the real-time values of the one or more cabin parameters (206) and the one or more environment parameters (207).
[037] In an embodiment, the prediction module (213) of the modules (210) may comprise, without limitation, the one or more trained ML model to predict the desired values of the one or more cabin parameters (208) based on the real-time values of the one or more cabin parameters (206), the one or more environment parameters (207) and the user input (205).

[038] In an embodiment, the automatic comfort control system, by the processor (203), using the controlling module (214) controls the HVAC system (104) intelligently to control the one or more cabin parameters (206) to maintain the cabin climate of the vehicle (100) according to the thermal comfort level that the user wishes to experience based on the desired values predicted by the one or more trained ML model.
[039] FIG. 3 illustrates a block diagram of automatic comfort control system in a vehicle using HVAC system, in accordance with some embodiments of the present disclosure.
[040] In an embodiment, modules illustrated in FIG. 3 are submodules of the modules (210) illustrated in FIG. 2 operating in sequence.
[041] In an embodiment, when a user gets into the vehicle (100) and wishes to experience a particular kind of thermal comfort inside the vehicle (100), the user selects the thermal comfort level on the infotainment system. The processor (203) of the apparatus (103) receives the user input (205) from the infotainment system of the vehicle (100), determines the real-time values of the one or more cabin parameters (206) and the one or more environment parameters (207) using the one or more sensors (102). The processor (203) further predicts the desired values of the one or more cabin parameters (208) based on the real-time values of the one or more cabin parameters (206), the one or more environment parameters (207), and the user input (205). The processor (203) of the apparatus (103) further controls the HVAC system (104) to control the one or more cabin parameters (206) by controlling rate of cooling/heating (301), rate of air flow (302), and air directivity mode (303) using the HVAC system (104) based on the desired values predicted by the one or more trained ML.
[042] In an implementation, the apparatus (103) is, without limitation, an ECU used in the vehicle (100) to control the electronics of the vehicle (100).

[043] FIG. 4 illustrates training of the Machine Learning (ML) model to predict the desired values of the one or more cabin parameters, in accordance with some embodiments of the present disclosure.
[044] In an embodiment, training the ML model 403 to predict the desired values of the one or more cabin parameters (208) comprises providing the training data set (401) and thermal comfort level parameters value (402) i.e., the plurality of desired values of a temperature level, a humidity level and an air flow rate associated with plurality of thermal comfort levels. The thermal comfort level parameters value (402) are the ground truth indicating the values of the one or more cabin parameters (208) that the user desires to experience.
[045] In an embodiment, the training data set (401) comprises, without limitation, training values of, the one or more cabin parameters, the one or more environment parameters and the plurality of thermal comfort levels.
[046] FIG. 5 is a flowchart illustrating a method for automatic comfort control in a vehicle using HVAC, in accordance with some embodiments of the present disclosure.
[047] As illustrated in FIG. 5, the method 500 may include one or more block illustrating a method for automatic comfort control in a vehicle (100). The order in which the method 500 is intended to be constructed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.
[048] At block 501, the method 500 includes receiving, by the processor (203), the user input (205) from the user;

[049] At block 502, the method 500 includes determining, by the processor (203), the real-time value of the one or more cabin parameters (206) and the one or more environment parameters (207) using the one or more sensors (102) of the vehicle (100);
[050] At block 503, the method 500 includes predicting, by the processor (203), the desired values of the one or more cabin parameters (208) using the one or more trained ML model based on the user input (205) indicating the thermal comfort level the user wishes to experience, the real-time values of the one or more cabin parameters (206) and the one or more environment parameters (207).
[051] In an embodiment, predicting the desired values of the one or more cabin parameters (208) comprises training the one or more ML model with training data set (401) and thermal comfort level parameters value (402) indicating plurality of desired values of a temperature level, a humidity level and an air flow rate associated with plurality of thermal comfort levels. And the trained ML model (401) when given with plurality of inputs understands a pattern in the inputs relating with the associated ground truths.
[052] In the same embodiment, the training data set (401) comprises, without limitation, training values of, the one or more cabin parameters, the one or more environment parameters and the plurality of thermal comfort levels.
[053] At block 504, the method 500 includes controlling, the one or more cabin parameters (206) by controlling the HVAC system (104) according to the desired values of the one or more cabin parameters (208). As an example, for the user input (205) of slightly cool comfort requirements, the apparatus (103) for automatic comfort control will set cabin parameters at 23°C and air flow at 3rd level basis inputs of one or more cabin parameters and environmental parameters. While the user comfort requirements remains same for period of time, the sizeable increase in ambient

temperature or radiant temperature of environment would trigger the apparatus (103) to alter the set cabin parameter to 22°C and air flow at 4th level.
[054] In an embodiment, controlling the cabin parameters (206) comprises, without limitation, controlling the rate of cooling/heating (301), the rate of air flow (302), and the air directivity mode (303) using the HVAC system (104).
[055] The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise.
[056] The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise.
[057] The enumerated listing of items does not imply that any or all the items are mutually exclusive, unless expressly specified otherwise. The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.
[058] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.
[059] When a single device or article is described herein, it will be clear that more than one device/article (whether they cooperate) may be used in place of a single device/article. Similarly, where more than one device/article is described herein (whether they cooperate), it will be clear that a single device/article may be used in place of the more than one device/article, or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or features of a device may be alternatively embodied by one or more other devices which

are not explicitly described as having such functionality/features. Thus, other embodiments of invention need not include the device itself.
[060] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
[061] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.
[062] Referral Numerals:

Reference Number Description
100 Vehicle
101 Input device
102 One or more sensor
103 Apparatus
104 Heating, Ventilating and Air Conditioning (HVAC) system.
201 I/O Interface
202 Memory
203 Processor

204 Data
205 User input
206 Real-time values of one or more cabin parameters
207 One or more environment parameters
208 Desired values of the one or more cabin parameters
210 Modules
211 Receiving module
212 Determining module
213 Predicting module
214 Controlling module
301 Rate of cooling/heating
302 Rate of air flow
303 Air directivity mode
401 Training data set
402 Thermal comfort parameters value

WE CLAIM:
1. A method for automatic comfort control in a vehicle (100), comprises:
receiving, by a processor (203), a real-time input (205) from a user indicating a
thermal comfort level from a plurality of thermal comfort levels;
determining, by the processor (203), real-time values of one or more cabin parameters (206) and one or more environment parameters (207) using one or more sensors (102);
predicting, by the processor (203), desired values of the one or more cabin parameters (208) using one or more Machine Learning (ML) model based on the real-time values of the one or more cabin parameters, the one or more environment parameters (207) and the thermal comfort level; and
controlling, by the processor (203), the one or more cabin parameters using a Heating, Ventilating and Air Conditioning (HVAC) system (104) according to the desired values of the one or more cabin parameters (208).
2. The method as claimed in claim 1, wherein the one or more cabin parameters comprises at least one of a temperature level, a humidity level and an air flow rate of the vehicle (100).
3. The method as claimed in claim 1, wherein the one or more environment parameters (207) comprise at least one of an air temperature level, a radiant temperature level, an air flow speed, and a humidity level outside the vehicle (100).
4. The method as claimed in claim 1, wherein predicting the desired values of the one or more cabin parameters (208) comprises using one or more trained ML model, wherein training one or more ML model comprises:

providing training data set to the one or more ML model, wherein the training data set comprises training values of, the one or more cabin parameters, the one or more environment parameters (207) and the plurality of thermal comfort levels;
providing a plurality of desired values of a temperature level, a humidity level and an air flow rate for the plurality of thermal comfort levels to the one or more ML model; and
predicting the desired values of the one or more cabin parameters (208) for each of the plurality of thermal comfort levels by the one or more ML model.
5. The method as claimed in claim 1, wherein controlling the one or more cabin
parameters using HVAC system (104) comprises:
controlling the HVAC system (104) to increase or decrease the one or more cabin parameters of the vehicle (100) according to the desired values of the one or more cabin parameters (208).
6. An apparatus (103) comprising a memory and a processor (203), the processor
(203) is configured to:
receive a real-time input (205) from a user indicating a thermal comfort level from a plurality of thermal comfort levels;
determine real-time values of one or more cabin parameters (206) and one or more environment parameters (207) using one or more sensors (102);
predict desired values of the one or more cabin parameters (208) using one or more Machine Learning (ML) model based on the real-time values of the one or more cabin parameters (206), the one or more environment parameters (207) and the thermal comfort level; and
control the one or more cabin parameters using a Heating, Ventilating and Air Conditioning (HVAC) system (104) according to the desired values of the one or more cabin parameters (208).

7. The apparatus (103) as claimed in claim 6, wherein the processor (203) is
configured to predict the desired values of the one or more cabin parameters (208)
using one or more trained ML model, wherein to train one or more ML model the
processor (203) is configured to:
provide training data set to the one or more ML model, wherein the training data set comprises training values of, the one or more cabin parameters, the one or more environment parameters (207) and the plurality of thermal comfort levels;
provide a plurality of desired values of a temperature level, a humidity level and a air flow rate for the plurality of thermal comfort levels to the one or more ML model; and
predict the desired values of the one or more cabin parameters (208) for each of the plurality of thermal comfort levels by the one or more ML model.
8. The apparatus (103) as claimed in claim 6, wherein the processor (203) is
configured to control the one or more cabin parameters using HVAC system (104),
wherein the processor (203) is configured to:
control the HVAC system (104) to increase or decrease the real-time values of one or more cabin parameters (206) of a vehicle (100) according to the desired values of the one or more cabin parameters (208).
9. A control system in a vehicle (100) comprises:
Input device (101);
one or more sensors (102);
a Heating, Ventilating and Air Conditioning (HVAC) system (104);

a memory (202); and
a processor (203) configured to perform method steps of 1-5.