Aerosol generating device and method of operation thereof

Abstract

The aerosol generating device and the method for performing self-diagnosis in the aerosol generating device determine whether to activate self-diagnosis for analyzing errors in the aerosol generating device when the aerosol generating device does not operate normally due to an error, and if the self-diagnosis is activated, perform a functional test by checking whether each function required for the normal performance of the heating operation of the aerosol generating device is normal, determine the defective component of the aerosol generating device based on the results of the functional test, determine the defective function of the defective component based on an error log recorded in the aerosol generating device, determine the severity of the determined defective function, and output a final diagnostic result related to the self-diagnosis based on the defective component, the defective function, and the severity.

Description

[Technical field]

[0001] The present invention relates to an aerosol generating device and a method of operating the same, and in particular to a self-diagnosis function of the aerosol generating device. [Background technology]

[0002] Recently, there has been an increasing demand for alternatives to traditional combustion cigarettes. For example, there has been an increasing demand for aerosol generating devices that generate aerosols by heating an aerosol generating material in an aerosol generating product (e.g., a cigarette) without combustion. This has led to active research into aerosol generating products and aerosol generating devices. Summary of the Invention [Problem to be solved by the invention]

[0003] Since the aerosol generating device is an electronic device, there is a possibility that an error or failure may occur in the hardware modules or software operations in the device, but it is difficult for a user to accurately grasp the cause of such an error or failure and take appropriate measures.

[0004] The problem to be solved by the present invention is to provide an aerosol generating device having a self-diagnosis function and a method of operating the same.

[0005] The technical problems that the present disclosure aims to solve are not limited to the technical problems described above, and further technical problems can be inferred from the following examples. [Means for solving the problem]

[0006] According to one aspect, a method for performing self-diagnosis in an aerosol generating device includes a step of determining whether to activate a self-diagnosis for analyzing the error of the aerosol generating device when the aerosol generating device does not operate normally due to an error; a step of performing a functional test by checking whether each function required for the heating operation of the aerosol generating device to be performed normally is normal if the self-diagnosis is activated; a step of determining a defective component of the aerosol generating device based on a result of the functional test; a step of determining a defective function of the defective component based on an error log recorded in the aerosol generating device; a step of determining a severity of the determined defective function; and a step of outputting a final diagnostic result related to the self-diagnosis based on the defective component, the defective function, and the severity. Effect of the Invention

[0007] As described above, when an error occurs in the aerosol generating device, the aerosol generating device can perform a self-diagnosis and provide a diagnosis result regarding the cause of the error, so that a user can more easily identify the cause of the error in the aerosol generating device and seek a solution to resolve the error. In addition, a service center can accurately identify the cause of the error by utilizing the self-diagnosis result of the aerosol generating device and repair the aerosol generating device. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is a block diagram showing the hardware configuration of an aerosol generating device according to an exemplary embodiment. [Figure 2A] 2 is a diagram showing various embodiments of the aerosol generating device of FIG. 1. [Figure 2B] 2 is a diagram showing various embodiments of the aerosol generating device of FIG. 1. [Figure 2C] 2 is a diagram showing various embodiments of the aerosol generating device of FIG. 1. [Figure 2D] 2 is a diagram showing various embodiments of the aerosol generating device of FIG. 1. [Figure 2E] 2 is a diagram showing various embodiments of the aerosol generating device of FIG. 1. [Diagram 3] 1 is a diagram for explaining that a self-diagnosis is performed in an aerosol generating device according to an exemplary embodiment. [Figure 4] 1 is a flowchart illustrating a process in which an aerosol generating device activates a self-diagnosis according to an exemplary embodiment. [Diagram 5] 1 is a diagram for explaining the entire process of self-diagnosis performed by an aerosol generating device according to an exemplary embodiment. [Figure 6] 13 is data showing an error log stored in the memory of an aerosol generating device according to an exemplary embodiment. [Figure 7] 1 is a flowchart of a first diagnostic process for self-diagnosis of an aerosol generating device according to an exemplary embodiment. [Figure 8] 13 is a flowchart of a secondary diagnostic process for self-diagnosis of an aerosol generating device according to an exemplary embodiment. [Figure 9] 13 is a flowchart of a third diagnostic process for self-diagnosis of an aerosol generating device according to an exemplary embodiment. [Figure 10] 1 is a diagram illustrating a target for which a final diagnosis result is output according to an exemplary embodiment; [Figure 11] 1 is a flowchart of a method for performing self-diagnosis by an aerosol generating device in accordance with an exemplary embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] According to one aspect, a method for performing self-diagnosis in an aerosol generating device includes a step of determining whether to activate a self-diagnosis for analyzing the error of the aerosol generating device when the aerosol generating device does not operate normally due to an error; a step of performing a functional test by checking whether each function required for the heating operation of the aerosol generating device to be performed normally is normal if the self-diagnosis is activated; a step of determining a defective component of the aerosol generating device based on a result of the functional test; a step of determining a defective function of the defective component based on an error log recorded in the aerosol generating device; a step of determining a severity of the determined defective function; and a step of outputting a final diagnostic result related to the self-diagnosis based on the defective component, the defective function, and the severity.

[0010] In addition, the step of determining whether to activate the self-diagnosis determines to activate the self-diagnosis if the error has recently occurred in the aerosol generating device or has occurred a predetermined number of times or more in the aerosol generating device.

[0011] In addition, the functional test is performed on the driving function of hardware including at least one of a heater, a sensor, a controller, and a battery provided in the aerosol generating device, and the execution function of software for controlling the heating operation of the aerosol generating device.

[0012] The function test is performed by referring to monitoring information relating to the usage history of the aerosol generating device.

[0013] In addition, the step of determining the defective components filters the defective components from among the components of the aerosol generating device based on the cumulative occurrence frequency and recent occurrence frequency of the defective functions relating to the multiple components of the aerosol generating device in the error log.

[0014] In addition, the step of determining the defective function includes determining the function identified by the functional test as the defective function of the defective component if the function identified by the functional test has a predetermined priority among a plurality of functions related to the defective component in the error log.

[0015] The method further includes a step of analyzing a frequency of water-submersion detection for the aerosol generating device, and the step of determining the severity determines the severity of the defective function using a first set of threshold levels if the frequency of water-submersion detection is greater than or equal to a predetermined threshold, and determines the severity of the defective function using a second set of threshold levels if the frequency of water-submersion detection is less than the predetermined threshold.

[0016] Furthermore, the final diagnosis result includes a diagnosis result due to flooding when the frequency of the flooding detection is equal to or greater than the predetermined threshold value.

[0017] The final diagnosis result also includes guide information indicating whether or not the aerosol generation device needs to be disassembled.

[0018] According to another aspect, the aerosol generating device includes a heater that generates an aerosol by heating an aerosol generating material; a battery; a memory that stores information related to a usage history and an error log of the aerosol generating device; and a controller that, when the aerosol generating device does not operate normally due to an error, determines whether to activate a self-diagnosis for analyzing the error of the aerosol generating device, and, when the self-diagnosis is activated, performs a functional test by checking whether each of the functions required for the heating operation of the aerosol generating device to be performed normally is normal, determines a defective component of the aerosol generating device based on a result of the functional test, determines a defective function of the defective component based on the error log, determines a severity of the determined defective function, and outputs a final diagnostic result related to the self-diagnosis based on the defective component, the defective function, and the severity.

[0019] The controller may also determine to activate the self-diagnosis if the error has recently occurred in the aerosol generation device or has occurred in the aerosol generation device a predetermined number of times or more.

[0020] In addition, the controller filters out the defective components among the components of the aerosol generating device based on the cumulative occurrence frequency and recent occurrence frequency of the defective functions related to multiple components of the aerosol generating device in the error log.

[0021] In addition, if a function identified by the functional test has a predetermined priority among a plurality of functions related to the defective component in the error log, the controller determines that the function identified by the functional test is the defective function of the defective component.

[0022] The aerosol generating device further includes a water ingress detection module that detects water ingress into the aerosol generating device, and the controller analyzes the frequency of water ingress detection by the water ingress detection module, and if the frequency of water ingress detection is greater than or equal to a predetermined threshold, determines the severity of the defective function using a first set of threshold levels, and if the frequency of water ingress detection is less than the predetermined threshold, determines the severity of the defective function using a second set of threshold levels.

[0023] According to yet another aspect, a computer readable non-transitory storage medium may include a storage medium having one or more programs stored thereon, the programs including instructions for performing the methods described above.

[0024] The terms used in the embodiments are currently widely used general terms as much as possible while considering the functions of the present invention, but this may vary depending on the intentions of those skilled in the art, precedents, the emergence of new technologies, etc. In addition, in certain cases, the applicant may arbitrarily select terms, and in such cases, the meanings of the terms will be described in detail in the description of the invention. Therefore, the terms used in the various embodiments must be defined based on the meanings of the terms and the overall content of the present invention, not just the names of the terms.

[0025] Throughout the specification, when a part "includes" a certain component, it does not mean excluding other components, but may further include other components, unless otherwise specified to the contrary. Furthermore, terms such as "... unit" and "... module" described in the specification mean a unit that processes at least one function or operation, and it may be realized by hardware or software, or a combination of hardware and software.

[0026] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention is not limited to the embodiments described herein, but may be embodied in many different forms and in any manner that is not intended to be limiting.

[0027] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

[0028] FIG. 1 is a block diagram showing a hardware configuration of an aerosol generating device according to an exemplary embodiment.

[0029] 1, the aerosol generating device 100 includes a battery 110, a heater 120, a controller 130, a user interface 140, a memory 150, and a sensor 160. However, the hardware components inside the aerosol generating device 100 are not limited to those shown in Fig. 1. A person having ordinary skill in the art related to this embodiment would understand that, depending on the design of the aerosol generating device 100, some components may be omitted from the hardware configuration shown in Fig. 1, or new components (e.g., a water intrusion detection module, a connecting port, a communication module, etc.) may be added.

[0030] Hereinafter, the operation of each component included in the aerosol generating device 100 will be described without being limited to the arrangement of each component.

[0031] The battery 110 supplies power used for the operation of the aerosol generating device 100. For example, the battery 110 may supply power to heat the heater 120. The battery 110 may also supply power required for the operation of other hardware components provided in the aerosol generating device 100, i.e., the heater 120, the controller 130, the user interface 140, the memory 150, or the sensor 160. The battery 110 may be a rechargeable battery or a disposable battery. For example, the battery 110 may be a lithium polymer (LiPoly) battery or a lithium ion battery, but is not limited thereto.

[0032] The heater 120 is supplied with power from the battery 110 under the control of the controller 130. The heater 120 is supplied with power from the battery 110 and can heat a cigarette inserted into the aerosol generation device 100 or a cartridge attached to the aerosol generation device 100. That is, the heater 120 can generate an aerosol by heating an aerosol generating material provided in the cigarette and / or the cartridge.

[0033] The heater 120 may be located in the body of the aerosol generating device 100. Alternatively, when the aerosol generating device 100 is composed of a body and a cartridge, the heater 120 may be located in the cartridge. When the heater 120 is located in the cartridge, the heater 120 may be supplied with power from a battery 110 located in at least one of the body and the cartridge.

[0034] The heater 120 may be made of any suitable electrically resistive material. For example, suitable electrically resistive materials may be metals or metal alloys including, but not limited to, titanium, zirconium, tantalum, platinum, nickel, cobalt, chromium, hafnium, niobium, molybdenum, tungsten, tin, gallium, manganese, iron, copper, stainless steel, nichrome, etc. The heater 120 may also be embodied by, but not limited to, a metal hot wire, a metal hot plate having a conductive track disposed thereon, a ceramic heating element, etc.

[0035] The heater 120 can heat a cigarette inserted in the accommodation space of the aerosol generating device 100. As the cigarette is accommodated in the accommodation space of the aerosol generating device 100, the heater 120 can be located inside and / or outside the cigarette. Thus, the heater 120 can heat the aerosol generating material in the cigarette to generate an aerosol.

[0036] Meanwhile, the heater 120 may also be embodied as a configuration included in a cartridge. The cartridge may include the heater 120, a liquid transfer means, and a liquid storage unit. The aerosol generating material contained in the liquid storage unit may move to the liquid transfer means, and the heater 120 may heat the aerosol generating material absorbed in the liquid transfer means to generate an aerosol. For example, the heater 120 may include a material such as nickel chromium and may be wound around the liquid transfer means or disposed adjacent to the liquid transfer means.

[0037] The heater 120 may also be an inductive heater for heating an aerosol product (e.g., a cigarette or cartridge) by induction heating, in which case the heater 120 may include a conductive coil that generates an alternating magnetic field and a susceptor that generates heat in response to the alternating magnetic field.

[0038] The controller 130 is hardware that controls the overall operation of the aerosol generating device 100. The controller 130 includes at least one processor such as an MCU (Micro Controller Unit). The processor may be realized by an array of a number of logic gates, or may be realized by a combination of a general-purpose microprocessor and a memory in which a program executed by the microprocessor is stored. Those skilled in the art will understand that the controller 130 may also be realized by other types of hardware.

[0039] The controller 130 analyzes the results sensed by the at least one sensor 160 and controls subsequent processing based on the results sensed. For example, the controller 130 controls the power supplied to the heater 120 so that the operation of the heater 120 starts or ends based on the results sensed by the at least one sensor 160. The controller 130 may also control the amount of power and the time for which the power is supplied to the heater 120 so that the heater 120 is heated to a predetermined temperature or maintained at a predetermined temperature based on the results sensed by the at least one sensor 160.

[0040] When the controller 130 receives a user input to the aerosol generating device 100, the controller 130 may set the heater 120 to a pre-heating mode to start the operation of the heater 120. In addition, the controller 130 may switch the mode of the heater 120 from the pre-heating mode to the operation mode after sensing a puff by the user using a puff sensor. In addition, the controller 130 may count the number of puffs using the puff sensor, and then interrupt the power supply to the heater 120 if the number of puffs reaches a preset number.

[0041] The controller 130 may control the user interface 140 based on the result sensed by at least one sensor 160. For example, after counting the number of puffs using a puff sensor, if the number of puffs reaches a preset number, the controller 130 may notify the user that the aerosol generating device 100 will soon be shut down using at least one of a lamp, a motor, and a speaker.

[0042] Meanwhile, the controller 130 may perform self-diagnosis regarding errors or failures occurring in the hardware components of the aerosol generating device 100, such as the battery 110, the heater 120, the user interface 140, the memory 150, and the sensor 160, and in the control software for controlling such hardware components. The controller 130 may generate an error report regarding the self-diagnosis result. The performance of the self-diagnosis by the controller 130 will be described in more detail with reference to the following drawings.

[0043] The user interface 140 provides the user with information related to the status of the aerosol generating device 100. The user interface 140 may include various interfacing means such as a display or lamp for outputting visual information, a motor for outputting tactile information, a speaker for outputting sound information, a terminal for data communication with an input / output (I / O) interfacing means (e.g., a button or a touch screen) for receiving information input from a user or outputting information to a user, a terminal for receiving charging power, and a communication interfacing module for wireless communication with an external device (e.g., WI-FI, WI-FI Direct, Bluetooth (registered trademark), NFC (Near-Field Communication), etc.).

[0044] The aerosol generating device 100 may be embodied by selecting one or more of the various user interfaces 140 exemplified above.

[0045] The memory 150 is hardware that stores various data processed in the aerosol generating device 100, and the memory 150 can store data processed by the controller 130 and data to be processed. The memory 150 can be realized by various types of memory such as a random access memory (RAM) such as a dynamic random access memory (DRAM) or a static random access memory (SRAM), a read-only memory (ROM), or an electrically erasable programmable read-only memory (EEPROM).

[0046] The memory 150 may store the operation time of the aerosol generation device 100, the maximum number of puffs, the current number of puffs, at least one temperature profile, data related to the smoking pattern of the user, water immersion information of the aerosol generation device 100, etc. In addition, the memory 150 may store information on the usage history of the aerosol generation device 100, and error log information related to the history of errors / failures that have occurred in the aerosol generation device 100.

[0047] Although not shown in Fig. 1, the aerosol generating device 100 may constitute an aerosol generating system together with a separate cradle. For example, the cradle is used to charge the battery 110 of the aerosol generating device 100. When the aerosol generating device 100 is accommodated in an accommodation space inside the cradle, the aerosol generating device 100 can receive power from the battery of the cradle and charge the battery 110 of the aerosol generating device 100.

[0048] Figures 2A to 2E show various embodiments of the aerosol generating device of Figure 1. Referring to Figures 2A to 2E, various types of aerosol generating devices 200a to 200e are embodied. In Figures 2A to 2E, batteries 110a to 110e, heaters 120a to 120e, and controllers 130a to 130e correspond to the battery 110, heater 120, and controller 130 of Figure 1, respectively.

[0049] FIG. 2A is a diagram illustrating an aerosol generating device 200a including a susceptor according to an example embodiment.

[0050] 2A, the aerosol generating device 200a includes a heater 120a including a coil 121 and a susceptor 122, a battery 110a, and a controller 130a. However, the aerosol generating device 200a is not limited thereto, and may further include other general elements in addition to the elements illustrated in FIG. 2A.

[0051] The aerosol generating apparatus 200a may generate an aerosol by heating a cigarette accommodated therein using an induction heating method. The induction heating method may refer to a method of applying an alternating magnetic field to a magnetic body to heat the magnetic body so that the magnetic body is heated by electromagnetic induction. Thus, the aerosol generating apparatus 200a may heat the cigarette by transferring thermal energy emitted from the magnetic body to the cigarette. Here, the magnetic body that generates heat due to an external magnetic field is also the susceptor 122. The susceptor 122 may be provided in the aerosol generating apparatus 200a or may be included inside the cigarette in the form of a slice, a flake, a strip, or the like.

[0052] The susceptor 122 may be made of a ferromagnetic substance. For example, the material of the susceptor 122 may include a metal or carbon. The material of the susceptor 122 may include at least one of ferrite, a ferromagnetic alloy, stainless steel, and aluminum (Al). The material of the susceptor 122 may also include at least one of graphite, ceramics such as zirconia, transition metals such as nickel (Ni) and cobalt (Co), and semi-metals such as boron (B) and phosphorus (P).

[0053] The aerosol generating device 200a can accommodate a cigarette. A space for accommodating the cigarette may be formed in the aerosol generating device 200a. A susceptor 122 may be disposed around the space for accommodating the cigarette. For example, the susceptor 122 has a tubular shape that surrounds the outside of the cigarette. Therefore, when a cigarette is accommodated in the accommodation space of the susceptor 122, the susceptor 122 may be disposed at a position that surrounds at least a portion of the outer surface of the cigarette. However, the shape of the susceptor 122 is not limited thereto and may be various.

[0054] The coil 121 is arranged to be wound around the outer surface of the susceptor 122, and can apply an alternating magnetic field to the susceptor 122. When power is supplied from the aerosol generating device 200a to the coil 121, a magnetic field can be formed in the inner region of the coil 121. When an alternating current is applied to the coil 121, the direction of the magnetic field formed inside the coil 121 can be changed continuously. When the susceptor 122 is located inside the coil 121 and exposed to the alternating magnetic field whose direction changes periodically, the susceptor 122 generates heat, and the cigarettes accommodated in the susceptor 122 can be heated.

[0055] The battery 110a may supply power to the coil 121 for the heating operation of the aerosol generating device 200a.

[0056] The controller 130a can control the heating operation of the heater 120a by controlling the power supplied to the coil 121. For example, the controller 130 can perform control to keep the heating temperature of the cigarette constant.

[0057] FIG. 2B is a diagram of an aerosol generating device 200b with a replaceable cartridge 220 that holds an aerosol generating material according to an example embodiment.

[0058] 2B includes a cartridge 220 that holds an aerosol generating material and a body 210 that supports the cartridge 220. In this case, the hardware components of the aerosol generating device 200b may be located in the body 210 and / or the cartridge 220.

[0059] A cartridge 220 containing an aerosol generating material may be coupled to the body 210. The cartridge 220 may be attached to the body 210 by inserting a portion of the cartridge 220 into a receptacle in the body 210.

[0060] The cartridge 220 may hold an aerosol generating material that is a liquid composition, but is not limited thereto, and may hold an aerosol generating material that has any one of a solid state, a gas state, or a gel state. For example, the liquid composition may be a liquid that contains a tobacco-containing material that includes a volatile tobacco flavor component, or a liquid that contains a non-tobacco material.

[0061] The heater 120b provided in the cartridge 220 may perform a heating operation in response to an electric signal or a wireless signal transmitted from the body 210. Thus, the aerosol generating material in the cartridge 220 may be vaporized by the heating of the heater 120b to generate an aerosol.

[0062] The heater 120b generates heat by electrical resistance to heat the aerosol generating material transferred to the liquid transfer means. Here, the heater 120b may be implemented as a conductive filament made of a metal material such as copper, nickel, or tungsten, or a ceramic heating element, and may be wound around the liquid transfer means or disposed adjacent to the liquid transfer means.

[0063] 2C-2E are diagrams of aerosol generating devices 200c-200e with a cigarette 260 inserted therein according to an example embodiment.

[0064] Referring to Fig. 2C, the aerosol generating device 200c includes a battery 110c, a controller 130c, and a heater 120c. Referring to Figs. 2D and 2E, the aerosol generating devices 200d and 200e further include a vaporizer 270. The vaporizer 270 includes an aerosol generating substance and may include a separate heater for heating the aerosol generating substance. A cigarette 260 may be inserted into the aerosol generating devices 200c to 200e. The aerosol generating devices 200c to 200e may correspond to the aerosol generating device 100 of Fig. 1.

[0065] In the aerosol generating device 200c of Fig. 2C, the battery 110c, the controller 130c, and the heater 120c are illustrated as being arranged in a line. In addition, in the aerosol generating device 200d of Fig. 2D, the battery 110d, the controller 130d, the vaporizer 270, and the heater 120d are illustrated as being arranged in a line. In contrast, in the aerosol generating device 200e of Fig. 2E, the vaporizer 270 and the heater 120e are illustrated as being arranged in parallel. However, the internal structures of the aerosol generating devices 200c to 200e are not limited to those illustrated in Figs. 2C to 2E.

[0066] When the cigarette 260 is inserted into the aerosol generating device 200c to 200e, the aerosol generating device 200c to 200e may operate the heater (120c to 120e) and / or the vaporizer 270 to generate an aerosol from the cigarette 260 and / or the vaporizer 270. The aerosol generated by the heater 120c to 120e and / or the vaporizer 270 passes through the cigarette 260 and is delivered to the user.

[0067] The batteries 110c to 110e provide the power used to operate the aerosol generation devices 200c to 200e.

[0068] The vaporizer 270 heats the liquid composition to generate an aerosol, and the generated aerosol may be transmitted to the user through the cigarette 260. That is, the aerosol generated by the vaporizer 270 moves along the airflow passage of the aerosol generating device 200d, 200e, and the airflow passage may be configured so that the aerosol generated by the vaporizer 270 passes through the cigarette and is transmitted to the user. For example, the vaporizer 270 may include, but is not limited to, a liquid storage section that stores the liquid composition, a liquid transfer means (e.g., a wick, etc.) that transfers the liquid to a heating element, and a heating element (e.g., a metal hot wire, etc.). The vaporizer 270 is also called a cartomizer or an atomizer.

[0069] Meanwhile, although not shown in Fig. 2A to Fig. 2E, the aerosol generating apparatus 200a to 200e may form a system together with a separate cradle. For example, the cradle may be used to charge the battery 110a to 110e of the aerosol generating apparatus 200a to 200e. Alternatively, the heater 120a to 120e may perform a heating operation using power supplied from the cradle when the cradle and the aerosol generating apparatus 200a to 200e are combined.

[0070] According to various embodiments, the aerosol generating device 100 of FIG. 1 may be embodied by at least one of the types of aerosol generating devices 200a to 200e of FIGS. 2A to 2E, but is not necessarily limited thereto.

[0071] FIG. 3 is a diagram for explaining the self-diagnosis performed in the aerosol generating device according to an exemplary embodiment.

[0072] As described above, the aerosol generating device 100 operates at a relatively high temperature due to heating by the heater 120, unlike other electronic devices. In addition, the liquid aerosol generating material held in the aerosol generating device 100 may leak out, or the vaporized aerosol may gradually permeate into other hardware components through minute gaps in the housing. In this case, an error or failure may occur in the aerosol generating device 100. Therefore, in order to use the aerosol generating device 100 safely and continuously, it is necessary to accurately understand the root cause of the error or failure occurring in the aerosol generating device 100.

[0073] 3, the controller 130 of the aerosol generating apparatus 100 executes a self-diagnosis module 133 to diagnose various types of errors or malfunctions that occur in the aerosol generating apparatus 100. Here, the self-diagnosis module 133 is a software module driven by the controller 130, and corresponds to a diagnostic solution (or diagnostic program) that performs diagnostic processing on various hardware components in the aerosol generating apparatus 100, such as the heater 120, the sensor 160, the battery 110, etc.

[0074] The self-diagnosis module 133 may perform a self-diagnosis on the heater 120. For example, if the heater 120 is not heated to a target temperature despite a predetermined power being supplied thereto, the self-diagnosis module 133 diagnoses that an error exists in the heating function of the heater 120. Also, if the temperature changes too rapidly or the heater 120 overheats despite a constant power supply to the heater 120, the self-diagnosis module 133 diagnoses that an error exists in the heating function of the heater 120. That is, if the heating of the heater 120 is not normally controlled, the self-diagnosis module 133 diagnoses that an error or failure has occurred in the heater 120.

[0075] The self-diagnosis module 133 may perform a self-diagnosis on the sensors 160 provided in the aerosol generating device 100, such as a puff sensor, a heater temperature sensor, and a battery temperature sensor. If the number of puffs is not counted even though the user puffs in the aerosol generating device 100, the self-diagnosis module 133 may detect that there is an error in the puff sensor. Also, if the temperature sensor erroneously senses the temperature or if the temperature sensing function is stopped, the self-diagnosis module 133 may diagnose that the temperature sensor needs to be replaced. That is, if the sensing result is outside the range of the expected sensing result, the self-diagnosis module 133 may determine that there is an error or failure in the sensor 160.

[0076] The battery 110 supplies power for the operation of various hardware components of the aerosol generating device 100. The self-diagnosis module 133 may perform checks such as whether the power (e.g., voltage) provided by the battery 110 is normal, whether the temperature of the battery 110 is normal, etc. If power is not supplied normally or the temperature of the battery 110 is outside the normal range, the self-diagnosis module 133 may diagnose that there is an error or failure in the battery 110. The self-diagnosis module 133 may also determine whether normal operation is possible based on the degree of deterioration of the battery 110.

[0077] The aerosol generation device 100 may additionally include a water inundation detection module 170. Based on the water inundation signal generated by the water inundation detection module 170, the self-diagnosis module 133 may monitor the number of times the aerosol generation device 100 has been inundated with water, or may diagnose that the aerosol generation device 100 has been inundated with water so much that it is unable to operate normally.

[0078] Meanwhile, the self-diagnosis module 133 may perform diagnosis on the control software 135 that controls the operation of the aerosol generating device 100 in addition to the hardware configuration of the aerosol generating device 100. For example, the self-diagnosis module 133 may diagnose errors in the control software 135 by grasping various software execution errors such as a collision, stop, or update failure of the control software 135.

[0079] The self-diagnosis module 133 performs a self-diagnosis on the aerosol generating device 100 and then outputs a self-diagnosis result. The self-diagnosis result may include various error information such as a location where an error occurred, a type of error, a seriousness of the error, and a solution to the error. A user can immediately deal with an error of the aerosol generating device 100 through the self-diagnosis result provided by the self-diagnosis module 133. Hereinafter, a process of performing a self-diagnosis in the aerosol generating device 100 will be described in more detail.

[0080] FIG. 4 is a flowchart illustrating a process in which an aerosol generating device activates a self-diagnosis according to an exemplary embodiment.

[0081] 4, the aerosol generating device (100 in FIG. 1) starts the operation of the aerosol generating device 100 in response to a user request in step 410. The aerosol generating device 100 may start its operation by receiving a user's request to smoke via an input interface such as a physical button or a touch screen, or the user may start the operation of the aerosol generating device 100 by inserting a cigarette into the aerosol generating device 100.

[0082] In step 420, the self-diagnosis module 133 of the controller 130 determines whether an error has occurred in the aerosol generating device 100 after the operation of the aerosol generating device 100 is started. That is, the self-diagnosis module 133 determines whether the aerosol generating device 100 operates normally. If it is determined that an error has occurred, the self-diagnosis module 133 performs step 430. However, if it is determined that no error has occurred, the self-diagnosis module 133 may continue to monitor whether an error has occurred.

[0083] In operation 430, the self-diagnosis module 133 determines whether the current error is the same as an error that has recently occurred in the aerosol generating device 100. Here, the recently occurred error may refer to an error that has occurred after a predetermined reference point in the past. The predetermined reference point may be set in various ways.

[0084] If it is determined that the currently occurring error is the same as the recently occurring error, the self-diagnosis module 133 determines that the aerosol generating device is not operating normally and performs step 450 to activate self-diagnosis. However, if it is determined that the currently occurring error is not the same as the recently occurring error, the self-diagnosis module 133 performs step 440.

[0085] In operation 440, the self-diagnosis module 133 determines whether the current error is the same as an error that has occurred consecutively in the past in the aerosol generating device 100. Here, the error that has occurred consecutively in the past may refer to an error of a type that has repeatedly occurred a predetermined number of times or more in the past. The predetermined number of times may be variously changed according to settings.

[0086] If it is determined that the current error is the same as an error that has occurred consecutively in the past, the self-diagnosis module 133 determines that the aerosol generating device is not operating normally and performs step 450 to activate self-diagnosis. However, if it is determined that the current error is not an error that has occurred consecutively in the past, the self-diagnosis module 133 may continue to monitor whether an error has occurred without activating self-diagnosis.

[0087] At step 450, the self-diagnostics module 133 activates a self-diagnostics to further analyze errors in the aerosol generating device 100.

[0088] The process for activating self-diagnosis described in FIG. 4 is a process for determining whether to start analysis of an error that has occurred in the aerosol generating device 100, and the self-diagnosis module 133 of the aerosol generating device 100 can perform self-diagnosis for error analysis through the process described in the following figures.

[0089] FIG. 5 is a flow chart of a self-diagnosis process performed by an aerosol generating device in accordance with an exemplary embodiment.

[0090] 5, in step 510, when the self-diagnosis is activated, the self-diagnosis module 133 monitors information on the aerosol generating device 100. Specifically, the self-diagnosis module 133 may refer to monitoring information on the usage history of the aerosol generating device 100. For example, the usage history of the aerosol generating device 100 indicates history information on how the user operates or uses the aerosol generating device 100, such as the number of heating operations, the number of charge / discharge operations, the operating time, the number of discharge operations, and the details of repairs performed by the aerosol generating device 100. By monitoring such usage history, the self-diagnosis module 133 may previously know which functions are mainly used in the aerosol generating device 100 and which functions are used incorrectly, and may refer to this information to perform accurate diagnosis in a subsequent diagnosis process.

[0091] In step 520, the self-diagnosis module 133 performs a function self-test (FST) to check whether each function required for the heating operation of the aerosol generating device 100 to be normally performed is normal. The self-diagnosis module 133 may determine an error category based on the result of the function test.

[0092] 3, the self-diagnosis module 133 may perform a functional test on the hardware such as the heater 120, the sensor 160, the controller 130, and the battery 110 provided in the aerosol generating device 100 and the execution function of the control software for controlling the heating operation of the aerosol generating device 100. That is, the self-diagnosis module 133 checks whether each hardware configuration and software execution is operating normally through the functional test.

[0093] In step 530, the self-diagnosis module 133 analyzes the recent operation log of the aerosol generating device 100. The recent operation log embodies the operation state of the aerosol generating device 100 related to the occurrence of an error, such as the most recent heater operation state, battery voltage, and heater temperature.

[0094] In step 540, the self-diagnosis module 133 analyzes the error log (see FIG. 6) of the aerosol generating device 100 to determine the error category (e.g., malfunctioning component) and detailed error item (e.g., description of the malfunction). For example, the self-diagnosis module 133 may determine the error category and error item based on the occurrence frequency of the error category and error item in the error log of the aerosol generating device 100.

[0095] FIG. 6 is a data table depiction showing an error log stored in the memory of an aerosol generating device in accordance with an example embodiment.

[0096] 6, the error log entries are listed in chronological order in a data table 600. Each error log entry includes information about an error category (e.g., a faulty component) in a “Fault Group” column, and information about a detailed error item (e.g., a faulty function of the faulty component) in a “Fault Description” column.

[0097] For example, if the function test result of the aerosol generating device 100 predicts that there is a problem with the heater function, the self-diagnosis module 133 acquires the total heater-related error log entries 610 and the most recent heater-related error log entries 620 from the error log. Then, the self-diagnosis module 133 compares the heater-related error log entries 610 and 620 with the function test result and the operation log of the aerosol generating device 100. As a result of the comparison, the self-diagnosis module 133 may determine that the error category is related to the heater. For example, if the number of the total heater-related log entries 610 exceeds a certain threshold, the self-diagnosis module 133 may determine that the error is related to the heater. Also, if the number of the most recent heater-related log entries 620 exceeds a certain threshold, the self-diagnosis module 133 may determine that the error category is related to the heater. The reference time for determining whether the error log entry is recent may be changed in various ways depending on the embodiment.

[0098] 6 is merely an example. That is, the error log managed by the aerosol generating device 100 may differ from the data table 600 in FIG.

[0099] Hereinafter, the entire self-diagnosis process described in FIG. 5 will be divided into a first, second and third diagnostic process and will be described.

[0100] 7 is a flowchart of a first diagnostic process of the self-diagnosis of the aerosol generating device according to an exemplary embodiment. Referring to FIG. 7, in the first diagnostic process, the self-diagnosis module 133 determines an error category by performing a function test to check whether each function required for the heating operation of the aerosol generating device 100 to operate normally is normal.

[0101] Specifically, in step 710, the self-diagnosis module 133 performs a function test to check whether all functions of the aerosol generating device 100 (e.g., the driving function of the hardware configuration, the execution function of the software) are operating normally.

[0102] In step 720, the self-diagnosis module 133 identifies a defective function (i.e., a function in which an error occurred) based on the functional test results. In step 730, the self-diagnosis module 133 analyzes all error log entries related to the identified defective function. For example, if the defective function is related to a heater, the self-diagnosis module 133 may analyze the error log entry 610 included in the data table 600 of FIG. 6.

[0103] In operation 740, the self-diagnosis module 133 analyzes the most recent error log entry related to the identified defective function. For example, if the defective function is related to a heater, the self-diagnosis module 133 may analyze the error log entry 620 included in the data table 600 of Fig. 6. Meanwhile, as described above, the reference time for determining whether an error log entry is recent may be changed in various ways depending on the embodiment.

[0104] In step 750, the self-diagnosis module 133 determines an error category related to the defective function based on the frequency of occurrence of the defective function analyzed in steps 730 and 740. For example, if the result of the function test indicates that the heater temperature is not accurately controlled, such a defective function may be due to a voltage malfunction (e.g., unstable battery voltage) or a malfunctioning heater. In this regard, the self-diagnosis module 133 may determine whether the error category is related to the heater or the battery. For example, if the error log shows a high frequency of occurrence of an error related to the heater (e.g., "heater temperature abnormal"), the self-diagnosis module 133 may determine the error category to be related to the heater. However, if the error log shows a high frequency of occurrence of an error related to the battery (e.g., "unstable battery voltage"), the self-diagnosis module 133 may determine the error category to be related to the battery.

[0105] The error category determined in step 750 is a first diagnostic result of the self-diagnosis, and the self-diagnosis module 133 may perform a second diagnostic process for a more detailed diagnosis.

[0106] 8 is a flowchart of a second diagnostic process of the self-diagnosis of the aerosol generating device according to an exemplary embodiment. Referring to FIG. 8, in the second diagnostic process, the self-diagnosis module 133 determines detailed error items within the error category determined in the first diagnosis by analyzing error data collected by a function test based on an error log recorded in the aerosol generating device 100.

[0107] Specifically, in step 810, the self-diagnosis module 133 obtains error data collected by the function test, and starts analyzing the obtained error data.

[0108] In step 820, the self-diagnosis module 133 analyzes the error data collected by the functional test based on the error log.

[0109] In step 830, the self-diagnosis module 133 determines whether the defective function identified in the error data corresponds to the first error item (i.e., defective function) among all error items of the error category determined in the first diagnosis in the error log. The first error item is also an error item that has a fatal effect on the function of the aerosol generating device 100. For example, the priority of the error items may be determined based on the occurrence frequency of the error items related to the error category in the error log. In this case, the error item with the highest occurrence frequency may have the priority. However, without being limited thereto, the priority of the error items may be variously changed according to the embodiment. If it is determined that the defective function identified by the function test corresponds to the first error item in the error log, the self-diagnosis module 133 performs step 870. However, if it is determined that the defective function identified by the function test does not correspond to the first error item in the error log, the self-diagnosis module performs step 840.

[0110] In step 840, the self-diagnosis module 133 determines whether the defective function identified in the error data corresponds to the next-ranked error item (e.g., 2nd to 5th rank) among all error items of the error category determined in the first diagnosis in the error log. As described above, the priority of the error items may be variously changed depending on the embodiment. If it is determined that the defective function identified by the functional test corresponds to any one of the next-ranked error items, the self-diagnosis module 133 performs step 870. Otherwise, the self-diagnosis module 133 performs step 850.

[0111] In step 850, the self-diagnosis module 133 determines whether the defective function identified by the functional test corresponds to the first most recent error item of the error category determined in the first diagnosis in the error log. If it is determined that the defective function identified by the functional test corresponds to the first most recent error item, the self-diagnosis module 133 performs step 870. If not, the self-diagnosis module 133 performs step 860.

[0112] At step 860, the self-diagnostic module 133 determines that the cause of the error cannot be identified from the error log.

[0113] In step 870, the self-diagnosis module 133 determines one of the error items ranked 1 to 5 among all error items in the error category determined in the first diagnosis, or the error item ranked 1 among the most recent error items in the error category determined in the first diagnosis, as a minor error item corresponding to a defective function identified by the function test. However, if the cause of the minor error item is determined to be unknown in step 860, the self-diagnosis module 133 determines the minor error item as an unknown error.

[0114] According to the secondary diagnosis process described in Fig. 8, the self-diagnosis module 133 determines a detailed error item corresponding to a defective function identified by a functional test for an error item of a predetermined priority among the error items of the determined error category in the error log. However, if the error item does not exist in the error log, the detailed error item may be determined to be of unknown cause.

[0115] 9 is a flowchart of a third diagnostic process of the self-diagnosis of the aerosol generating device according to an exemplary embodiment. Referring to FIG. 9, in the third diagnostic process, the self-diagnosis module 133 determines the severity of the determined detailed error items, and outputs a final diagnosis result related to the self-diagnosis based on the error category, the detailed error items, and the severity.

[0116] Specifically, in step 910, the self-diagnosis module 133 analyzes how frequently the water ingress detection module (170 in FIG. 3) has detected water ingress in the past.

[0117] In step 920, the self-diagnosis module 133 determines whether the frequency of water ingress detection is equal to or greater than a first threshold value. Here, the first threshold value is a preset value according to the usage environment of the aerosol generating device 100, and is a changeable value. For example, when the aerosol generating device 100 includes a liquid aerosol generating material, the first threshold value may be set to a relatively low value, and when the aerosol generating device 100 does not include a liquid aerosol generating material and uses only a solid aerosol generating material, the first threshold value may be set to a relatively high value. However, such a manner of setting the first threshold value is merely an example, and the first threshold value may be preset to various values ​​to suit the usage environment as described above.

[0118] In step 930, if the frequency of water ingress detection is equal to or greater than the first threshold, the self-diagnosis module 133 determines the severity of the minor error item using a first set of threshold levels.

[0119] In step 940, the self-diagnosis module 133 determines whether water ingress is the cause of the error based on the water ingress detection frequency.

[0120] If the self-diagnosis module 133 determines that water ingress is a factor that contributed to the occurrence of the error, the self-diagnosis module 133 includes the water ingress diagnosis result in the final diagnosis result in step 950. That is, if the frequency of water ingress detection is equal to or greater than a first threshold, the self-diagnosis module 133 may include the water ingress diagnosis result in the final diagnosis result.

[0121] In step 960, if the frequency of water ingress detection is less than the first threshold, the self-diagnosis module 133 determines the severity of the minor error items using a second set of threshold levels.

[0122] The first and second sets of threshold levels for determining the severity are also different from each other. For example, if a user uses the aerosol generation device 100 carefully, the frequency of water ingress detection is relatively low. Conversely, if a user uses the aerosol generation device 100 relatively carelessly, the frequency of water ingress detection is relatively high. In such an aspect, the error severity of an aerosol generation device 100 that has been used carefully is lower than the error severity of an aerosol generation device 100 that has been used carelessly. Therefore, the self-diagnosis module 133 may determine the error severity at different sets of threshold levels in consideration of the frequency of water ingress detection that can infer the user's management state for the aerosol generation device 100.

[0123] Meanwhile, the threshold level may be configured to classify the severity in stages according to the frequency of occurrence of the error item. The threshold level may be preset according to the type of error item, the usage environment of the aerosol generating device 100, and the like.

[0124] In step 970, the self-diagnosis module 133 determines whether or not the aerosol generating device 100 needs to be disassembled, taking into consideration the type and severity of the minor error item.

[0125] At step 980, the self-diagnostic module 133 determines which parts of the aerosol generating device 100 need to be replaced if disassembly is determined to be necessary.

[0126] In step 990, the self-diagnosis module 133 outputs a final diagnosis result related to the self-diagnosis based on the error category, detailed error items, and severity. In this case, the final diagnosis result may include guide information related to the part to be replaced determined in step 980.

[0127] As described in Figures 3 to 9, through the self-diagnosis process (i.e., the first to third diagnostic processes) performed by the controller 130, the aerosol generating device 100 can enter a self-diagnosis mode by itself and provide a diagnostic result if an error occurs.

[0128] 10 is a diagram for explaining an output target of a final diagnosis result according to an exemplary embodiment. Referring to FIG. 10, an error report 1010 corresponding to a final diagnosis result generated by a self-diagnosis performed in the aerosol generating device 100 may be output to various destinations.

[0129] For example, if a user takes the aerosol generating device 100 to a service center 1020, the service center 1020 may connect the aerosol generating device 100 to a diagnostic device and access / download the error report 1010 from the aerosol generating device 100. Through this, the service center 1020 may identify the error in the aerosol generating device 100 and repair or replace the erroneous / broken part, thereby resolving the error in the aerosol generating device 100.

[0130] Alternatively, the aerosol generating device 100 may transmit the error report 1010 to a portable terminal 1030 such as a smartphone or tablet via wired / wireless communication. After checking the error report 1010 on the portable terminal 1030, the user may take the aerosol generating device 100 to a service center 1020 or repair the aerosol generating device 100 directly.

[0131] The aerosol generating device 100 can also display the error report 1010 through the display screen 1040 of the user interface 140.

[0132] An error report 1010, which is a final diagnostic result generated as a result of the self-diagnosis, can be output / provided in various ways so that the user can easily understand the cause of the error.

[0133] 11 is a flowchart of a method for performing a self-diagnosis in an aerosol generating device according to an exemplary embodiment. Referring to FIG. 11, the self-diagnosis method in the aerosol generating device 100 is composed of steps that are processed in a time series manner in the aerosol generating device 100 of the above-mentioned drawings. Therefore, even if the following content is omitted, the content described for the aerosol generating device 100 of the above-mentioned drawings can also be applied to the method of FIG. 11.

[0134] In step 1110, the controller 130 (i.e., the self-diagnosis module 133) determines whether to activate a self-diagnosis for analyzing errors in the aerosol generating device 100 if the aerosol generating device 100 does not operate normally.

[0135] In step 1120, when self-diagnosis is activated, the controller 130 analyzes the error category by performing a functional test to check whether each function required for the normal performance of the heating operation of the aerosol generating device 100 is normal.

[0136] In step 1130, the controller 130 analyzes the error data collected by the function test based on the error log to determine specific error items within the error category.

[0137] In step 1140, the controller 130 determines the severity of the determined detail error item.

[0138] In step 1150, the controller 130 outputs a final diagnosis result related to the self-diagnosis based on the error category, detailed error item, and severity.

[0139] Meanwhile, the above-mentioned method can be created into a program executed by a computer, and can be embodied in a general-purpose digital computer that operates the program using a computer-readable non-transitory recording medium. Also, the data structure used in the above-mentioned method can be recorded in a computer-readable recording medium through various means. The computer-readable recording medium includes recording media such as magnetic recording media (e.g., ROM (Read Only Memory), RAM (Random Access Memory), USB, floppy disk, hard disk, etc.) and optical recording media (e.g., CD-ROM, DVD, etc.).

[0140] Those skilled in the art will understand that the present invention can be embodied in various modified forms without departing from the essential characteristics of the above description. Therefore, the disclosed method should be considered in an illustrative rather than restrictive manner. The scope of the present invention is defined in the claims, not the above description, and all differences within the scope of the equivalents should be interpreted as being included in the present invention.

Claims

1. 1. A method for performing self-tests on an aerosol generating device, comprising: determining whether to activate a self-diagnosis for analyzing the error of the aerosol generating device when the aerosol generating device does not operate normally due to an error; performing a function test by checking whether each function required for a heating operation of the aerosol generating device to be normally performed is normal when the self-diagnosis is activated; determining a defective component of the aerosol generating device based on results of the functional test; and determining a defective function of the defective component based on an error log recorded in the aerosol generating device; determining a severity of the determined defective functionality; outputting a final diagnosis result related to the self-diagnosis based on the defective component, the defective function, and the severity; The step of determining defective components comprises: A method for filtering out defective components among the components of the aerosol generating device based on the cumulative occurrence frequency and recent occurrence frequency of the defective functions relating to multiple components of the aerosol generating device in the error log.

2. The step of determining whether to activate the self-diagnosis further comprises: The method of claim 1 , further comprising determining to activate the self-diagnosis if the error has recently occurred in the aerosol generation device or has occurred in the aerosol generation device a predetermined number of times or more.

3. The functional test includes: The method of claim 1, performed on the driving function of hardware including at least one of a heater, a sensor, a controller, and a battery provided in the aerosol generating device, and on the execution function of software for controlling the heating operation of the aerosol generating device.

4. The method of claim 1 , wherein the functional test is performed by referring to monitoring information relating to the usage history of the aerosol generating device.

5. The step of determining defective functions comprises:

2. The method of claim 1, further comprising: determining a function identified by the functional test as the defective function of the defective component if the function identified by the functional test has a predetermined priority among a plurality of functions related to the defective component in the error log.

6. Analyzing the frequency of water ingress detection for the aerosol generating device; The step of determining the severity comprises:

2. The method of claim 1, further comprising: determining the severity of the defective function using a first set of threshold levels if the frequency of the water submersion detection is equal to or greater than a predetermined threshold; and determining the severity of the defective function using a second set of threshold levels if the frequency of the water submersion detection is less than the predetermined threshold.

7. The final diagnosis result is The method of claim 6 , comprising a diagnosis of water flooding if the frequency of water flooding detection is greater than or equal to the predetermined threshold.

8. The final diagnosis result is The method of claim 1 , further comprising guide information indicating whether or not the aerosol generating device needs to be disassembled.

9. In the aerosol generating device, A heater that generates an aerosol by heating an aerosol generating material; A battery; a memory for storing information related to a usage history and an error log of the aerosol generating device; a controller for determining whether to activate a self-diagnosis for analyzing the error of the aerosol generating device when the aerosol generating device does not operate normally due to an error, and for performing a function test by checking whether each function required for a heating operation of the aerosol generating device to be normally performed is normal when the self-diagnosis is activated, determining a defective component of the aerosol generating device based on a result of the function test, determining a defective function of the defective component based on the error log, determining a severity of the determined defective function, and outputting a final diagnosis result related to the self-diagnosis based on the defective component, the defective function, and the severity, The controller: An aerosol generating device that filters out the defective components among the components of the aerosol generating device based on the cumulative occurrence frequency and recent occurrence frequency of the defective functions related to the multiple components of the aerosol generating device in the error log.

10. The controller: The aerosol generating device according to claim 9 , wherein the self-diagnosis is determined to be activated if the error has recently occurred in the aerosol generating device or has occurred a predetermined number of times in the aerosol generating device.

11. The controller: The aerosol generating device of claim 9, wherein if a function identified by the functional test has a predetermined priority among multiple functions related to the defective component in the error log, the function identified by the functional test is determined to be the defective function of the defective component.

12. a water ingress detection module for detecting water ingress into the aerosol generating device; The controller: Analyzing the frequency of water submersion detection by the water submersion detection module; The aerosol generating device of claim 9, wherein if the frequency of the water-immersion detection is greater than or equal to a predetermined threshold, a first set of threshold levels is used to determine the severity of the defective function, and if the frequency of the water-immersion detection is less than the predetermined threshold, a second set of threshold levels is used to determine the severity of the defective function.

13. A non-transitory computer-readable recording medium having a program recorded thereon for causing a computer to execute the method of claim 1.

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