Control method for an aerosol generator using a histogram

Abstract

A computer-implemented method for controlling an aerosol generator is provided, the method comprising: collecting multiple values ​​of at least one usage pattern parameter related to the use of the aerosol generator; creating a histogram by classifying each collected value of the usage pattern parameter into histogram bins; extracting histogram feature information from the histogram; and controlling the aerosol generator using operational constraints based on the histogram feature information.

Description

Technical Field

[0001] The present disclosure relates to a computer-implemented method for controlling an aerosol generating device. The present disclosure further relates to an aerosol generating device, an aerosol generating system comprising an aerosol generating device and a companion device, a computer program, and a computer-readable medium.

Background Art

[0002] An aerosol generating device is typically designed as a handheld device that can be used by a user to consume or experience an aerosol generated by heating an aerosol generating substrate or aerosol generating article, for example, in one or more usage sessions. The aerosol generating devices to which the present disclosure relates are commonly referred to as heated tobacco products (HTPs), heat-not-burn devices, electronic cigarettes, and / or vaporizers. The applicant sells such devices under the brand name IQOS (registered trademark), for example.

[0003] An exemplary aerosol-generating substrate may include a solid substrate material such as tobacco material or tobacco cast leaf (TCL) material. The substrate material may, for example, be assembled with other elements or components to form a substantially stick-shaped aerosol-generating article. Such a stick or aerosol-generating article may be configured in a shape and size that is at least partially inserted into an aerosol generator, which may, for example, include a heating element or heater device for heating the aerosol-generating article and / or aerosol-generating substrate. Alternatively or additionally, the aerosol-generating substrate may include one or more liquids and / or solids that may be supplied to the aerosol generator, for example, in the form of a cartridge or container. A corresponding exemplary aerosol-generating article may, for example, include a refillable cartridge containing a liquid and / or solid substrate that may vaporize during aerosol consumption by the user based on heating the substrate and / or liquid. Typically, such a cartridge or container may be connected to, attached to, or at least partially inserted into an aerosol generator. Alternatively, the cartridge may be permanently mounted to an aerosol generator and refilled by inserting liquid and / or solid into the cartridge.

[0004] To generate aerosols during use or consumption, heat may be supplied by a heating element, heater device, or heat source to heat at least a portion of the aerosol generating substrate. The heating element, heater device, or heat source may be disposed within the handle of a handheld device or aerosol generating device. Alternatively, or additionally, at least a portion or all of the heating element, heater device, or heat source may be fixedly associated with or disposed with the aerosol generating article in the form of a stick or cartridge, which may be attached to and / or powered by the handle of a handheld device or aerosol generating device.

[0005] Exemplary heating elements or heater devices may be based on one or more of resistance heating, induction heating, and microwave heating, using electrical energy supplied via, drawn from, or stored within the battery of an aerosol generator. As used herein, the battery of an aerosol generator may generally refer to an energy storage of an aerosol generator configured to store electrical energy. Consequently, the term battery may include one or more capacitors, one or more accumulators, or other types of energy storage. Furthermore, any reference to a battery herein may include multiple batteries.

[0006] Typically, an aerosol generator may be equipped with a battery that provides the necessary electrical energy to operate the aerosol generator and, in particular, to heat the aerosol generating substrate and / or articles, for example, to generate aerosols in one or more use sessions using one or more aerosol generating articles. The battery may be, for example, a lithium-ion battery. The battery capacity may typically be chosen so that the aerosol generator can provide the user with at least a minimum number of uses, for example, at least two or more consecutive use sessions or experiences, without requiring the battery or aerosol generator to be recharged midway. To improve the user experience, the aerosol generator is usually designed to allow the user to start a use session only when the battery contains enough electrical energy to completely complete the use session. However, the energy required for a use session can be highly variable and may depend on numerous factors, from external parameters such as ambient temperature to user habits. Conventional statistical models used to control aerosol generators may be hampered by the limited computing power typically available on these devices. Furthermore, for example, taking the average energy consumption per usage session may lead to overgeneralization in some cases or for certain parameters, and therefore may not result in an accurate estimate of individual usage cases at hand. Consequently, it may occur that a user may be denied further usage sessions even when there is a good opportunity for such sessions to be fully provided under certain circumstances.

[0007] Therefore, it may be desirable to provide improved control of aerosol generators and / or aerosol generation systems.

[0008] This is achieved by the subject matter of the independent claim. Optional features are provided by the dependent claims and the specification. [Overview of the project]

[0009] According to one aspect of the present disclosure, a computer-implemented method for controlling an aerosol generator is provided, the method comprising: collecting a plurality of values ​​of at least one usage pattern parameter related to the use of the aerosol generator; creating a histogram by classifying each collected value of the usage pattern parameter into histogram bins; extracting histogram feature information from the histogram; and controlling the aerosol generator using operational constraints based on the histogram feature information. In other words, the method may also include controlling the aerosol generator based on the histogram feature information by adapting the operational constraints of the aerosol generator.

[0010] Usage pattern parameters may indicate different usage and / or operating characteristics of an aerosol generator by a user. For example, usage pattern parameters may describe or relate to parameters that describe a user's use or operation of an aerosol generator, specifically how, and / or how often, and / or when, and / or how long, and / or under what conditions the aerosol generator is used or operated by the user, and / or has been used or operated. Usage pattern parameters may also relate to, or relate to, usage sessions of the aerosol generator and the time between usage sessions, for example, one or both of the aerosol generator's downtime or recharge events. Thus, the usage pattern parameters described herein, which may also be referred to herein as “parameters,” may characterize the different preferences and / or habits of individual users, which may vary among users. Therefore, the method may provide a highly individualized control of the aerosol generator.

[0011] In one embodiment, at least one of the usage pattern parameters may indicate the user's use or operation of the aerosol generator to generate aerosols in one or more usage sessions. For example, the fume extraction volume may be measured during one or more usage sessions and collected as a usage pattern parameter. The average or mean value may be calculated from multiple, e.g., all fume extractions from a single usage session. Additionally, or by other means, the fume extraction volume may be measured during two or more usage sessions. The average or mean value may be calculated from multiple, e.g., all fume extractions from all usage sessions. Additionally, or by other means, there may be parameters that can only be determined by observing two or more usage sessions. For example, the rest time between usage sessions can only be determined when two usage sessions occur. In another embodiment, the frequency may be at least two usage sessions that occur consecutively without any recharging of the aerosol generator in between. This parameter can also only be determined by observing two or more usage sessions. The values ​​of the usage pattern parameters may be numerical values ​​corresponding to the degree, magnitude, or count of the usage pattern parameter.

[0012] A histogram may be an approximation or simplified representation of the distribution of numerical data, for example, the values ​​of at least one used pattern parameter. In a histogram, each value may be classified into a bin, which represents a range or interval of numerical values. Values ​​that fall outside the range or interval of a single bin may be classified into a different bin or may be optionally ignored. The bins of a histogram may represent consecutive, adjacent, and non-overlapping intervals or ranges of values ​​for the used pattern parameter. However, at least some bins may overlap. The bins may, but are not required, have the same size or width range or interval. Thus, the definition of a histogram in the context of this disclosure may be the same as that used in conventional methods.

[0013] One of the advantages of using histograms in this invention lies in the fact that histograms can approximate and therefore simplify the distribution of usage pattern parameter values. Thus, they may require far less computational power to manipulate and extract information from them than other statistical approaches. At the same time, histograms may provide a more detailed resolution of the underlying data than, for example, averaging values ​​applied by conventional methods. The inventors have found that, particularly when observing the usage pattern parameters of aerosol generator users, there are often bimodal or multimodal patterns that represent additional information in the data that would be lost when averaging. For example, a user who experiences 2-minute and 6-minute usage sessions with equal frequency using an aerosol generator would be assumed to have an average usage session duration of 4 minutes, which would not accurately represent a single usage session among the actual usage sessions experienced by that user. In contrast, histograms may clearly show this bimodal distribution, which may be taken into consideration when controlling the aerosol generator.

[0014] Therefore, a key feature of the present invention may be the extraction of histogram feature information from a histogram. Histogram feature information may correspond to, be associated with, or represent one or more histogram features. Histogram feature information may be representative of the probability that, in the future, preferably in the near future, the usage pattern parameter will have a particular value or will be within a particular range or interval of values. In one embodiment, histogram feature information may be representative of the probability that, in the next, approaching, or recently started usage session or pause period, the usage pattern parameter will have a particular value or will be within a particular range or interval of values. This probability may be determined empirically from the data in the histogram, as will be described in more detail below. Based on the histogram feature information, for example, based on the probability of future values ​​of the usage pattern parameter, the aerosol generator may be controlled to adapt and / or predict this future value, and in particular, the approaching usage session or pause period.

[0015] Controlling an aerosol generator based on histogram feature information involves fitting the aerosol generator's operational constraints or operation constraints to the histogram feature information in such a way that the operational constraints of the aerosol generator fit the histogram feature information, and therefore fit the individual user preferences of the aerosol generator. The operational constraints of the aerosol generator may be increased, tightened, decreased, or loosened. For example, if the currently implemented operational constraints of the aerosol generator indicate that no further usage sessions will be provided to the user, but the histogram feature information indicates that another usage session can actually be provided according to the user's individual habits, then the currently implemented operational constraints may be changed, in this case loosened, to allow the device to provide another usage session to the user. Conversely, if the currently implemented operating constraints of an aerosol generator indicate, for example, that three usage sessions may be provided to a user using one fully charged battery, but histogram feature information indicates that only two usage sessions may be provided according to the user's individual habits, then the currently implemented operating constraints may be modified to tighten so that only two usage sessions are provided to the user using one fully charged battery. These may relate to the usage sessions and / or charging of the aerosol generator. Operating constraints may also include limitations on the battery and / or power consumption management of the aerosol generator. These may also include limitations on the length / duration and / or number of usage sessions provided to the user before the battery is recharged. For example, the operating constraints of an aerosol generator may be duration, such as the length of time a usage session lasts.If the histogram features extracted from the histogram indicate that the battery capacity is sufficient to support one or more usage sessions of longer durations, as currently set, the maximum duration of one or more usage sessions, for example, all usage sessions, may be increased. Conversely, if the histogram features extracted from the histogram indicate that the battery capacity is not sufficient to support one or more usage sessions of the duration currently set, the maximum duration of one or more usage sessions, for example, all usage sessions, may be reduced. In this way, the individual maximum duration of usage sessions may be found for each individual user. Other operational constraints may include, for example, the total number of usage sessions provided to the user before the battery is recharged, regardless of whether further usage sessions are allowed, the charge state of the battery at the time of charging, or the charging rate at which the battery is charged. These constraints are further described below.

[0016] Usage pattern parameters may be collected over a predetermined period. This predetermined period may be, for example, a certain number of hours, days, weeks, or months after the first use of the aerosol generator. Alternatively, the predetermined period may be the entire time since the first use of the aerosol generator. Optionally, the aerosol generator may be designed or configured to collect usage pattern parameters, preferably automatically, periodically, and / or continuously.

[0017] Collecting usage pattern parameters may include storing corresponding data displaying one or more usage pattern parameters in the data storage of, for example, the aerosol generator or another device communicably connected to the aerosol generator. Alternatively or additionally, the aerosol generator may include means for storing data, preferably numerically, for determining and / or displaying the usage pattern parameters, or their corresponding values. These means may include, for example, counters and / or timers, and / or sensors such as temperature sensors, volume sensors, humidity sensors, and others. In one embodiment, usage pattern parameters may be collected over the entire lifespan of the aerosol generator, which may mean from the first usage session to the last usage session of the aerosol generator.

[0018] The aerosol generator may have storage or memory in which collected parameters, parameter values, and / or corresponding data may be stored. Collected usage pattern parameters may also be stored in a user profile and / or transferred to another aerosol generator or other device that can be communicatively connected to the aerosol generator, such as a companion device, server, smartphone, or other computing device.

[0019] At least one usage pattern parameter is the following parameter: - Energy consumption per session, - The number of usage sessions in which the aerosol generator operated to generate aerosols (preferably per a predetermined time interval, for example, per day), - Duration of session used, - A pause between consecutive usage sessions, preferably such that the usage pattern parameter value for the pause between consecutive usage sessions changes only for the pause between subsequent usage sessions of 0 to 40 minutes. - The frequency with which at least two consecutive use sessions occur, especially without recharging the aerosol generator between them (also known as a back-to-back regime), - Ambient temperature during the session, - Ambient air pressure during the session, - Ambient humidity during the session, - Ambient temperature during recharging of the aerosol generator's battery, - Battery temperature of the aerosol generator during the session, - The temperature of the heating element or heater device of the aerosol generator during a predefined period prior to the start of the session. - Number of puffs per session, - Smoke absorption volume, - Frequency of smoking, - Smoking rhythm, - Start time of pause mode in aerosol generator, - End time of pause mode in aerosol generator, - Duration of pause mode in aerosol generator, - The downtime after recharging the aerosol generator, -Hibernation time with battery charge below 10%, -Hibernation time with battery charge exceeding 90%, - The density of the aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols. - The weight of the aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols, - The type of aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols, - Humidity of aerosol generating substrate or aerosol generating article used in aerosol generating device, - A temperature profile selected by the user, may be selected from.

[0020] The energy consumption per use session may, for example, describe the amount of electrical energy consumed from the battery of the aerosol generating device to provide or supply the use session, from the start to the end of the use session. This may be expressed in units of battery capacity, for example, as a percentage of the state of charge (SOC) of the battery consumed to provide the use session. This may also be expressed, for example, in mAh, which is a standard expression of battery capacity, as the total amount of battery capacity required to provide the use session.

[0021] The number of use sessions of the aerosol generating device, each the number of use sessions during which the aerosol generating device has operated, may be a relevant parameter as it may characterize the intensity of use of the device by the user. Thus, this may make it possible to distinguish occasional users from heavy users and may be used to describe the progression over the life of the device and / or battery. Alternatively, the number of use sessions may be related to a criterion different from a predetermined time interval. For example, the number of use sessions between recharges of the device may be collected. For this value, the amount of time between two consecutive recharge events of the device may be irrelevant.

[0022] The method according to the present disclosure may include any one or any combination of the listed parameters, but it is particularly preferred that at least one usage pattern parameter is preferably selected from the parameters of energy consumption per use session and / or number of use sessions during which the aerosol generating device operates to generate aerosol per predefined time interval.

[0023] The duration of a single use session varies by user and may affect battery drain. Since the aerosol generator should preferably maintain a heating temperature during this period, the amount of energy required for a use session may be highly correlated with its duration. As just one example, a typical aerosol generator allows for use sessions of up to 6 minutes.

[0024] The rest period between consecutive usage sessions may relate to the temperature of the device, its heating element, and the battery. During a usage session, the heating element, device, and battery may be heated by heating the aerosol generating substrate or article. After a usage session, the device and battery begin to cool down until they reach ambient temperature. This duration can be called the rest period. In a non-limiting embodiment, after about 40 minutes, the battery typically reaches ambient temperature, which may mean that, in terms of temperature, different rest periods of 40 minutes or more may have the same effect. For this reason, optionally, only rest periods between 0 and 40 minutes may result in different values ​​for the corresponding usage pattern parameters, while times longer than 40 minutes may have the same value. Shorter rest periods, not long enough for the device to reach ambient temperature, may place less strain on the battery and therefore result in less battery degradation.

[0025] The frequency with which at least two consecutive use sessions occur without recharging the aerosol generator or battery in between is sometimes referred to as a back-to-back regime. This parameter may be described, for example, by the percentage of consecutive use sessions that occur without the aerosol generator or battery being recharged before the start of the second use session. For example, in an aerosol generator designed or configured to provide two use sessions after a full battery charge, recharging the aerosol generator after each use session would result in a back-to-back regime of 0%, while recharging the device only after two use sessions have been performed would result in a back-to-back regime of 100%. A 50% back-to-back regime would describe recharging the device for half the time after one use session and then recharging for the remaining time only after two use sessions. Generally, the frequency with at least two consecutive use sessions may be determined by dividing the number of consecutive use sessions by the total number of use sessions.

[0026] In this disclosure, "smoke extraction" may describe the act of a user pulling and / or inhaling an aerosol generator while inhaling a mixture of air and aerosol. "Smoke extraction volume" may describe the volume of the mixture inhaled in a single pull or inhale. "Smoke extraction frequency and rhythm" may describe the corresponding patterns in the occurrence of smoke extraction characteristics for individual users. As merely an example, a typical aerosol generator is designed to allow up to 14 smoke extractions per aerosol generating article.

[0027] The term "pause mode" may refer to a special mode of an aerosol generator that allows for pausing during a usage session. Therefore, pause mode may not be related to, and may differ from, the rest period between usage sessions.

[0028] The aerosol generator may operate in at least two operating modes: an aerosol release mode and a pause mode. The aerosol generator may be configured to heat the heating element, aerosol generating article, and / or substrate at a first temperature level in the aerosol release mode, where the first temperature level may correspond to a predetermined heating temperature or a temperature above it, which may be sufficient to generate an aerosol. The aerosol generator may be further configured to heat the heating element, aerosol generating article, and / or substrate at a second temperature level below the first temperature level in the pause mode of the aerosol generator. The second temperature level may refer to, for example, a temperature above room temperature and below the first temperature level.

[0029] A user experience, also referred to herein as a use session or experience of an aerosol-generating article, may be interrupted, for example, by switching the device to pause mode and later resumed by the user, during which the aerosol-generating article or substrate is kept at a temperature below a first temperature level and / or below a predetermined heating temperature used during normal use of the device (specifically, during a user experience or use session), but still above or well above room temperature. That is, the second temperature level may preferably be chosen to avoid degradation of the undepleted substrate or aerosol-generating article. Specifically, the second temperature level may be chosen to be low enough to minimize depletion of the substrate or article during pause mode, and at the same time high enough to avoid vapor condensation in the device, which could otherwise affect the quality of the undepleted aerosol-generating substrate or article.

[0030] During use of the device, specifically when a user experience or usage session is taking place, the aerosol generator may operate in aerosol release mode, while during pauses in the use of the device, i.e., when no user experience or usage session is taking place and / or when a usage session is interrupted by a pause, the aerosol generator may operate in pause mode. During both the aerosol release mode and the pause mode of the aerosol generator, the heating element, heating circuit and / or heating arrangement may be operating, specifically in heating operation, but nevertheless at different temperature levels, i.e., during aerosol release mode, there may be a first temperature level which is selected to be sufficiently high to generate aerosols, and during pause mode, there may be a second temperature level which is lower than the first temperature level which is selected to be sufficiently low to avoid degradation while minimizing substrate depletion.

[0031] Depending on the type and composition of the specific aerosol-generating article or substrate used with the device, the first temperature level may be in the range of 250°C to 450°C, more specifically 270°C to 430°C, and more specifically 315°C to 355°C. These temperatures may be suitable operating or heating temperatures sufficient to allow volatile compounds to be released from the aerosol-generating article or substrate, for example, during one or more usage sessions and / or when the device is operated in aerosol-release mode. For example, the first temperature level and / or heating temperature for liquid aerosol-generating articles or substrates may be lower than the first temperature level for solid aerosol-generating articles or substrates.

[0032] Generally, the second temperature level may be chosen to maintain the usefulness of the aerosol-generating article or substrate for an extended period. The second temperature level may also depend on the type and composition of the aerosol-generating article or substrate used with the apparatus. As a result, the second temperature level may be in the range of 175°C to 225°C, specifically 185°C to 215°C, and more specifically 195°C to 205°C. These temperatures may be low enough to minimize substrate depletion during pause mode, but at the same time, they may be high enough to avoid vapor condensation within the apparatus, which could lead to degradation of the aerosol-generating article or substrate.

[0033] To avoid condensation effects in the apparatus, specifically to avoid condensation of aerosol-generating articles or substances within the substrate, the second temperature level may be at least 150 degrees Celsius, specifically at least 175 degrees Celsius, preferably at least 185 degrees Celsius, and more preferably at least 195 degrees Celsius.

[0034] Conversely, in order to minimize the depletion of the substrate or article during the pause mode, the second temperature level may be up to 220 degrees Celsius, specifically up to 225 degrees Celsius, preferably up to 215 degrees Celsius, and more preferably at least 205 degrees Celsius. Specifically, the second temperature level may be chosen to reduce aerosol formation by at least 50 percent compared to the aerosol release mode.

[0035] The second temperature level may be relatively lower than the first temperature level by, for example, at least 50 degrees Celsius, more specifically at least 75 degrees Celsius, and more specifically at least 100 degrees Celsius.

[0036] The given temperature value is preferably the average temperature of the aerosol-generating article or substrate during the operation of the apparatus. In addition, as already mentioned, the temperature value may depend, in particular, on the type and composition of the aerosol-generating article or substrate used in the apparatus.

[0037] As used herein, pause mode may refer to a first operating mode of the aerosol generator in which the heating elements, heating circuits, and / or heating arrangements are operated during pause, i.e., the use of the aerosol generator is paused, i.e., the user experience or use session is paused and aerosol generation may not occur or be reduced to at least a minimum level. In other words, in pause mode, the aerosol generator is in a paused state of use.

[0038] Conversely, the aerosol emission mode may also refer to a second operating mode of the aerosol generator, which is the normal heating operation mode of the heating element, heating circuit, and / or heating arrangement for aerosol generation, where the heating element, heating circuit, and / or heating arrangement may operate while the user is using the device, i.e., when a user experience or usage session takes place, specifically when aerosol generation is occurring. Generally, aerosol generation may be performed continuously or on demand, specifically on a fume extraction basis, i.e., at the user's request when fume extraction is performed.

[0039] The density, weight, type, and / or humidity of the aerosol-generating substrate or aerosol-generating article may be detected by an aerosol generator that recognizes, senses, and / or identifies the stick or cartridge, for example, through RFID or other means. These factors may affect the energy required for aerosol generation from the substrate or article, and therefore may also affect battery degradation.

[0040] The method may also include collecting two or more usage pattern parameters, creating a histogram for each of the usage pattern parameters, and controlling the aerosol generator based on histogram feature information extracted from the multiple histograms. The two or more usage pattern parameters may be selected from the list described above. If the method described herein relates to two or more usage pattern parameters, for example, at least two usage pattern parameters, these usage pattern parameters may be different from each other. Thus, each parameter may be one of the parameters listed above, and each parameter may be different from the others. Specifically, it should be noted that, as used herein, two usage pattern parameters may not describe or refer to different values ​​of the same parameter, e.g., numerical values, but rather may describe or refer to values ​​of different parameters. Each usage pattern parameter may be used to create at least one separate histogram. In this way, information from an arbitrary number or all of the collected usage pattern parameters may be extracted from the histograms. Therefore, the method according to this disclosure may provide detailed and highly personalized information on which an aerosol generator may be controlled.

[0041] In both cases where one histogram or two or more histograms are used in the present invention, it may be provided that at least one histogram feature information extracted from the histograms is weighted differently from others. In addition or by other means, it may be provided that histogram feature information extracted from different histograms is weighted differently. For example, at least one or each histogram feature information may be provided with a weighting factor or multiplier, such as a multiplier factor, which increases or decreases the numerical value provided by the histogram feature information and used to control the aerosol generator. Thus, the method may take into consideration that different histogram feature information and / or different histograms and / or different usage pattern parameters may have different importance for controlling the aerosol generator. Therefore, the numerical values ​​of more important histogram feature information and / or histograms and / or usage pattern parameters may increase and thus have a greater impact on the control of the aerosol generator, and then have less important histogram feature information and / or histograms and / or usage pattern parameters, and vice versa.

[0042] Generally, extracted histogram feature information or histogram features may relate to any information available in or deriveable from the data relating to one or more usage pattern parameters provided as a histogram. As described above, providing data to one or more histograms may simplify further processing of the data and require less computational power than conventional statistical methods, while potentially increasing the informational content that can be derived or obtained from one or more histograms.

[0043] In one embodiment, the histogram feature information is: - One or more local maximums in the histogram, - Identity of one or more bins in the histogram corresponding to one or more local maxima in the histogram, - One or more heights of the histogram bins, where the bins preferably correspond to one or more local maximums of the histogram, - The sum of the heights of two or more bins in a histogram, preferably the bins whose heights are summed are adjacent to each other, - The average of the values ​​of the usage pattern parameter classified into one or more bins in the histogram. - The median value of the usage pattern parameter that is classified into one or more bins in the histogram. - The maximum value of the usage pattern parameter that is classified into one or more bins in the histogram. - Includes at least one of the minimum values ​​of the usage pattern parameter that are classified into one or more bins in the histogram.

[0044] A histogram's maxima may be a bin or a group of adjacent bins that has a height higher than, for example, an adjacent bin or group of adjacent bins. For example, a maxima may be defined as the bin with the maximum height among all the bins in the histogram. For the purpose of finding the maxima, the heights of adjacent bins may also be summed together. Thus, a maxima may represent or indicate a bin or group of bins (and therefore a range of values ​​for the usage pattern parameter represented by the bin) where more usage pattern parameter values ​​may be classified than other areas of the histogram. A single histogram may have one or more maxima in, for example, a bimodal or multimodal distribution of usage pattern parameter values.

[0045] The identity of one or more bins may correspond to a range of values ​​for the usage pattern parameters classified into that bin. By identifying the maximal bins, a range of usage pattern parameter values ​​that frequently occur during the collection of usage pattern parameter values ​​may be identified.

[0046] Preferably, the height of a bin may correspond to, or be proportional to, the number of values ​​of the usage pattern parameter that are classified into that bin. For example, if three values ​​of a particular usage pattern parameter fall within the range of a particular bin and are therefore classified into that bin, the height of that bin may be 3. Thus, it is immediately apparent that the heights of one or more bins may be added together. For example, the heights of adjacent or neighboring bins may be added together.

[0047] A comparison may be provided between the total heights of two or more bin groups in one or more histograms. For example, the total height of all bins associated with at least one local maximum may be compared to the total height of all other bins, specifically all other bins not associated with at least one local maximum. In this way, the probability that an approaching event, e.g., a usage session or a period of inactivity, falls within a range of values ​​represented, in this case also by the summed bins, can be calculated quickly and easily, as will be explained in more detail below. The fact that an approaching event falls within a range of values ​​represented, in this case also by a bin, or by two or more bins, may mean that if a value for the usage pattern parameter in the problem were determined for this event, the value would be classified into this bin or this group of bins.

[0048] In general, there are numerous different conclusions that may be drawn from the extracted histogram feature information and may also be used to control the aerosol generator. The method may include, for example, determining from the histogram feature information, for example, within a given degree of certainty, the number of usage sessions that can be provided to the user for aerosol generation by the maximum battery capacity of the aerosol generator. Many of the usage pattern parameters described above affect energy consumption during a usage session and may therefore be used for this determination.

[0049] In one embodiment, a suitable parameter may be the number of use sessions in which the aerosol generator operated to generate aerosols between recharging and / or energy consumption per use session. For example, during the time in which the use pattern parameters are collected, it may be determined that X use sessions can be provided between two consecutive recharge events. Thus, it may be assumed that this number of use sessions can be provided to the user again. Alternatively, during the time in which the use pattern parameters are collected, it may be determined that X use sessions can be provided, taking into account the maximum capacity of the aerosol generator's battery, because the energy consumption per use session is very high. It may then be assumed that this number of use sessions can be provided to the user again. The maximum capacity of the battery may be the nominal, initial, or original maximum capacity of the aerosol generator's battery, or the current maximum capacity. Over the lifespan of the aerosol generator, the battery capacity may degrade with use. Thus, the current maximum capacity of the battery may describe, or relate to, the actual state of the battery currently in use in the device. Hence, the current maximum capacity of the battery may be less than the nominal, initial, or original maximum capacity. There are several methods that can be used to determine the current battery capacity or the state of battery degradation, and therefore do not need to be explained in detail.

[0050] Throughout this disclosure, a certain degree of certainty may mean having a certainty of 95%, 90%, 85%, 80%, 75%, or 70%. For example, it may be determined from collected values ​​of a pattern parameter used that X% of the value falls within a certain numerical range, which is represented by one or more bins in a histogram. It may then be determined that an approaching value of the pattern parameter used may fall within this numerical range with a certainty of X%. The certain degree of certainty may then be X%. The certain degree of certainty may also be a fixed value, e.g., Y%. It may then be provided that only bins representing at most Y% of the pattern parameter used are considered, and / or that there may be a comparison between this Y% and the X% determined as described above. The result of this comparison, e.g., whether X% is above or below Y%, may then be used to control the aerosol generator.

[0051] The method may additionally or alternatively include, for example, determining from histogram feature information whether additional usage sessions can be provided by considering the current charge state of the aerosol generator's battery, within a predetermined degree of certainty. For example, if the average energy consumption per usage session determined from the histogram is higher than the current charge state of the battery, it may be determined that additional usage sessions cannot be provided. Conversely, if the average energy consumption per usage session determined from the histogram is lower than the current charge state of the battery, it may be determined that additional usage sessions can be provided. Instead of average energy consumption, the histogram can be used to determine which proportion of the total usage sessions used less energy than the current charge state of the battery. For this purpose, for example, the heights of all bins representing energy consumption below the current charge state of the battery may be summed together and divided by the sum of the heights of all other bins in the histogram relating to energy consumption per usage session. The result may be equal to the probability that the current charge state of the battery may be sufficient for the approaching usage session, and therefore the probability that additional usage sessions can be provided.

[0052] Considering the results determined from the histogram feature information of the embodiments described above, controlling the aerosol generator based on such histogram feature information may involve adjusting operational constraints that apply to, or include, the total number of use sessions provided to the user to generate aerosols before the aerosol generator's battery is recharged. In other words, operational constraints may include limitations on battery and / or power consumption management. Therefore, controlling the aerosol generator based on such histogram feature information may involve limiting the total number of use sessions provided to the user to generate aerosols before the aerosol generator's battery is recharged to a number of use sessions that can be provided within a certain degree of certainty. In addition, or otherwise, controlling the aerosol generator based on such histogram feature information may involve enabling or preventing additional use sessions before the aerosol generator's battery is recharged. This may also be achieved by adjusting operational constraints that apply to, or include, limitations on battery and / or power consumption management. In addition, or otherwise, in this case as well, controlling the aerosol generator based on such histogram feature information may involve forcing and / or requesting battery recharging. Therefore, the aerosol generator may be designed so that the user cannot start a usage session when a predetermined number of usage sessions have been reached before recharging, or when it is determined that no additional usage sessions can be fully provided. In this way, the user experience is improved and waste of aerosol generating items due to incomplete usage sessions can be avoided. Forcing and / or requesting battery recharging may involve putting the aerosol generator into a state where no usage session can be started. In addition, notifications or messages to the user may be presented to inform the user when the aerosol generator's battery needs to be recharged.For this purpose, the aerosol generator may be equipped with light, a display, a loudspeaker, or a vibration device for delivering visual, acoustic, or tactile notifications or messages to the user.

[0053] The method may further include, for example, determining, within a predetermined degree of certainty, the total amount of battery capacity required to operate the aerosol generator between two consecutive recharge events of the aerosol generator's battery, based on histogram feature information. For example, it may be determined that a certain percentage of the capacity of a fully charged battery is required to operate the aerosol generator between two consecutive recharge events. This percentage may relate to the state of charge (SOC) of the battery. Alternatively, the total amount of battery capacity required to operate the aerosol generator between two consecutive recharge events may also be expressed as an absolute value, for example, in mAh. Consecutive recharge events may relate to recharge events that directly follow each other, using only a variable amount of downtime and / or a variable number of usage sessions between recharge events. Thus, from the perspective of a single recharge event, consecutive recharge events may be either the next recharge event or the previous recharge event. For example, the number of usage sessions between two consecutive recharge events may be counted to determine how often a user operates the aerosol generator and provides usage sessions before the device is recharged again. The energy consumption per usage session may then be totaled to determine the total amount of battery capacity required before the device is recharged again. Alternatively, the battery charge state immediately before or when recharging begins may be collected.

[0054] Based on this information, a user may decide, according to their individual user habits, that they do not need the full capacity of the battery between two consecutive recharge events. For example, the number of usage sessions a user needs between two consecutive recharge events may be low enough that the full capacity of the battery is not used. Alternatively, a user's individual user habits may lead to energy-conserving usage sessions that do not use the full capacity of the battery between two consecutive recharge events. In this case, the aerosol generator may be controlled in a way that minimizes battery degradation. For example, it may be provided to control the aerosol generator based on the histogram feature information, including adjusting the operating constraints of the aerosol generator, including limits on the battery and / or power and / or charge management. This may mean that controlling the aerosol generator based on the histogram feature information includes terminating the aerosol generator's battery recharge event when the charge level is below 100%, preferably below 95%, or below 90%, or below 85%, or below 80%. It is known that recharging the battery until it is fully charged accelerates degradation. Similarly, it is known that recharging a battery only to a charge state below its maximum slows down battery degradation. If the user determines through the methods of this disclosure that they only need a fraction of the battery's total capacity or maximum capacity, for example, the current total capacity, this information can be used to slow down battery degradation by avoiding fully charging the battery. Similarly, it is known that completely discharging a battery also accelerates battery degradation. Therefore, the aerosol generator may be controlled so that the battery is not completely discharged during use and at least a residual charge state of the battery, for example, 5%, 10%, 15%, or 20% of the battery's charge state, is preserved. This residual charge state of the battery may also be taken into consideration when determining when to terminate a battery recharge event, so that the battery capacity between the residual charge state and the charge state to which the battery was recharged before the termination of the recharge event corresponds to the total amount of battery capacity required to operate the aerosol generator between two consecutive recharge events.

[0055] The method may further include, for example, determining, within a certain degree of certainty, the amount of time that an aerosol generator battery recharge event lasts from histogram feature information. The histogram may, for example, relate to usage pattern parameter durations of aerosol generator recharge events. In other words, this may determine how long an aerosol generator is typically connected to a power source to recharge its battery, according to the individual user's habits.

[0056] Taking this information into consideration, controlling the aerosol generator based on the histogram feature information may include adjusting the operating constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management. This may mean that controlling the aerosol generator based on the histogram feature information may include limiting the charging rate during a recharge event of the aerosol generator's battery. High charging rates compared to rapid charging are known to be detrimental from the standpoint of battery degradation. Therefore, it may be advantageous to limit the charging rate if it is known that the duration of the recharge event is long enough to recharge the battery to a desired charge state even using a limited charging rate. For example, a user may habitually recharge the aerosol generator overnight, which provides ample time to slowly charge the battery at a limited charging rate. This would result in slower degradation and a longer battery life.

[0057] This is a habit of a specific user, and a user's habits may vary significantly with respect to different locations and / or different times in which the aerosol generator operates, for example, to generate aerosols during a usage session or to recharge the battery. Therefore, the present invention may include collecting at least one usage pattern parameter along with location and / or time information regarding where and / or when the aerosol generator operates. Location information may relate to a geographical location.

[0058] Location information may be determined through the aerosol generator's connection to the local area network via Wi-Fi or WLAN, such as the user's home Wi-Fi, office Wi-Fi, or public Wi-Fi, cellular network information, or information from geolocator tags, through means such as the Global Positioning System (GPS) or different Global Navigation Satellite System (GNSS) systems.

[0059] Time information may also relate to the time and / or calendar date, for example, determined by the internal timepiece and / or calendar of the aerosol generator. All usage pattern parameters described herein may be collected using corresponding location and / or time information. Such information may be collected, for example, for all usage sessions, recharge events, and / or downtimes, for each of the start and / or end of a usage session, a recharge event, and / or downtime.

[0060] Collecting either or both time and location information may allow for a more detailed analysis of data regarding usage pattern parameters. For example, the use of aerosol generators may differ significantly between when a user is at work and when they are at home. Usage may also vary depending on whether it is a workday or a holiday, or between work hours and leisure time. Therefore, methods may involve identifying different usage patterns of aerosol generators in different locations and / or over different periods of time.

[0061] For example, separate histograms and / or bins may be created for the location and / or time period. In this sense, a usage pattern may describe a set of values ​​for a usage pattern parameter collected with location and / or time information that is different from another set of values ​​for the same usage pattern parameter collected with different location and / or time information. For example, if a usage pattern parameter has different values ​​when collected at different locations and / or different times, this usage pattern parameter may be determined to have different usage patterns depending on the location and / or time at which the values ​​of the usage pattern parameter are collected. It may then be provided to take these differences in the values ​​of the usage pattern parameter into account by creating a separate histogram for each usage pattern of the usage pattern parameter. A usage pattern may be considered different if the histogram features extracted from histograms for at least two usage patterns would lead to different control of the aerosol generator based on the histogram features extracted from either of these histograms. For example, histograms relating to different usage patterns may include different or different numbers of local maxima, or any other histogram feature information or histogram features described herein.

[0062] To utilize this additional information provided by location and / or time information, the aerosol generator may be designed to collect current location and / or time information. Current location and / or time information may also relate to the current situation of the aerosol generator and / or user, for example, where and / or at what time the aerosol generator and / or user are at that moment. In this way, information may be available regarding where and / or when the user's current use of the aerosol generator occurs. The method may include extracting histogram feature information from a histogram corresponding to the location and / or time of the current use of the aerosol generator, and controlling the aerosol generator based on the histogram feature information extracted from the histogram. In this way, the control of the aerosol generator may be based on data regarding the location and / or time at which the user actually uses the device. Therefore, for example, differences in use that result in different usage patterns may be taken into consideration when controlling the aerosol generator.

[0063] The values ​​of usage pattern parameters may have an infinite range of numerical values. Therefore, different values ​​of usage pattern parameters may be classified into the same bin of a histogram if they have the same meaning despite being numerically different from one another. Similarly, location and / or time information collected along with usage pattern parameters may, in principle, have an infinite number of numerical values. Therefore, location and / or time information may also be divided into meaningful groups to identify meaningful locations and / or times in which different usage patterns occur, in such a way that each usage pattern results in a different control of the aerosol generator than any other usage pattern. For this reason, the method may optionally include stratifying the collected values ​​of at least one usage pattern parameter into one or more categories according to the location and / or time information. Thus, each category may indicate or represent a location and / or time that stratifies the user's movement and / or life rhythms into meaningful subunits.

[0064] For example, the method may include creating different categories for the values ​​of usage pattern parameters collected or generated below, or for the collected values ​​of at least one usage pattern parameter relating to a session of use of an aerosol generator. - In the user's workplace, - At the user's home, - While the user is on the move, - In the user's entertainment location, - During the user's working time, - During the user's free time, - During the user's holidays, or - During spring, summer, autumn, or winter, A method according to a prior embodiment, comprising creating different categories for the collected values ​​of at least one usage pattern parameter relating to the usage session of the aerosol generator.

[0065] The method may include receiving information from the user that identifies a place and / or time, for example, the current place and / or current time. Thus, the user may provide the aerosol generator with information that the place where the user is at that moment is their workplace or home, or another place the user frequently visits. Similarly, the user may provide the aerosol generator with information that the user works on a particular day and / or at a particular time, or that the user is off on a particular day and / or week. In addition, or otherwise, the method may include the aerosol generator independently determining this information by continuously collecting underlying data and identifying the categories described.

[0066] The categories related to user travel may include both travel away from places the user usually visits, such as international travel, and travel between places the user usually visits, such as travel between their home and their workplace or entertainment venue.

[0067] The method may include generating separate histograms for the values ​​of usage pattern parameters for at least two, more, or all of the categories described above. Controlling an aerosol generator through the method of the present disclosure may take into account different usage patterns or user habits connected to different locations and / or times. For example, a user may recharge an aerosol generator more frequently at work than at home, and therefore may not need to fully recharge the battery when the user is at home, but may need to fully recharge it when the user is at work, according to the principle outlined above. By splitting the available data into different histograms corresponding to location and / or time information, the method of the present disclosure may provide adaptive smart control of an aerosol generator requiring only minimal computing power.

[0068] The histograms used in this method may have any number of bins necessary to represent the underlying data in a meaningful way. Different histograms may have different numbers of bins. The number of bins in each histogram may change as more values ​​of the represented usage pattern parameter are collected over time. For example, the method may include dynamically adjusting the number of bins in the histogram used to classify the values ​​of at least one usage pattern parameter. Different numbers of bins may be required as the number of collected values ​​and / or the distribution of usage pattern parameter values ​​changes over time. The method may also include limiting the number of values ​​for at least one usage pattern parameter or all usage pattern parameters to a certain number of values ​​or values ​​collected during a given period. For example, the number of values ​​for at least one usage pattern parameter may be limited to the last 50, 40, 30, 20, or 10 collected values ​​for at least one usage pattern parameter. Any values ​​exceeding this number with respect to previously collected values ​​may be removed. Similarly, the method may include limiting the collected values ​​of at least one usage pattern parameter to values ​​collected during a predetermined period, for example, the last 12 months, 6 months, 3 months, 1 month, 2 weeks, 1 week, or 1 day. Any values ​​collected before this period may be removed. In this way, the data that can be relied upon to control the aerosol generator may always be up-to-date. At the same time, the computational power required for the method according to this disclosure is further reduced. Therefore, since the data represented by each histogram may change over time, how this data may be organized within the histogram may also change by dynamically adjusting the number of bins.

[0069] For example, it may be determined that the number of histogram bins is too small to extract meaningful histogram feature information. In other words, the bins available in the histogram may provide too low a data resolution to extract meaningful histogram feature information from the histogram. This is typically the case when an excessive number of values ​​for a usage pattern parameter are classified into a single bin of the histogram. Therefore, the method may optionally include increasing the number of histogram bins used to classify the values ​​of at least one usage pattern parameter when the proportion of values ​​of at least one usage pattern parameter in a single bin exceeds a predetermined threshold. The predetermined threshold may be, for example, 50%, 60%, 70%, 80%, or 90% of all values ​​of at least one usage pattern parameter in the histogram. The number of histogram bins may also be increased, for example, by dividing a range of values ​​to be classified into a bin, preferably a bin with most values ​​classified into it, into two or more ranges or sub-ranges, each of which is represented by a new bin and reclassifies the values ​​of at least one usage pattern parameter accordingly.

[0070] In addition, or alternatively, the method may include increasing the number of bins in the histogram used to classify the values ​​of at least one usage pattern parameter when the collected values ​​of at least one usage pattern parameter do not fit into any of the available bins. In this case, the new bins may be created to represent a range of numerical values ​​to which the collected values ​​of at least one usage pattern parameter fit. The new bins may be added to the histogram so that subsequently collected values ​​may be classified into these bins in the future.

[0071] The method may also include reducing the number of histogram bins used to classify the values ​​of at least one usage pattern parameter when the proportion of the values ​​of the usage pattern parameter in all bins falls below a predetermined threshold. The predetermined threshold may be, for example, 10%, 20%, 30%, or 40% of all values ​​of at least one usage pattern parameter in the histogram. In this case, adjacent bins may be joined together or merged so that a new bin representing the range of numerical values ​​of both bins may be created together. Accordingly, the height of the new bin may be determined by summing the heights of the merged bins. In addition, or alternatively, bins that do not have any values ​​classified into them may be deleted. Such empty bins may occur, for example, as a result of older values ​​of the usage pattern parameter being deleted.

[0072] Aside from the methods for extracting histogram features outlined above, other methods may be employed for this purpose. For example, the method may include using an (artificial) intelligence engine or network or machine learning in extracting histogram features from a histogram and / or controlling an aerosol generator based on such histogram features. For example, a convolutional neural network (CNN), random forest, decision forest, decision tree, etc., may be employed in extracting histogram features and / or controlling an aerosol generator. These engines or networks may be pre-trained on large datasets to enable accurate decision-making based on the data available for any one of the aerosol generators. Organizing this data into histograms may improve the performance of the (artificial) intelligence engine or intelligence network or machine learning.

[0073] In another aspect of this disclosure, an aerosol generator is provided configured to carry out the steps of the method according to this disclosure, for example, at least a subset or all of the steps. All the features, effects, and advantages described in this method are also valid for aerosol generators and apply equally to aerosol generators, and vice versa.

[0074] The aerosol generator may include a battery for storing electrical energy and a processing circuit or control circuit having one or more processors configured to carry out steps of a method as disclosed herein, for example, at least a subset or all of the steps.

[0075] In another aspect of the present disclosure, an aerosol generating system is provided, comprising a control arrangement, the control arrangement being configured to perform steps of the method according to the present disclosure, e.g., at least a subset or all of the steps. The control arrangement may comprise, for example, a processing circuit having one or more processors. In addition, or otherwise, the aerosol generating system may comprise an aerosol generator and a companion device communicably connected to the aerosol generator, the companion device being configured to perform steps of the method according to the present disclosure, e.g., at least a subset or all of the steps. All the features, effects, and advantages described in the present method are also valid for aerosol generating systems and equally applicable to aerosol generators, and vice versa.

[0076] The companion device may be, for example, a smartphone, tablet computer, personal computer, computing device, server, or device configured to charge an aerosol generator. It may be advantageous to implement the method according to this disclosure on the companion device, particularly in cases where the companion device has more computing power than the aerosol generator. Furthermore, in cases where a user owns and / or operates two or more aerosol generators, all of these may be communicably linked to the companion device so that the companion device can collect data from multiple aerosol generators, such as values ​​of usage pattern parameters. In this way, all control of the aerosol generator may be improved, regardless of when or where the user uses which aerosol generator.

[0077] In another aspect of this disclosure, a computer program or software or computer executable code is provided that, when executed on a processor of an aerosol generator and / or companion device, performs the steps of the method according to this disclosure, for example, at least a subset or all of the steps. All the features, effects, and advantages described in this method are also valid and equally applicable to computer programs or software or computer executable code, and vice versa.

[0078] In another aspect of this disclosure, a computer-readable medium or software or computer-executable code having a computer program stored thereon is provided, which, when executed on a processor of an aerosol generator and / or companion device, performs the steps of the method according to this disclosure, e.g., at least a subset or all of the steps. All the features, effects, and advantages described in this method are also valid for computer-readable medium and apply equally to computer-readable medium, and vice versa.

[0079] The present invention is defined in the claims. However, a non-exclusive list of non-limiting embodiments is provided below. One or more features of these embodiments may be combined with one or more features of any of the features described above, for example, one or more features of other embodiments, forms, or aspects described herein.

[0080] Example 1. A computer-implemented method for controlling an aerosol generator, To collect multiple values ​​of at least one usage pattern parameter related to the use of an aerosol generator, By classifying each collected value of the pattern parameter used into histogram bins, a histogram is created. Extracting histogram feature information from a histogram, A method comprising controlling an aerosol generator using operational constraints based on histogram feature information.

[0081] Example 2. At least one usage pattern parameter is the following parameter: - Energy consumption per session, - Preferably, the number of usage sessions in which the aerosol generator operated to generate aerosols per predetermined time interval, - Duration of session used, - A rest period between consecutive usage sessions, preferably such that the usage pattern parameter value for the rest period between consecutive usage sessions changes only for rest periods between subsequent usage sessions of 0 to 40 minutes. - In particular, the frequency at which at least two usage sessions occur consecutively without the need to recharge the aerosol generator in between, - Ambient temperature during the session, - Ambient air pressure during the session, - Ambient humidity during the session, - Ambient temperature during recharging of the aerosol generator's battery, - Battery temperature of the aerosol generator during the session, - The temperature of the heating element or heater device of the aerosol generator during a predefined period prior to the start of the session. - Number of puffs per session, - Smoke absorption volume, - Frequency of smoking, - Smoking rhythm, - Start time of pause mode in aerosol generator, - End time of pause mode in aerosol generator, - Duration of pause mode in aerosol generator, - Duration of the aerosol generator recharge event, - The downtime after recharging the aerosol generator, -Hibernation time with battery charge below 10%, -Hibernation time with battery charge exceeding 90%, - The density of the aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols. - The weight of the aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols, - The type of aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols, - Humidity of aerosol generating substrate or aerosol generating article used in aerosol generating device, - A method according to Example 1, selected from a temperature profile selected by the user.

[0082] Example 3. A method according to any of the preceding embodiments, comprising: collecting two or more usage pattern parameters; creating a histogram for each of the usage pattern parameters; and controlling an aerosol generator based on histogram feature information extracted from the multiple histograms.

[0083] Example 4. At least one histogram feature extracted from the histogram is weighted differently from the others, and / or A method according to a previous example, in which histogram feature information extracted from different histograms is weighted differently.

[0084] Example 5. Extracted histogram feature information: - One or more local maximums in the histogram, - Identity of one or more bins in the histogram corresponding to one or more local maxima in the histogram, - The height of one or more bins of the histogram corresponding to one or more local maximums in the histogram, preferably the height of a bin corresponding to or proportional to the number of values ​​of the usage pattern parameter classified into that bin. - The sum of the heights of two or more bins in a histogram, preferably such that the bin height corresponds to or is proportional to the number of values ​​of the usage pattern parameter classified into this bin. - The average of the values ​​of the usage pattern parameter classified into one or more bins in the histogram. - The median value of the usage pattern parameter that is classified into one or more bins in the histogram. - The maximum value of the usage pattern parameter that is classified into one or more bins in the histogram. - A method according to any of the prior embodiments, which includes at least one of the minimum values ​​of the usage pattern parameter that are classified into one or more bins of the histogram.

[0085] Example 6. From the histogram feature information, - The number of usage sessions that can be provided to the user for generating aerosols by the maximum capacity of the aerosol generator's battery, preferably the number of usage sessions where the maximum capacity of the battery is the nominal maximum capacity or current maximum capacity of the aerosol generator's battery. A method according to any of the prior embodiments, further comprising determining at least one of the following: - whether an additional usage session can be provided, taking into account the current charge state of the battery of the aerosol generator.

[0086] Example 7. Preferably, the method further includes a step of changing the operating constraints of the aerosol generator, including limitations on battery and / or power consumption management based on histogram feature information, and / or controlling the aerosol generator based on histogram feature information. - Limit the total number of usage sessions provided to the user for aerosol generation before the battery of the aerosol generator is recharged to the number of usage sessions that can be provided with a certain degree of certainty. - Before recharging the aerosol generator's battery, enable or prevent additional usage sessions, and / or A method according to a prior embodiment, further comprising at least one of forcing and / or requesting a recharge of a battery.

[0087] Example 8. A method according to any of the prior embodiments, further comprising determining the total amount of battery capacity required to operate the aerosol generator between two consecutive recharge events of the aerosol generator's battery, based on histogram feature information.

[0088] Example 9. A method according to a prior embodiment, in which controlling the aerosol generator based on histogram feature information includes adjusting the operating constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management, and / or preferably terminating the battery recharge event of the aerosol generator at a charge state of less than 100%, preferably less than 95%, or less than 90%, or less than 85%, or less than 80%.

[0089] Example 10. A method according to any of the prior embodiments, further comprising determining the amount of time that a battery recharge event of an aerosol generator persists from histogram feature information.

[0090] Example 11. A method according to a prior embodiment, wherein controlling the aerosol generator based on histogram feature information includes adjusting the operating constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management, and / or preferably limiting the charging rate during a battery recharge event of the aerosol generator.

[0091] Example 12. A method according to any of the prior embodiments, comprising collecting at least one usage pattern parameter along with location and / or time information regarding where and / or when the aerosol generator is operating.

[0092] Example 13. A method according to a preceding example, comprising identifying different usage patterns of an aerosol generator at different locations and / or over different time periods, and preferably creating separate histograms and / or bins for the locations and / or time periods.

[0093] Example 14. A method according to a prior embodiment, comprising extracting histogram feature information from a histogram corresponding to the current location and / or time of use of an aerosol generator, and controlling the aerosol generator based on the histogram feature information extracted from the histogram.

[0094] Example 15. A method according to any of Examples 12-14, comprising hierarchizing the collected values ​​of at least one usage pattern parameter into one or more categories according to location information and / or time information.

[0095] Example 16. The following, - In the user's workplace, - At the user's home, - While the user is on the move, - In the user's entertainment location, - During the user's working time, - During the user's free time, - During the user's holidays, or - During spring, summer, autumn, or winter, A method according to a prior embodiment, comprising creating different categories for the collected values ​​of at least one usage pattern parameter relating to the usage session of the aerosol generator.

[0096] Example 17. A method according to any of the preceding examples, comprising dynamically adjusting the number of bins in a histogram used to classify the values ​​of at least one usage pattern parameter.

[0097] Example 18. A method according to any of the preceding embodiments, comprising increasing the number of bins in a histogram used to classify the values ​​of at least one usage pattern parameter when the proportion of values ​​of at least one usage pattern parameter in one bin exceeds a predetermined threshold.

[0098] Example 19. A method according to any of the preceding embodiments, comprising increasing the number of bins in a histogram used to classify the value of at least one usage pattern parameter when the collected value of at least one usage pattern parameter does not fit into any available bin.

[0099] Example 20. A method according to any of the preceding embodiments, comprising reducing the number of bins in a histogram used to classify the values ​​of at least one usage pattern parameter when the proportion of the values ​​of at least one usage pattern parameter in all bins falls below a predetermined threshold.

[0100] Example 21. A method according to any of the prior embodiments, wherein an intelligence engine, network, or machine learning is used to extract histogram feature information from a histogram and / or control an aerosol generator based on said histogram feature information.

[0101] Example 22. An aerosol generator configured to carry out the steps of the method according to any one of the preceding examples.

[0102] Example 23. A battery for storing electrical energy, An aerosol generator according to Example 22, comprising a processing circuit having one or more processors configured to carry out the steps of the method according to any one of Examples 1 to 21.

[0103] Example 24. An aerosol generating system comprising an aerosol generator and a companion device that can be communicatively connected to the aerosol generator, wherein the companion device is configured to carry out the steps of the method according to any one of Examples 1 to 21.

[0104] Example 25. An aerosol generating system according to Example 24, wherein the companion device may be configured to charge a smartphone, tablet computer, personal computer, server, or aerosol generator.

[0105] Example 26. A computer program that performs the steps of any one of Examples 1 to 21 when executed on the processor of an aerosol generator and / or companion device.

[0106] Example 27. A computer-readable medium storing a computer program thereon, which performs the steps of any one of Examples 1 to 21 when executed on the processor of an aerosol generator and / or companion device.

[0107] Example 28. Collect multiple values ​​of at least one usage pattern parameter related to the use of an aerosol generator. A histogram is created by classifying each collected value of the pattern parameters used into histogram bins. Extract histogram feature information from the histogram, and An aerosol generation system comprising a control configuration that controls the aerosol generator using operational constraints based on histogram feature information.

[0108] Example 29. At least one usage pattern parameter is the following parameter: - Energy consumption per session, - Preferably, the number of usage sessions in which the aerosol generator operated to generate aerosols per predetermined time interval, - Duration of session used, - A rest period between consecutive usage sessions, preferably such that the usage pattern parameter value for the rest period between consecutive usage sessions changes only for rest periods between subsequent usage sessions of 0 to 40 minutes. - In particular, the frequency at which at least two usage sessions occur consecutively without the need to recharge the aerosol generator in between, - Ambient temperature during the session, - Ambient air pressure during the session, - Ambient humidity during the session, - Ambient temperature during recharging of the aerosol generator's battery, - Battery temperature of the aerosol generator during the session, - The temperature of the heating element or heater device of the aerosol generator during a predefined period prior to the start of the session. - Number of puffs per session, - Smoke absorption volume, - Frequency of smoking, - Smoking rhythm, - Start time of pause mode in aerosol generator, - End time of pause mode in aerosol generator, - Duration of pause mode in aerosol generator, - Duration of the aerosol generator recharge event, - The downtime after recharging the aerosol generator, -Hibernation time with battery charge below 10%, -Hibernation time with battery charge exceeding 90%, - The density of the aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols. - The weight of the aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols, - The type of aerosol generating substrate or aerosol generating article used in an aerosol generating device to generate aerosols, - Humidity of aerosol generating substrate or aerosol generating article used in aerosol generating device, - Temperature profile selected by the user, Aerosol generation system according to a prior embodiment, selected from the above.

[0109] Example 30. An aerosol generation system according to any of Examples 28 to 29, wherein two or more usage pattern parameters are collected, a histogram is created for each of the usage pattern parameters, and the aerosol generator is controlled based on histogram feature information extracted from the multiple histograms.

[0110] Example 31. At least one histogram feature extracted from the histogram is weighted differently from the others, and / or An aerosol generation system according to a previous example, in which histogram feature information extracted from different histograms is weighted differently.

[0111] Example 32. The extracted histogram feature information is - One or more local maximums in the histogram, - Identity of one or more bins in the histogram corresponding to one or more local maxima in the histogram, - The height of one or more bins of the histogram corresponding to one or more local maximums in the histogram, preferably the height of a bin corresponding to or proportional to the number of values ​​of the usage pattern parameter classified into that bin. - The sum of the heights of two or more bins in a histogram, preferably such that the bin height corresponds to or is proportional to the number of values ​​of the usage pattern parameter classified into this bin. - The average of the values ​​of the usage pattern parameter classified into one or more bins in the histogram. - The median value of the usage pattern parameter that is classified into one or more bins in the histogram. - The maximum value of the usage pattern parameter that is classified into one or more bins in the histogram. - An aerosol generation system according to any of Examples 28 to 31, comprising at least one of the minimum values ​​of the usage pattern parameter that are classified into one or more bins in the histogram.

[0112] Example 33. At least one of the following is histogram feature information: - The number of usage sessions that can be provided to the user for generating aerosols by the maximum capacity of the aerosol generator's battery, preferably the number of usage sessions where the maximum capacity of the battery is the nominal maximum capacity or current maximum capacity of the aerosol generator's battery. - An aerosol generating system according to any of Examples 28-32, determined by whether an additional usage session can be provided, taking into account the current charge state of the aerosol generating device's battery.

[0113] Example 34. Preferably, the method further includes a step of modifying the operating constraints of an aerosol generator, including limitations on battery and / or power consumption management based on histogram feature information, and / or controlling the aerosol generator based on said histogram feature information. - Limit the total number of usage sessions provided to the user for aerosol generation before the battery of the aerosol generator is recharged to the number of usage sessions that can be provided with a certain degree of certainty. - Before recharging the aerosol generator's battery, enable or prevent additional usage sessions, and / or A method according to a prior embodiment, further comprising at least one of forcing and / or requesting a recharge of a battery.

[0114] Example 35. An aerosol generating system according to any of Examples 28-34, in which the total amount of battery capacity required to operate the aerosol generating device between two consecutive battery recharge events is determined from histogram feature information.

[0115] Example 36. An aerosol generating system according to a previous embodiment, wherein controlling the aerosol generator based on histogram feature information includes adjusting the operating constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management, and / or preferably terminating a battery recharge event of the aerosol generator at a charge state of less than 100%, preferably less than 95%, or less than 90%, or less than 85%, or less than 80%.

[0116] Example 37. An aerosol generating system according to any of Examples 28-36, further comprising determining the amount of time that a battery recharge event of the aerosol generating device persists from histogram feature information.

[0117] Example 38. An aerosol generating system according to a prior embodiment, wherein controlling the aerosol generator based on histogram feature information includes adjusting the operating constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management, and / or preferably limiting the charging rate during a battery recharge event of the aerosol generator.

[0118] Example 39. An aerosol generating system according to any of Examples 28-38, wherein at least one usage pattern parameter is collected along with location and / or time information regarding where and / or when the aerosol generating device operates.

[0119] Example 40. An aerosol generating system according to a previous example, wherein different usage patterns of the aerosol generating device are identified at different locations and / or over different time periods, and preferably, separate histograms and / or bins are produced for those locations and / or time periods.

[0120] Example 41. An aerosol generating system according to a previous embodiment, wherein histogram feature information is extracted from a histogram corresponding to the current location and / or time of use of the aerosol generating device, and the aerosol generating device is controlled based on the histogram feature information extracted from the histogram.

[0121] Example 42. An aerosol generating system according to any of Examples 28-41, wherein location information and / or time information are used to stratify the collected values ​​of at least one usage pattern parameter into one or more categories.

[0122] Example 43. The following, - In the user's workplace, - At the user's home, - While the user is on the move, - In the user's entertainment location, - During the user's working time, - During the user's free time, - During the user's holidays, or - During spring, summer, autumn, or winter, A method according to a prior embodiment, comprising creating different categories for the collected values ​​of at least one usage pattern parameter relating to the usage session of the aerosol generator.

[0123] Example 44. An aerosol generation system according to any of Examples 28-43, wherein the number of histogram bins used to classify the values ​​of at least one usage pattern parameter is dynamically adjusted.

[0124] Example 45. An aerosol generation system according to any of Examples 28 to 44, wherein the number of bins in a histogram used to classify the values ​​of at least one usage pattern parameter increases when the proportion of values ​​of at least one usage pattern parameter in one bin exceeds a predetermined threshold.

[0125] Example 46. An aerosol generation system according to any of Examples 28-45, wherein the number of histogram bins used to classify the values ​​of at least one usage pattern parameter is increased when the collected values ​​of at least one usage pattern parameter do not fit into any available bin.

[0126] Example 47. An aerosol generation system according to any of Examples 28 to 46, wherein the number of bins in a histogram used to classify the values ​​of at least one usage pattern parameter decreases when the proportion of the values ​​of at least one usage pattern parameter in all bins falls below a predetermined threshold.

[0127] Example 48. An aerosol generating system according to any of Examples 28 to 47, wherein an intelligence engine, network, or machine learning is used to extract histogram feature information from a histogram and / or to control an aerosol generating device based on said histogram feature information.

[0128] Example 49. An aerosol generating system according to any of Examples 28 to 48, comprising an aerosol generator and a companion device, wherein the control arrangement is located on the aerosol generator and / or the companion device.

[0129] Here, we will further describe the examples with reference to the figures. [Brief explanation of the drawing]

[0130] [Figure 1] Figure 1 shows an aerosol generation system comprising an aerosol generator and a companion device. [Figure 2] Figure 2 shows a histogram of energy consumption for usage pattern parameters per session. [Figure 3] Figure 3 shows a histogram of the number of usage pattern parameters for the usage sessions in which the aerosol generator operated to generate aerosols per day. [Figure 4] Figure 4 shows a flowchart of the method. [Modes for carrying out the invention]

[0131] These diagrams are merely schematic and do not represent actual dimensions.

[0132] Figure 1 shows an aerosol generating system 1 for generating aerosols, for example, for user consumption in one or more usage sessions. System 1 may comprise an aerosol generating device 2 for generating aerosols, and a companion device 3 for at least partially receiving the aerosol generating device 2. The companion device 3 may be a charging device for charging the aerosol generating device 2 and / or its energy storage or battery.

[0133] The aerosol generator 2 may include an insertion opening 4 for at least partially inserting the aerosol generating article 17. The aerosol generating article 17 may include a cartridge containing an aerosol-forming substrate, such as a tobacco-containing substrate, and / or a liquid, such as a liquid that can be aerosolized for inhalation.

[0134] The aerosol generator 2 may further include a processing circuit 5 or control circuit 5 having one or more processors 6. In order to generate aerosols during use or consumption of the aerosol generating article 17, the aerosol generator 2 may include at least one heating element 7 or heater device to heat at least a portion of the aerosol generating article 17. The processing circuit 5 may be configured to control the operation, starting, and / or stopping of at least one heating element 7. The processing circuit 5 may be further configured to carry out the steps of the method described herein.

[0135] To power at least one heating element 7 using electricity, the aerosol generator 2 may further include at least one energy storage, for example in the form of a battery 15, for storing electrical energy or power. The aerosol generator 2 may further include at least one electrical connector 12 for connecting to at least one corresponding electrical connector 13 of the companion device 3. For example, when the aerosol generator 2 is at least partially inserted into the opening 14 of the companion device 3, one or more electrical connectors 12 of the aerosol generator 2 may be connected to one or more electrical connectors 13 of the companion device 3 to charge at least one battery 15 of the aerosol generator 2.

[0136] The aerosol generator 2 may further include a user interface component having an input element in the form of, for example, a push button 8. The push button 8 may be used as a power button to start or stop the heating element 7 for aerosol generation, thereby starting or stopping the aerosol generator 2. Upon starting the aerosol generator 2, the heating element 7 may be started, and heat may be applied to at least a portion of the aerosol generating article 17, thereby generating aerosols for consumption by the user, for example, during a usage session.

[0137] The aerosol generator 2 may further include a communication arrangement 9 or communication circuit 9 having one or more communication interfaces 10 to enable communication between the aerosol generator 2 and the companion device 3, for example via an internet connection, wireless LAN connection, WiFi connection, Bluetooth connection, mobile data connection (e.g., 3G / 4G / 5G connection, but not limited thereto), edge connection, LTE connection, BUS connection, wireless connection, wired connection, optical data connection (e.g., IrDa, but not limited thereto), radio connection, near-field connection, and / or IoT connection.

[0138] The aerosol generator 2 may further include a data storage 11 for storing information or data such as collected usage pattern parameter values, battery degradation data, and / or one or more mathematical functions or formulas, and for storing computer instructions that can be executed by the processing circuit 5.

[0139] As described in detail above and below in this specification, the aerosol generator 2 is configured to collect, gather, and / or store values ​​of at least one usage pattern parameter related to the use of the aerosol generator 2. One or more sensors 16 may be disposed on the aerosol generator 2 to collect data such as, for example, values ​​of the usage pattern parameter and / or battery capacity data and / or location information and / or time information.

[0140] Figure 2 shows an example histogram of usage pattern parameter energy consumption per usage session. The histogram may contain a total of five bins. Energy consumption per usage session may be measured by the total capacity of the battery used per usage session. The numerical range of the bins may differ for each bin. In the embodiment shown in Figure 2, the histogram may be designed to determine how many usage sessions, within the range of one to five usage sessions, can be provided to the user by the energy stored in battery 15 with a current maximum capacity of a model value of 235 mAh. The numerical range of the bins may be calculated by dividing the current maximum capacity of battery 15 by the number of usage sessions that can theoretically be provided. The resulting number may represent the upper end of the numerical range for each bin, while the lower end of the numerical range for each bin may be either 0 or determined by the upper end of the numerical range of the adjacent bin.

[0141] For example, dividing the current maximum capacity of battery 15 (235mAh) by the maximum number of possible usage sessions (five) equals 47mAh. This may be the upper limit of the numerical range of the first bin, with a lower limit of 0mAh. Dividing the current maximum capacity of battery 15 (235mAh) by the next four possible usage sessions equals 59mAh. This may be the upper limit of the numerical range of the second bin, with a lower limit starting where the upper limit of the previous bin ends. Dividing the current maximum capacity of battery 15 (235mAh) by the next three possible usage sessions equals 78mAh. This may be the upper limit of the numerical range of the third bin, with a lower limit starting where the upper limit of the previous bin ends. Dividing the current maximum capacity of battery 15 (235mAh) by the next two possible usage sessions equals 117mAh. This may be the upper limit of the numerical range of the fourth bin, with a lower limit starting where the upper limit of the previous bin ends. The current maximum capacity of a 235mAh battery 15, divided by the next possible number of usage sessions, is equal to 235mAh. This may be the upper end of the numerical range of the fifth bin, and the lower end may begin where the upper end of the previous bin ends. As a result, the first bin may represent the numerical range of 0-47mAh, the second bin may represent the numerical range of 48-59mAh, the third bin may represent the numerical range of 60-78mAh, the fourth bin may represent the numerical range of 79-117mAh, and the fifth bin may represent the numerical range of 118-235mAh.

[0142] During the operation of the aerosol generator 2, values ​​for energy consumption per usage session may be collected and classified into bins in a histogram. If the energy consumption of all usage sessions of the aerosol generator 2 is classified into the first bin, this means that very little energy is used per usage session, and all five usage sessions can be provided by a single full charge of battery 15. Similarly, if the energy consumption of all usage sessions of the aerosol generator 2 is classified into the second bin, this means that only four usage sessions may be provided by a single full charge of battery 15, etc. In reality, the energy consumption per usage session may not be this homogeneous. The histogram in Figure 2 shows an exemplary, but more realistic, distribution of the values ​​of the usage pattern parameter. Specifically, the number of values ​​n classified into the first bin is 6, the number of values ​​n classified into the second bin is 3, the number of values ​​n classified into the third bin is 8, the number of values ​​n classified into the fourth bin is 3, and the number of values ​​n classified into the fifth bin is 0. Histograms may only show the most recent 20 values ​​collected.

[0143] The histogram shown in Figure 2 may be used to calculate how many usage sessions can be provided to the user using a single full charge of battery 15 within a predetermined degree of certainty. The histogram feature information extracted from the histogram for this determination is represented by the height of the bins and the sum of these heights. In this case, the predetermined degree of certainty may be represented as the proportion of n values ​​that are classified into all of the histogram bins. For example, if the number of n values ​​classified into the first bin represents a proportion of all values ​​in all of the histogram bins that is greater than or equal to the proportion required for the predetermined degree of certainty, then a total of five usage sessions can be provided to the user. If this is not the case, further bins must be considered. For example, if the combined sum of n values ​​classified into the first and second bins represents a proportion of all values ​​in all of the histogram bins that is greater than or equal to the proportion required for the predetermined degree of certainty, then a total of five usage sessions can be provided to the user. If this is also not the case, another bin may be considered. For example, the heights of the first, second, and third bins may be totaled as described above and checked against a predetermined degree of certainty to determine if three usage sessions can be provided. Similarly, the heights of the first, second, third, and fourth bins may be totaled as described above and checked against a predetermined degree of certainty to determine if two usage sessions can be provided. If this total does not satisfy the predetermined degree of certainty, only one usage session may be provided.

[0144] In the embodiment shown in Figure 2, the first, second, and third bins together contain or represent 17 of the 20 most recent use sessions, where 20 is an exemplary non-limiting value. This means that within a certainty of 17 / 20 * 100% = 85%, three use sessions can be provided to the user using a single full charge of battery 15. Thus, the method may include limiting the total number of use sessions provided to the user to generate aerosols before recharging of battery 15 of the aerosol generator 2 to three use sessions. This may also be used to determine whether to allow further use sessions depending on the number of use sessions that have already occurred since the last recharge event.

[0145] If a user has just begun using the aerosol generator 2, there may not be enough data available to make meaningful decisions based on the user's usage pattern parameters. In this case, the aerosol generator 2 may be provided to be controlled in a predetermined manner until sufficient data has been collected.

[0146] Figure 3 shows an example of a histogram relating to the number of usage pattern parameters for usage sessions in which the aerosol generator 2 operated to generate aerosols per day. The histogram may include a total of six bins, each representing one more usage session per day than the previous one. In the exemplary example of Figure 3, one value of the usage pattern parameter is classified into the first bin, representing one usage session per day; three values ​​of the usage pattern parameter are classified into the second bin, representing two usage sessions per day; sixteen values ​​of the usage pattern parameter are classified into the third bin, representing three usage sessions per day; two values ​​of the usage pattern parameter are classified into the fourth bin, representing four usage sessions per day; and zero usage sessions are classified into the fifth and sixth bins, respectively, representing five and six usage sessions per day.

[0147] From the histogram shown in Figure 3, it may be determined, within a certain degree of certainty, how many usage sessions the user will need per day. The histogram feature information extracted from the histogram for this determination may, in this case, also be represented by the height of the bins and the sum of these heights. For example, the first, second, and third bins together may contain, or represent, the values ​​of 20 out of a total of 22 collected usage pattern parameters. Thus, it may be determined, within a degree of certainty of 20 / 22 * 100% = 90.9%, that the user will need a maximum of three usage sessions per day. If the user recharges the aerosol generator 2 once a day, it may also be determined, within the same degree of certainty, that the user will need three usage sessions between two consecutive recharge events of the aerosol generator 2.

[0148] As an example, both histograms in Figures 2 and 3 can be assumed to pertain to the same user. As explained above, from the histogram in Figure 2, it may be determined with an 85% degree of certainty that the user requires a maximum battery capacity of 78mAh per usage session. This means that for three usage sessions, the user will likely require a recharge event in between, according to the histogram in Figure 3, and the user will require a total battery capacity of 3 × 78mAh = 234mAh. If the current maximum battery capacity of battery 15 is 300mAh, this required capacity can be provided when battery 15 is charged to 234 / 300 * 100% = 78%. Therefore, the aerosol generator 2 may be controlled in such a way that battery 15 is not recharged above, for example, 80%, 85%, or 90%. This battery management may result in lower battery degradation over time, while still providing the user with the desired number of usage sessions within a high probability.

[0149] Figure 4 shows a flowchart of Method 18 of the present disclosure. Method 18 may begin in step 19, in which multiple values ​​of at least one usage pattern parameter related to the use of the aerosol generator 2 may be collected, for example, for a given number of usage sessions. In step 20, a histogram may be produced by classifying each collected value of the usage pattern parameter into histogram bins. This may result in a histogram such as those shown, for example, in Figures 2 and 3. In step 21, histogram feature information may be extracted from the histogram. Histogram feature information may relate, for example, to the heights of different bins in the histogram, or to the sum of the heights of adjacent bins. Finally, Method 18 may include step 22, in which the aerosol generator 2 may be controlled based on the histogram feature information. Specifically, Method 18 may enable the adaptation of operating constraints of the aerosol generator 2 according to the histogram feature information. Method 18 of the present disclosure may enable the control of the aerosol generator 2 taking into account the habits of individual users. Battery management and / or the availability or duration of usage sessions may be adapted in this manner. At the same time, method 18 requires only minimal memory or storage space and computing power, and is therefore suitable for implementation on the aerosol generator 2.

[0150] For the purposes of this specification and the appended claims, unless otherwise indicated, all numbers representing amounts, quantities, percentages, etc., are understood to be modified in all cases by the term “approximately.” Furthermore, all ranges include the disclosed maximum and minimum points and any intermediate ranges within them, which may or may not be specifically listed herein. Thus, in this context, the number A is understood as A ± 10%. In this context, the number A may be considered to include a number that falls within the general standard error of the measurement of the characteristic that the number A modifies. In some cases used in the appended claims, the number A may deviate by the percentages listed above, provided that the amount of deviation of A does not substantially affect the basic and novel characteristics of the claimed invention. Furthermore, all ranges include the disclosed maximum and minimum points and any intermediate ranges within them, which may or may not be specifically listed herein.

Claims

1. A computer-implemented method for controlling an aerosol generator, Collecting multiple values ​​of at least one usage pattern parameter related to the use of the aerosol generator, A histogram is created by classifying each collected value of the aforementioned usage pattern parameter into the bins of the histogram. Extracting histogram feature information from the aforementioned histogram, A method comprising controlling the aerosol generator using operational constraints based on the histogram feature information.

2. The aforementioned at least one usage pattern parameter is the following parameter: - Energy consumption per session, - Preferably, the number of usage sessions in which the aerosol generator operated to generate aerosols per predetermined time interval, - Duration of session used, - A rest period between consecutive usage sessions, preferably such that the usage pattern parameter value with respect to the rest period between consecutive usage sessions changes only for rest periods between subsequent usage sessions of 0 to 40 minutes. - In particular, at a frequency in which at least two usage sessions are performed consecutively without recharging the aerosol generator in between, - Ambient temperature during the session, - Ambient air pressure during the session, - Ambient humidity during the session, - Ambient temperature during recharging of the battery of the aerosol generator, - The battery temperature of the aerosol generator during the usage session, - The temperature of the heating element or heater device of the aerosol generator during a predefined period prior to the start of the usage session. - Number of puffs per session, - Smoke absorption volume, - Frequency of smoking, - Smoking rhythm, - Start time of pause mode in aerosol generator, - The end time of the pause mode in the aerosol generator, - Duration of the pause mode in the aerosol generator, - Duration of the recharge event of the aerosol generator, - The downtime after the aerosol generator has been recharged, -Hibernation time with battery charge below 10%, -Hibernation time with battery charge exceeding 90%, - The density of the aerosol generating substrate or aerosol generating article used in the aerosol generating device to generate aerosols, - The weight of the aerosol generating substrate or aerosol generating article used in the aerosol generating device to generate aerosols, - The type of aerosol generating substrate or aerosol generating article used in the aerosol generating apparatus to generate aerosols, - Humidity of the aerosol generating substrate or aerosol generating article used in the aerosol generating device, - The method according to claim 1, selected from a temperature profile selected by the user.

3. The aforementioned at least one usage pattern parameter is the following parameter: - Energy consumption per session, - Preferably, the method according to claim 1, selected from the number of usage sessions in which the aerosol generator operated to generate aerosols per predetermined time interval.

4. The method according to any one of claims 1 to 3, comprising: collecting two or more usage pattern parameters; creating a histogram for each of the usage pattern parameters; and controlling the aerosol generator based on histogram feature information extracted from a plurality of the histograms.

5. At least one histogram feature extracted from the histogram is weighted differently from the others, and / or The method according to claim 4, wherein histogram feature information extracted from different histograms is weighted differently.

6. The extracted histogram feature information is as follows: - One or more local maximums in the histogram, - Identity of one or more bins in the histogram corresponding to one or more local maximums in the histogram, - The height of one or more bins of the histogram corresponding to one or more local maximums of the histogram, preferably the height of a bin corresponding to or proportional to the number of values ​​of the usage pattern parameter classified into that bin, - The sum of the heights of two or more bins in the histogram, preferably such that the height of the bin corresponds to or is proportional to the number of values ​​of the usage pattern parameter classified into that bin. - The average of the values ​​of the usage pattern parameters classified into one or more bins of the histogram, - The median value of the usage pattern parameter that is classified into one or more bins of the histogram, - The maximum value of the usage pattern parameter that is classified into one or more bins of the histogram, - The method according to any one of claims 1 to 5, comprising at least one of the minimum values ​​of the usage pattern parameters that are classified into one or more bins of the histogram.

7. The following from the aforementioned histogram feature information: - The number of usage sessions that can be provided to the user for generating aerosols by the maximum capacity of the battery of the aerosol generator, preferably the number of usage sessions such that the maximum capacity of the battery is the nominal maximum capacity or current maximum capacity of the battery of the aerosol generator. -Further including determining at least one of the following, taking into account the current charge state of the battery of the aerosol generator, whether an additional usage session can be provided: Preferably, the method further includes a step of modifying the operating constraints of the aerosol generator, including limitations on battery and / or power consumption management based on the histogram feature information, and / or controlling the aerosol generator based on the histogram feature information, as follows: - Limiting the total number of usage sessions provided to the user for generating aerosols before the battery of the aerosol generator is recharged to a number of usage sessions that can be provided within a predetermined degree of certainty. - Allowing or preventing additional usage sessions before recharging the battery of the aerosol generator, and / or The method according to any one of claims 1 to 6, further comprising at least one of forcing and / or requesting the recharging of the battery.

8. The method further includes determining, from the histogram feature information, the total amount of battery capacity required to operate the aerosol generator between two consecutive recharge events of the aerosol generator's battery, Preferably, the method according to any one of claims 1 to 7, wherein controlling the aerosol generator based on the histogram feature information includes adjusting the operating constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management, and / or preferably terminating a battery recharge event of the aerosol generator at a charge state of less than 100%, preferably less than 95%, or less than 90%, or less than 85%, or less than 80%.

9. The method further includes determining the duration of the battery recharge event of the aerosol generator from the histogram feature information, Preferably, the method according to any one of claims 1 to 8, wherein controlling the aerosol generator based on the histogram feature information includes adjusting the operational constraints of the aerosol generator, including limitations on the battery and / or power and / or charge management, and / or preferably limiting the charging rate during a battery recharge event of the aerosol generator.

10. The method according to any one of claims 1 to 9, comprising collecting the at least one usage pattern parameter along with location and / or time information relating to where and / or when the aerosol generator operates.

11. This includes identifying different usage patterns of the aerosol generator at different locations and / or over different time periods, and preferably creating separate histograms and / or bins for the locations and / or time periods. Preferably, the method according to claim 10, comprising: extracting histogram feature information from the histogram corresponding to the location and / or time of current use of the aerosol generator; and controlling the aerosol generator based on the histogram feature information extracted from the histogram.

12. The method according to any one of claims 10 to 11, comprising hierarchizing the collected values ​​of the at least one usage pattern parameter into one or more categories according to the location information and / or time information.

13. The method according to any one of claims 1 to 12, comprising dynamically adjusting the number of bins in the histogram used to classify the values ​​of the at least one usage pattern parameter.

14. An aerosol generator configured to carry out the steps of the method described in any one of claims 1 to 13.

15. An aerosol generating system comprising an aerosol generating device and a companion device that can be communicatively connected to the aerosol generating device, wherein the companion device is configured to carry out the steps of the method according to any one of claims 1 to 13.

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