Method for controlling aerosol-generating device using histogram

Abstract

A computer-implemented method of controlling an aerosol-generating device, the method comprising: collecting a plurality of values of at least one usage pattern parameter relating to usage of the aerosol-generating device; creating a histogram by classifying each collected value of the usage pattern parameter into a box of the histogram; extracting histogram feature information from the histogram; and controlling the aerosol-generating device with operational constraints based on the histogram feature information.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a computer-implemented method of controlling an aerosol-generating device. The present disclosure also 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

[0002] Generally, aerosol-generating devices are designed as hand-held devices that can be used by a user for consuming or experiencing, for example, during one or more usage sessions, an aerosol generated by heating an aerosol-generating substrate or an aerosol-generating article. The aerosol-generating devices to which the present disclosure relates are generally referred to as heat-not-burn devices, electronic cigarettes and / or vaporizers. The Applicant has, for example, marketed such devices under the brand name GLO

[0003] Exemplary aerosol-generating substrates can comprise a solid substrate material, such as a tobacco material or a tobacco cast leaf (TCL) material. The substrate material may, for example, be generally assembled together with other elements or components to form a substantially rod-like aerosol-generating article. This rod or aerosol-generating article can be configured in shape and size to be at least partially inserted into an aerosol-generating device, which may, for example, comprise a heating element or a heater arrangement for heating the aerosol-generating article and / or the aerosol-generating substrate. Alternatively or additionally, the aerosol-generating substrate can comprise one or more liquids and / or solids, which may, for example, be supplied to the aerosol-generating device in the form of a cartridge or a container. A corresponding exemplary aerosol-generating article may, for example, comprise a cartridge containing or fillable with a liquid and / or solid substrate, which can be vaporized during a user-based consumption of an aerosol based on heating the substrate and / or the liquid. Generally, this cartridge or container can be coupled to, attached to or at least partially inserted into the aerosol-generating device. Alternatively, the cartridge can be fixedly mounted to the aerosol-generating device and refilled by inserting a liquid and / or solid into the cartridge.

[0004] For generating an aerosol during usage or consumption, heat can be supplied by a heating element, a heater arrangement or a heat source to heat at least a portion or part of the aerosol-generating substrate. The heating element, the heater arrangement or the heat source can be arranged in the hand-held portion of the hand-held device or the aerosol-generating device. Alternatively or additionally, at least a portion or the entire heating element or heater arrangement or heat source can be fixedly associated with or arranged within an aerosol-generating article, for example in the form of a rod or a cartridge, which can be attached to and / or powered by the hand-held portion of the hand-held device or the aerosol-generating device.

[0005] Exemplary heating elements or heater arrangements can be based on one or more of resistive heating, inductive heating, and microwave heating using electrical energy supplied via a battery of the aerosol-generating device, drawn from the battery, or stored in the battery. As used herein, a battery of an aerosol-generating device can generally refer to an energy storage device of the aerosol-generating device configured to store electrical energy. Thus, the term battery can include one or more capacitors, one or more accumulators, or other types of energy storage devices. Additionally, any reference herein to a battery can include a plurality of batteries.

[0006] Generally, an aerosol-generating device can comprise a battery providing electrical energy required for operating the aerosol-generating device and, in particular, for heating an aerosol-generating substrate and / or article, e.g. to generate an aerosol using one or more aerosol-generating articles in one or more usage processes. For example, the battery can be a lithium-ion battery. Generally, the battery capacity can be chosen such that the aerosol-generating device can provide at least a minimum number, e.g. at least two or more, consecutive usage processes or experiences to a user without having to recharge the battery or the aerosol-generating device in between. To improve the user experience, the aerosol-generating device can generally be designed to only allow a user to start a usage process if the battery contains enough electrical energy to completely finish the usage process. However, the energy required for a usage process can be highly variable and can depend on many factors from external parameters such as ambient temperature to user habits. Conventional statistical models for controlling aerosol-generating devices can be hampered by the limited computational power generally available on these devices. Additionally, in some cases or for some parameters, employing e.g. an average of the energy consumption per usage process can be too general and thus can not yield an accurate estimate for the individual usage case at hand. Thus, although it can well be possible to provide this process in full in a particular case, situations can arise in which a user can be denied a further usage process.

[0007] It can therefore be desirable to provide for improved control of an aerosol-generating device and / or aerosol-generating system.

[0008] This is achieved by the subject matter of the independent claims. Optional features are provided by the dependent claims and the description. SUMMARY

[0009] According to an aspect of the disclosure, there is provided a computer-implemented method of controlling an aerosol-generating device, the method comprising: collecting a plurality of values of at least one usage pattern parameter related to usage of the aerosol-generating device; creating a histogram by classifying each collected value of the usage pattern parameter into a bin of the histogram; extracting histogram feature information from the histogram; and controlling the aerosol-generating device with an operational constraint based on the histogram feature information. In other words, the method can comprise controlling the aerosol-generating device based on the histogram feature information by adapting an operational constraint of the aerosol-generating device.

[0010] The usage pattern parameter can be indicative of different usage and / or operational characteristics of the aerosol-generating device by the user. For example, the usage pattern parameter can be related to a parameter describing or relating to the usage or operation of the aerosol-generating device by the user, in particular the way and / or frequency and / or time and / or length of time and / or state in which the aerosol-generating device is used or operated by the user. The usage pattern parameter can be related to or relate to one or both of the usage process of the aerosol-generating device and the time between usage processes, for example, the rest time of the aerosol-generating device or a recharging event. Thus, the usage pattern parameters described herein can also be referred to herein as “parameters” which can characterize different preferences and / or habits of each individual user, which can differ between users. Thus, the method can provide a high degree of individual control of the aerosol-generating device.

[0011] In examples, at least one of the usage pattern parameters can be indicative of the usage or operation of the aerosol-generating device by the user to generate aerosol in one or more usage processes. For example, the puff volume can be measured during one or more usage processes and collected as a usage pattern parameter. An average or mean value can be calculated from the puffs, for example all puffs, from one usage process. Additionally or alternatively, the puff volume can be measured during more than one usage process. An average or mean value can be calculated from the puffs, for example all puffs, from all usage processes. Additionally or alternatively, there can also be parameters that can only be determined by observing more than one usage process. For example, the rest time between usage processes can only be determined if two usage processes occur. Another example can be the frequency of at least two usage processes in succession, in particular without recharging the aerosol-generating device in between. This parameter can also only be determined by observing more than one usage process. The value of the usage pattern parameter can be a numerical value corresponding to a degree or range or count of the usage pattern parameter.

[0012] A histogram can be an approximate or simplified representation of a distribution of values of a numerical data, e.g. values of at least one usage pattern parameter. In a histogram, each value can be classified into a bin, which represents a range or interval of values. Values that fall outside the range or interval of one bin can be classified into a different bin or optionally be ignored. The bins of a histogram can represent consecutive, adjacent and non-overlapping intervals or ranges of values of a usage pattern parameter. However, at least some bins can be overlapping. The bins can have but do not necessarily have the same size or width of ranges or intervals. Thus, the definition of a histogram can be the same as commonly used in the context of the present disclosure.

[0013] One of the advantages of using histograms in the present invention is that histograms can approximate a distribution of values of a usage pattern parameter and thus simplify the distribution of values of a usage pattern parameter. Thus, they can require much less computational power to operate and extract information compared to other statistical methods. At the same time, histograms can provide a more detailed underlying data resolution than, for example, averaging values as commonly applied. The inventors found that, especially when observing usage pattern parameters of users of aerosol-generating devices, there can often be a bimodal or multimodal pattern, which represents additional information in the data that would be lost when averaging values. For example, a user who experiences usage sessions of 2 minutes and 6 minutes with the same frequency would be considered to have an average usage session duration of 4 minutes, which would not correctly represent the individual usage sessions in the real usage sessions experienced by that user. In contrast, a histogram can clearly show this bimodal distribution, which can then be taken into account when controlling an aerosol-generating device.

[0014] Thus, a key feature of the present invention can be to extract histogram feature information from a histogram. The histogram feature information can correspond to or relate to or indicate one or more histogram features. The histogram feature information can represent a probability that a usage pattern parameter will have a certain value or will be in a certain range or interval of values in the future, preferably in the near future. In an example, the histogram feature information can represent a probability that a usage pattern parameter will have a certain value or will be in a certain range or interval of values in the next, i.e. upcoming or just starting, usage session or break period. This probability can be determined empirically from the data in the histogram, as will be explained in more detail below. Based on the histogram feature information, e.g. based on the probability of a future value of a usage pattern parameter, an aerosol-generating device can be controlled to adapt to and / or anticipate this future value and especially an upcoming usage session or break period.

[0015] Controlling an aerosol-generating device based on histogram feature information comprises adapting operational constraints or operation constraints of the aerosol-generating device in such a way that the operational constraints of the aerosol-generating device comply with the histogram feature information and thus with the individual usage preferences of the user of the aerosol-generating device. The operational constraints of the aerosol-generating device can be increased or tightened or decreased or relaxed. For example, if the currently implemented operational constraints of the aerosol-generating device indicate that no further usage session is to be provided to the user, but the histogram feature information indicates that according to the individual habits of the user, actually another usage session can be provided, the currently implemented operational constraints can be changed, in this case relaxed, to allow the device to provide another usage session to the user. Conversely, if the currently implemented operational constraints of the aerosol-generating device indicate that for example three usage sessions can be provided to the user with one fully charged battery, but the histogram feature information indicates that according to the individual habits of the user only two usage sessions can be provided, the currently implemented operational constraints can be changed, in this case tightened, so that only two usage sessions are provided to the user with one fully charged battery. They can relate to usage sessions and / or charging of the aerosol-generating device. The operational constraints can comprise limitations of the battery and / or power consumption management of the aerosol-generating device. They can also comprise limitations on the length / duration and / or number of usage sessions provided to the user before recharging of the battery. For example, the operational constraints of the aerosol-generating device can be the duration of a usage session in terms of length of time. If the histogram feature information extracted from the histogram indicates that the capacity of the battery is sufficient to support one or more usage sessions of a longer duration as currently set, the maximum duration of one or more, for example all, usage sessions can be increased. Conversely, if the histogram feature information extracted from the histogram indicates that the capacity of the battery is insufficient to support one or more usage sessions of a duration as currently set, the maximum duration of one or more, for example all, usage sessions can be decreased. In this way, an individual maximum duration of usage sessions can be found for each individual user. Other operational constraints can for example comprise the total number of usage sessions provided to the user before recharging of the battery, whether additional usage sessions are allowed, the state of charge at which the battery is charged when charging or the charging rate at which the battery is charged when charging. These constraints will be further explained below.

[0016] The usage pattern parameters can be collected over a predetermined time period. The predetermined time period can be for example a fixed number of hours, days, weeks or months after the first use of the aerosol-generating device. Alternatively, the predetermined time period can be the entire time since the first use of the aerosol-generating device. Optionally, the aerosol-generating device can be designed or configured to collect the usage pattern parameters, preferably automatically, periodically and / or continuously.

[0017] Collecting usage pattern parameters can comprise storing corresponding data indicative of one or more usage pattern parameters, for example in a data storage device of the aerosol-generating device or other device communicably coupled thereto. Alternatively or additionally, the aerosol-generating device can comprise means for determining usage pattern parameters, preferably as numerical values, and / or for storing data indicative of usage pattern parameters or corresponding values thereof. These means can be or can comprise, for example, counters and / or timers and / or sensors, such as temperature sensors, volume sensors, humidity sensors, and others. In examples, usage pattern parameters can be collected over the entire lifetime of the aerosol-generating device, which can mean from the first use process to the last use process of the aerosol-generating device.

[0018] The aerosol-generating device can comprise a storage device or memory in which the collected parameters, parameter values, and / or corresponding data can be stored. The collected usage pattern parameters can also be stored in a user profile and / or transmitted to another aerosol-generating device or other device communicably coupled to the aerosol-generating device, such as a companion device, a server, a smartphone, or other computing device.

[0019] The at least one usage pattern parameter can be selected from the following parameters:

[0020] - energy consumption per use process,

[0021] - number of use processes for which the aerosol-generating device has been operated to generate aerosol, preferably per predefined time interval, for example per day,

[0022] - duration of a use process,

[0023] - rest time between consecutive use processes, preferably wherein the usage pattern parameter value related to the rest time between consecutive use processes varies only for rest times between subsequent use processes of 0 to 40 minutes,

[0024] - frequency of consecutive, in particular at least two use processes without recharging of the aerosol-generating device in between (also referred to as back-to-back regime),

[0025] - ambient temperature during a use process,

[0026] - ambient air pressure during a use process,

[0027] - ambient humidity during a use process,

[0028] - ambient temperature during recharging of a battery of the aerosol-generating device,

[0029] - temperature of a battery of the aerosol-generating device during a use process,

[0030] - the temperature of the heating element or heater arrangement of the aerosol-generating device within a predefined time period before the start of a usage session,

[0031] - the number of puffs per usage session,

[0032] - the puff volume,

[0033] - the puff frequency,

[0034] - the puff rhythm,

[0035] - the time at which a pause mode was initiated at the aerosol-generating device,

[0036] - the time at which a pause mode was terminated at the aerosol-generating device,

[0037] - the duration of a pause mode at the aerosol-generating device,

[0038] - the rest time after recharging the aerosol-generating device,

[0039] - the rest time when the battery charge state is less than 10%,

[0040] - the rest time when the battery charge state is more than 90%,

[0041] - the density of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate an aerosol,

[0042] - the weight of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate an aerosol,

[0043] - the type of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate an aerosol,

[0044] - the humidity of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device,

[0045] - the temperature profile selected by the user.

[0046] The energy consumption per usage session can describe, for example, the amount of electrical energy discharged from the battery of the aerosol-generating device to provide or grant the usage session from the start of the usage session to the end of the usage session. This can be expressed in units of battery capacity, for example as a percentage of the state of charge (SOC) of the battery discharged to provide the usage session. It can also be expressed as the total amount of battery capacity required to provide the usage session, for example expressed in mAh, which is a standard representation of battery capacity.

[0047] The number of use sessions of the aerosol-generating device, the number of use sessions for which the aerosol-generating device has been operated can be relevant parameters, respectively, as it can characterize the intensity of the user’s use of the device. It can thus allow to distinguish between light and heavy users and can be used to describe the progress during the lifetime of the device and / or battery. The number of use sessions can alternatively be related to a reference different from a predefined time interval. For example, the number of use sessions between recharges of the device can be collected. For this value, the amount of time between two consecutive recharge events of the device can be irrelevant.

[0048] Although the method according to the present disclosure can comprise any one or any combination of the listed parameters, it is particularly preferred that at least one use pattern parameter can be selected from the parameters: the energy consumption per use session and / or the number of use sessions for which the aerosol-generating device has been operated to generate aerosol, preferably per predefined time interval.

[0049] The duration of one or more use sessions can vary from user to user and can have an impact on the strain on the battery. The amount of energy required within a use session can be highly correlated with its duration, as the aerosol-generating device should preferably maintain a heating temperature during this period. As an example only, a typical aerosol-generating device allows for use sessions of up to 6 minutes.

[0050] The rest time between consecutive use sessions can be related to the temperature of the device, the temperature of the heating element of the device and the temperature of the battery. During a use session, the heating element, the device and the battery can be heated by heating the aerosol-generating substrate or article. After a use session, the device and the battery start to become cold or cool down until the device and the battery reach ambient temperature. This duration of time can be referred to as rest time. As a non-limiting example, after about 40 minutes, the battery usually reaches ambient temperature, which can mean that different rest times of 40 minutes or more can have the same effect from a temperature point of view. For this reason, optionally, only rest times between 0 minutes and 40 minutes can result in different values for the corresponding use pattern parameter, while 40 minutes and more can have the same value. A short rest time, which is not sufficient for the device to reach ambient temperature, can have less stress on the battery and thus result in less battery degradation.

[0051] The frequency of at least two consecutive usage processes, in particular without recharging the aerosol-generating device or the battery in between, can also be referred to as back-to-back regime. This parameter can for example be described by the percentage of two consecutive usage processes that occur without the aerosol-generating device or the battery being recharged before starting the second usage process. For example, in an aerosol-generating device that is designed or configured to provide two usage processes after a full charge of the battery, recharging the aerosol-generating device after each usage process would result in a back-to-back regime of 0%, while recharging the device only after two usage processes have been performed would result in a back-to-back regime of 100%. A back-to-back regime of 50% would then describe a situation where the device is recharged after one usage process half of the time and only after two usage processes in the other half of the time. In general, the frequency of at least two consecutive usage processes can be determined by dividing the number of consecutive usage processes by the total number of usage processes.

[0052] Puffing in the sense of the present disclosure can describe a deep draw and / or puff on the aerosol-generating device when a user inhales a mixture of air and aerosol. A puff volume can describe the volume of the mixture that is inhaled in one deep draw or inhalation. Puff frequency and rhythm can describe the corresponding pattern in which the puffing characteristics of an individual user occur. Merely as an example, a typical aerosol-generating device is designed to allow up to 14 puffs per aerosol-generating article.

[0053] The pause mode can refer to a special mode of the aerosol-generating device that allows for pausing during a usage process. The pause mode can thus not be with respect to the rest time between usage processes and can be different from the rest time between usage processes.

[0054] The aerosol-generating device can operate in at least two operational modes, namely the aerosol release mode and the pause mode. The aerosol-generating device can be configured to heat the heating element, the aerosol-generating article and / or the substrate at a first temperature level in the aerosol release mode. Therein, the first temperature level can correspond to a predetermined heating temperature or a temperature above thereof, which can be sufficient to generate an aerosol. The aerosol-generating device can further be configured to heat the heating element, the aerosol-generating article and / or the substrate at a second temperature level below the first temperature level in the pause mode of the aerosol-generating device. The second temperature level can for example refer to a temperature above room temperature and below the first temperature level.

[0055] The user experience (also referred to herein as the use process or experience of the aerosol generating article) can be interrupted (e.g. by switching the device into a pause mode) and later resumed by the user, wherein the aerosol generating article or substrate can be held in a pause mode of the aerosol generating device at a temperature lower than the first temperature level and / or lower than a predetermined heating temperature used during normal use of the device, in particular during the user experience or use process, but still higher or much higher than room temperature. That is, preferably the second temperature level can be selected such as to avoid degradation of the unconsumed substrate or aerosol generating article. In particular, the second temperature level can be selected such as to be low enough to minimize consumption of the substrate or article during the pause mode, and at the same time high enough to avoid condensation of the vapour in the device, which can otherwise affect the quality of the unconsumed aerosol generating substrate or article.

[0056] During use of the device, in particular when the user experience or use process is to take place, the aerosol generating device can be operated in an aerosol release mode, while during a pause of use of the device, i.e. when the user experience or use process is not taking place and / or when the use process is interrupted by a pause, the aerosol generating device can be operated in a pause mode. In both the aerosol release mode and the pause mode of the aerosol generating device, the heating element, heating circuitry and / or heating means can be in operation, in particular in heating operation, but at different temperature levels, i.e. at a first temperature level which can be selected high enough to generate an aerosol during the aerosol release mode, and at a second temperature level which is lower than the first temperature level during the pause mode, which can be selected low enough to minimize consumption of the substrate, while avoiding degradation.

[0057] Depending on the type and composition of the particular aerosol generating article or substrate to be used with the device, the first temperature level can be in the range between 250 degrees Celsius and 450 degrees Celsius, in particular between 270 degrees Celsius and 430 degrees Celsius, more particularly between 315 degrees Celsius and 355 degrees Celsius. These temperatures can be suitable operating or heating temperatures sufficient to allow volatile compounds to be released from the aerosol generating article or substrate, e.g. during one or more use processes and / or when the device is operated in the aerosol release mode. For example, the first temperature level and / or heating temperature for a liquid aerosol generating article or substrate can be lower than for a solid aerosol generating article or substrate.

[0058] In general, the second temperature level can be chosen to maintain the usability of the aerosol generating article or substrate for an extended period of time. The second temperature level can also depend on the type and composition of the aerosol generating article or substrate to be used with the device. Thus, the second temperature level can be in the range between 175 degrees Celsius and 225 degrees Celsius, in particular between 185 degrees Celsius and 215 degrees Celsius, more particularly between 195 degrees Celsius and 205 degrees Celsius. These temperatures can be low enough to minimize the consumption of the substrate during the pause mode, but at the same time high enough to avoid condensation of the vapor in the device, which can lead to degradation of the aerosol generating article or substrate.

[0059] In order to avoid condensation effects in the device, in particular to avoid condensation of the substance in the aerosol generating article or substrate, the second temperature level can be at least 150 degrees Celsius, in particular at least 175 degrees Celsius, preferably at least 185 degrees Celsius, more preferably at least 195 degrees Celsius.

[0060] Conversely, in order to minimize the consumption of the substrate or article during the pause mode, the second temperature level can be at most 220 degrees Celsius, in particular at most 225 degrees Celsius, preferably at most 215 degrees Celsius, more preferably at least 205 degrees Celsius. In particular, the second temperature level can be chosen to reduce the formation of aerosol by at least 50%, such as compared to the aerosol release mode.

[0061] In relative terms, the second temperature level can be at least 50 degrees Celsius lower than the first temperature level, in particular at least 75 degrees Celsius lower, more particularly at least 100 degrees Celsius lower.

[0062] The temperature values given above can preferably be the average temperature of the aerosol generating article or substrate during operation of the device. In addition, as already mentioned, the temperature values can depend in particular on the type and composition of the aerosol generating article or substrate to be used with the device.

[0063] As used herein, the pause mode can refer to a first operating mode of the aerosol generating device in which the heating element, the heating circuitry and / or the heating device can be operated during an operation pause, i.e. a pause in the use of the aerosol generating device, i.e. when the user experience or use process is paused and aerosol generation can not occur or at least can be reduced to a minimum level. That is, in the pause mode, the aerosol generating device is in a use pause.

[0064] Conversely, the aerosol release mode can refer to a second operating mode of the aerosol-generating device, which is the normal heating operating mode of the heating element, the circuitry and / or the device for aerosol generation, the heating element, the heating circuitry and / or the heating device can be operated in said second operating mode during use of the device by a user, i.e. when the user experience or use process takes place, in particular when aerosol generation takes place. Generally, aerosol generation can take place continuously or on demand, in particular based on a puff, i.e. on demand when a user puffs.

[0065] The density, weight, type and / or humidity of the aerosol-generating substrate or the aerosol-generating article can be detected by the aerosol-generating device recognizing, sensing and / or identifying the stick or cartridge (e.g. by RFID or other means). As these factors can influence the energy required to generate an aerosol from the substrate or article, they also influence the battery degradation.

[0066] The method can further comprise collecting two or more usage pattern parameters and creating a histogram for each of the usage pattern parameters, and controlling the aerosol-generating device based on histogram feature information extracted from the plurality of histograms. The two or more usage pattern parameters can be selected from the list as described above. In case the method described herein involves more than one usage pattern parameter, e.g. at least two usage pattern parameters, these usage pattern parameters can be different from each other. Thus, each parameter can be one of the parameters listed above, wherein each parameter can be different from the other parameters. In particular, it is noted that two usage pattern parameters as used herein can not describe or refer to different values (e.g. numerical values) of the same parameter, but to values of different parameters. Each usage pattern parameter can be used to create at least one different histogram. In this way, information from an arbitrary number of or all collected usage pattern parameters can be extracted from the histograms. Thus, the method according to the present disclosure can provide detailed and highly individualized information, based on which the aerosol-generating device can be controlled.

[0067] In case one histogram or two or more histograms are used in the present application, it can be provided that at least one histogram feature information extracted from a histogram is weighted differently from other histogram feature information. Additionally or alternatively, it can be provided that histogram feature information extracted from different histograms is weighted differently. For example, at least one histogram feature information or each histogram feature information can be provided with a weighting or scaling factor (e.g. a multiplication factor) increasing or decreasing a value provided by the histogram feature information and used for controlling the aerosol-generating device. In this way, the method can take into account that different histogram feature information and / or different histograms and / or different usage pattern parameters can have different importance for controlling the aerosol-generating device. Thus, the value of more important histogram feature information and / or histograms and / or usage pattern parameters can be increased and thus have a greater influence on controlling the aerosol-generating device than less important histogram feature information and / or histograms and / or usage pattern parameters and vice versa.

[0068] Generally, the extracted histogram feature information or histogram features can relate to any information available in or derivable from the data provided as a histogram in relation to one or more usage pattern parameters. As explained above, providing data in one or more histograms can make further processing of the data easier and can require less computational power than conventional statistical methods while also possibly increasing the information content derivable or available from the one or more histograms.

[0069] In examples, the histogram feature information comprises at least one of:

[0070] - one or more local maxima of the histogram,

[0071] - the identity of one or more bins of the histogram corresponding to one or more local maxima of the histogram,

[0072] - one or more heights of bins of the histogram, preferably corresponding to one or more local maxima of the histogram,

[0073] - the sum of the heights of two or more bins of the histogram, preferably wherein the bins whose heights are summed are adjacent to each other,

[0074] - the average of the values of the usage pattern parameter classified into one or more bins of the histogram,

[0075] - the median of the values of the usage pattern parameter classified into one or more bins of the histogram,

[0076] - the maximum of the values of the usage pattern parameter classified into one or more bins of the histogram,

[0077] - a minimum value of the values of the usage pattern parameter that are classified into one or more bins of the histogram.

[0078] A local maximum of a histogram can for example be a bin or a grouping of adjacent bins having a greater height than adjacent bins or a grouping of adjacent bins. For example, a local maximum can be defined as a bin having the greatest height of all bins of the histogram. For the purpose of finding a local maximum, the heights of adjacent or adjacent bins can also be summed together. Thus, a local maximum can represent or indicate a bin or a grouping of bins (and thus represent or indicate a range of values of the usage pattern parameter represented by the bin or the grouping of bins) into which more values of the usage pattern parameter are classified than into other regions of the histogram. One histogram can have one or more local maxima, for example in a bimodal or multimodal distribution of values of the usage pattern parameter.

[0079] The identity of the one or more bins can correspond to a range of values of the usage pattern parameter that are classified into this one or more bins. By identifying the one or more bins of a local maximum, a range of values of the usage pattern parameter can be identified that frequently occurs during the collection of values of the one or more usage pattern parameters.

[0080] Preferably, the height of a bin can correspond to or can be proportional to the number of values of the usage pattern parameter that are classified into this bin. For example, if 3 values of a particular usage pattern parameter fall within the range of a particular bin and thus are classified into this bin, the height of this bin can be 3. Thus, it is immediately apparent that the heights of one or more bins can be summed together. For example, the heights of adjacent or adjacent bins can be summed.

[0081] A comparison between the summed heights of two or more groups of bins of one or more histograms can be provided. For example, the summed heights of all bins associated with at least one local maximum can be compared with the summed heights of all other bins, in particular with the summed heights of all other bins that are not associated with at least one local maximum. In this way, the probability that an upcoming event (e.g. a usage process or a break period) again falls within the range of values represented by the summed bins can be quickly and easily calculated, as will be explained in more detail below. An upcoming event again falling within the range of values represented by a bin or by more than one bin can mean that if the value of the usage pattern parameter in question is determined for that event, this value would be classified into this bin or this grouping of bins.

[0082] In general, many different conclusions can be drawn from the extracted histogram feature information and these conclusions can be used to control the aerosol-generating device. The method can comprise determining, e.g. within a predetermined degree of certainty, from the histogram feature information, the number of usage sessions that can be provided to a user by the maximum capacity of the battery of the aerosol-generating device to generate aerosol. Many of the usage pattern parameters mentioned above have an influence on the energy consumption during a usage session and can thus be used for this determination.

[0083] In an example, a suitable parameter can be the number of usage sessions in which the aerosol-generating device has been operated to generate aerosol between recharging the device and / or the energy consumption per usage session. For example, it can be determined that during the time in which the usage pattern parameters are collected, X usage sessions can be provided between two consecutive recharging events. It can thus be assumed that this number of usage sessions can be provided to the user again. Alternatively, it can be determined that during the time in which the usage pattern parameters are collected, the energy consumption per usage session is so high that X usage sessions can be provided when considering the maximum capacity of the battery of the aerosol-generating device. It can then be assumed that this number of usage sessions can be provided to the user again. The maximum capacity of the battery can be the nominal, initial or original maximum capacity or the current maximum capacity of the battery of the aerosol-generating device. During the lifetime of the aerosol-generating device, the battery capacity can decay with usage. The current maximum capacity of the battery can thus describe or relate to the actual state of the battery currently used in the device. The current maximum capacity of the battery can thus be smaller than the nominal, initial or original maximum capacity. There are several methods to determine the current battery capacity or decay state of the battery which can be employed and which therefore do not need to be explained in detail.

[0084] Throughout this disclosure, within a predetermined degree of certainty can mean a certainty of 95% or 90% or 85% or 80% or 75% or 70%. For example, from the collected values of the usage pattern parameters, it can be determined that X% of the values fall within a certain numerical range, which is represented by one or more bins of the histogram. It can then be determined from this with a certainty of X% that upcoming values of the usage pattern parameter can again lie within this numerical range. The predetermined degree of certainty can then be X%. The predetermined degree of certainty can also be a fixed value, e.g. Y%. It can then be provided that only bins representing at most Y% of the values of the usage pattern parameter are considered and / or this Y% can be compared to the X% determined as described above. The result of this comparison, e.g. that X% lies above or below Y%, can then be used to control the aerosol-generating device.

[0085] The method can additionally or alternatively comprise considering a current charge state of the battery of the aerosol-generating device, determining from the histogram characteristic information whether an additional use session can be provided, e.g. within a predetermined certainty. For example, if the average energy consumption per use session determined from the histogram is higher than the current charge state of the battery, it can be determined that an additional use session cannot be provided. Conversely, if the average energy consumption per use session determined from the histogram is lower than the current charge state of the battery, it can be determined that an additional use session can be provided. Instead of the average energy consumption, it can be determined from the histogram how much proportion of the total use sessions use less energy than the current charge state of the battery. To this end, for example, the height of all bins representing an energy consumption lower than the current charge state of the battery can be summed together and divided by the summed height of all other bins of the histogram relating to the energy consumption of each use session. The result can equal a probability that the current charge state of the battery can be sufficient for the upcoming use session and thus whether an additional use session can be provided.

[0086] Considering the result determined from the histogram characteristic information in the examples explained above, controlling the aerosol-generating device based on the histogram characteristic information can involve adjusting an operational constraint directed to or comprising a total number of use sessions provided to the user to generate aerosol before recharging the battery of the aerosol-generating device. In other words, the operational constraint can comprise a limit of the battery and / or power consumption management. Controlling the aerosol-generating device based on the histogram characteristic information can thus involve limiting the total number of use sessions provided to the user to generate aerosol before recharging the battery of the aerosol-generating device to a number of use sessions that can be provided within a predetermined certainty. Additionally or alternatively, controlling the aerosol-generating device based on the histogram characteristic information can involve allowing or prohibiting an additional use session before recharging the battery of the aerosol-generating device. This can also be achieved by adjusting an operational constraint relating to or comprising a limit of the battery and / or power consumption management. Again, additionally or alternatively, controlling the aerosol-generating device based on the histogram characteristic information can involve forcing and / or requesting a recharge of the battery. The aerosol-generating device can thus be designed such that the user cannot start a use session when a predetermined number of use sessions before recharging is reached or when it has been determined that an additional use session cannot be provided in full. In this way, the user experience is improved and wasting of the aerosol-generating article due to incomplete use sessions can be avoided. Forcing and / or requesting a recharge of the battery can involve putting the aerosol-generating device into a state in which a use session cannot be started. Additionally, a notification or message can be presented to the user informing the user that a recharge of the battery of the aerosol-generating device is necessary. To this end, the aerosol-generating device can comprise a light, a display, a loudspeaker or a vibration device delivering a visual, acoustic or haptic notification or message to the user.

[0087] The method can further comprise determining, from the histogram characteristic information, a total amount of battery capacity required to operate the aerosol-generating device between two consecutive recharging events of a battery of the aerosol-generating device, for example, within a predetermined determination degree. For example, it can be determined what percentage of the capacity of a fully charged battery is required to operate the aerosol-generating device between two consecutive recharging events. This percentage can relate to the state of charge (SOC) of the battery. Alternatively, the total amount of battery capacity required to operate the aerosol-generating device between two consecutive recharging events can also be expressed as an absolute value, for example, in mAh. Consecutive recharging events can relate to directly one after another recharging events with only a variable amount of rest time and / or a variable number of usage processes in between. Thus, from the perspective of one recharging event, consecutive recharging events can be the next recharging event or the previous recharging event. For example, by counting the number of usage processes between two consecutive recharging events, it can be determined how often a user operates the aerosol-generating device to provide usage processes before recharging the device again. The energy consumption of each usage process can then be summed up to determine the total amount of battery capacity required before the device is recharged again. Alternatively, the state of charge of the battery just before recharging or when recharging is initiated can be collected.

[0088] From this information, it can be determined that the user does not need the full capacity of the battery between two consecutive recharging events according to his individual user habits. For example, the number of usage sessions the user needs between two consecutive recharging events can be low such that the full capacity of the battery is not used. It can also be that the individual user habits of the user result in energy saving usage sessions such that the full capacity of the battery is not used between two consecutive recharging events. In this case, the aerosol-generating device can be controlled in a way that minimizes the degradation of the battery. For example, it can be prescribed that controlling the aerosol-generating device based on the histogram feature information comprises adjusting the operational constraints of the aerosol-generating device including the limits of the battery and / or power and / or charge management. This can mean that controlling the aerosol-generating device based on the histogram feature information comprises terminating a recharging event of the battery of the aerosol-generating device at a state of charge below 100%, preferably below 95% or below 90% or below 85% or below 80%. It is known that recharging a battery until it is fully charged causes accelerated degradation. Similarly, it is known that recharging a battery only to a state of charge below the maximum value slows down the degradation of the battery. If it is determined by the method of the present disclosure that the user only needs a small fraction of the total capacity of the battery or the maximum capacity, e.g. a small fraction of the current total capacity, this information can then be used to slow down the degradation of the battery by avoiding to fully charge the battery. Similarly, it is known that fully discharging a battery also accelerates the degradation of the battery. Therefore, the aerosol-generating device can be controlled such that the battery is not fully discharged during use and at least a remaining state of charge of the battery is maintained, e.g. 5% or 10% or 15% or 20% of the state of charge of the battery. This remaining state of charge of the battery can also be taken into account when determining when to terminate a recharging event of the battery such that the capacity of the battery between the remaining state of charge and the state of charge to which the battery is recharged before terminating the recharging event corresponds to the total amount of battery capacity needed to operate the aerosol-generating device between two consecutive recharging events.

[0089] The method can also comprise determining from the histogram feature information the amount of time a recharging event of the battery of the aerosol-generating device will last, e.g. within a predetermined degree of certainty. The histogram can for example relate to the usage pattern parameter - the duration of a recharging event of the aerosol-generating device. In other words, it can be determined from the individual habits of the user how long the aerosol-generating device is typically connected to a power source in order to charge its battery.

[0090] Taking this information into account, it can be provided that controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of the battery and / or power and / or charge management. This can mean that controlling the aerosol-generating device based on the histogram feature information comprises limiting the charging rate during a recharge event of the battery of the aerosol-generating device. High charging rates known for fast charging are detrimental in terms of battery decay. Therefore, it can be advantageous to limit the charging rate when the duration of the recharge event is known to be long enough to recharge the battery to a desired state of charge even with a limited charging rate. For example, a user can be in the habit of recharging the aerosol-generating device overnight, which provides enough time to slowly charge the battery with a limited charging rate. This will result in a slower decay of the battery and a longer lifetime.

[0091] The habits of a user, this is the habits of one particular user, can differ greatly for different locations and / or different times of operating the aerosol-generating device, e.g. operating the aerosol-generating device to generate aerosol during use or to recharge the battery. Therefore, the present invention can comprise collecting at least one usage pattern parameter and location information and / or time information related to where and / or when the aerosol-generating device is operated. The location information can relate to a geographical location.

[0092] The location information can be determined by means such as a global positioning system (GPS) or different global navigation satellite system (GNSS) systems; by a connection of the aerosol-generating device to a local area network, e.g. by Wifi or WLAN, e.g. a home Wifi, office Wifi or public Wifi of the user; mobile cellular network information or information from a geolocator tag.

[0093] The time information can relate to the time of day and / or the date of the calendar, e.g. determined by an internal timepiece and / or calendar of the aerosol-generating device. All usage pattern parameters mentioned herein can be collected with corresponding location information and / or time information. This information can be collected, for example, for each use, recharge event and / or rest time, e.g. for the start and / or end of a use, each recharge event and / or rest time.

[0094] Collecting one or both of the time and location information can enable a more detailed analysis of the data related to the usage pattern parameters. For example, the use of the aerosol-generating device can differ greatly when the user is at work and when the user is at home. The use can also differ for weekdays or holidays or working hours and free time. Therefore, the method can comprise identifying different usage patterns of the aerosol-generating device at different locations and / or in different time periods.

[0095] For example, separate histograms and / or bins can be created for the location and / or time period. In this sense, a usage pattern can describe a set of values of a usage pattern parameter collected together with location information and / or time information that is different from another set of values of the same usage pattern parameter collected together with different location information and / or time information. For example, if a usage pattern parameter has different values when collected at different locations and / or at different times, it can be determined that the usage pattern parameter has different usage patterns depending on the location and / or time at which the value of the usage pattern parameter is collected. It can then be provided that these different of values of the usage pattern parameter are taken into account by creating separate histograms for each usage pattern of the usage pattern parameter. Usage patterns can be considered different when histogram feature information extracted from histograms related to at least two usage patterns would result in controlling the aerosol-generating device differently based on the histogram feature information extracted from either of these histograms. For example, histograms related to different usage patterns can comprise different or different numbers of local maxima or any other histogram feature information or histogram features mentioned herein.

[0096] To make use of this additional information provided by location information and / or time information, the aerosol-generating device can be designed to collect current location information and / or time information. The current location information and / or time information can relate to the current situation of the aerosol-generating device and / or the user, for example to the location in which the aerosol-generating device and / or the user is currently located and / or the current time. In this way, information about the location and / or time at which the user currently uses the aerosol-generating device can be obtained. The method can comprise extracting histogram feature information from a histogram corresponding to the location and / or time of the current use of the aerosol-generating device and controlling the aerosol-generating device based on the histogram feature information extracted from the histogram. In this way, the control of the aerosol-generating device can be based on data related to the location and / or time at which the user actually uses the device. Thus, usage differences (e.g. resulting in different usage patterns) can be taken into account when controlling the aerosol-generating device.

[0097] The values of the usage mode parameter can have an unlimited range of numerical values. Thus, when different values of the usage mode parameter have the same meaning, they can also be classified into the same bin of the histogram, although they differ from each other in numerical value. Similarly, the location information and / or the time information collected together with the usage mode parameter can in principle have an unlimited number of numerical values. Thus, in order to identify different usage modes to meaningful locations and / or times at which each usage mode actually leads to a different way of controlling the aerosol-generating device from other usage modes, the location information and / or the time information can also be divided into meaningful groupings. For this reason, the method can optionally comprise stratifying the collected values of the at least one usage mode parameter into one or more categories according to the location information and / or the time information. Thus, each category can indicate or represent a stratification of the user’s movement and / or rhythm of life into meaningful sub-units of location and / or time.

[0098] For example, the method can comprise creating different categories for the collected values of at least one usage mode parameter relating to the value of the usage mode parameter or to the course of use of the aerosol-generating device

[0099] - at the user’s place of work,

[0100] - at the user’s home,

[0101] - during the user’s travels,

[0102] - at the user’s leisure location,

[0103] - during the user’s working hours,

[0104] - during the user’s free time,

[0105] - during the user’s holidays, or

[0106] - during spring or summer or autumn or winter.

[0107] The method can comprise receiving information from the user identifying a location and / or a time, e.g. the current location and / or the current time. Thus, the user can provide the aerosol-generating device with information that the location in which the user is currently located is his place of work or his home or another location that he frequents. Similarly, the user can provide the aerosol-generating device with information that he works on specific days and / or at specific times or that he will be on holiday on specific days and / or weeks. Additionally or alternatively, the method can comprise the aerosol-generating device determining this information itself by continuously collecting the underlying data and identifying the mentioned categories.

[0108] The categories relating to the user's travel can relate both to travel away from the places the user normally visits (e.g. relating to outdoor travel) and to travel between places the user normally visits (e.g. relating to travel between the user's home and a place of work or leisure).

[0109] The method can comprise creating separate histograms for the values of the usage pattern parameters relating to at least two or more or all of the categories mentioned above. In this way, the control of the aerosol-generating device by the method of the present disclosure can take into account different usage patterns or user habits linked to different locations and / or times. For example, a user can recharge the aerosol-generating device more frequently at home than at work, so when the user is at home, the battery can not need to be fully recharged, but when the user is at work, the battery can need to be fully recharged according to the principles outlined above. By splitting the available data into different histograms corresponding to location information and / or time information, the method according to the present disclosure can provide an adaptive, intelligent control of the aerosol-generating device that requires only minimal computational power.

[0110] The histograms used in the method can have any number of bins required to represent the underlying data in a meaningful way. Different histograms can have different numbers of bins. The number of bins of each histogram can change as more values of the represented usage pattern parameters are collected over time. For example, the method can comprise dynamically adjusting the number of bins of the histogram used to classify the values of at least one usage pattern parameter. Different numbers of bins can be required as the number of collected values and / or the distribution of values of the usage pattern parameter changes over time. The method can also comprise limiting the number of values of at least one usage pattern parameter or all usage pattern parameters to a certain number of values or to values collected during a predetermined time period. For example, the number of values of at least one usage pattern parameter can be limited to the last 50 or 40 or 30 or 20 or 10 collected values of at least one usage pattern parameter. Any values relating to values collected earlier than this number can be removed. Similarly, the method can comprise limiting the collected values of at least one usage pattern parameter to values collected during a predetermined time period, for example the past 12 months or 6 months or 3 months or one month or 2 weeks or one week or one day. Any values collected before this period can be removed. In this way, the data relied on by the control of the aerosol-generating device can always be up to date. At the same time, the computational power required by the method according to the present disclosure is further reduced. As the data represented by each histogram can change over time, how this data is organised in the histogram can also change by dynamically adjusting the number of bins.

[0111] For example, it can be determined that the number of bins of the histogram is too low to extract any meaningful histogram feature information. In other words, the bins available in the histogram can provide too low data resolution for extracting meaningful histogram feature information from the histogram. This is often the case when too many values of the usage pattern parameter are classified into a single bin of the histogram. Therefore, the method can optionally comprise increasing the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter when the percentage of values of the at least one usage pattern parameter in one bin exceeds a predetermined threshold. The predetermined threshold can for example be 50% or 60% or 70% or 80% or 90% of all values of the at least one usage pattern parameter related to the histogram. The number of bins of the histogram can for example be increased by dividing the range of values classified into the bin, preferably the bin having the most values classified into it, into two or more ranges or sub-ranges, each new range or sub-range being represented by a new bin, and reclassifying the values of the at least one usage pattern parameter accordingly.

[0112] Additionally or alternatively, the method can comprise increasing the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter when the collected values of the at least one usage pattern parameter do not fit into any of the available bins. In this case, a new bin can be created, the new bin representing the range of values the collected values of the at least one usage pattern parameter fit into. The new bin can be added to the histogram such that the collected values can subsequently in the future be classified into this bin.

[0113] The method can further comprise decreasing the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter when the percentage of values of the at least one usage pattern parameter in all bins falls below a predetermined threshold. The predetermined threshold can for example be 10% or 20% or 30% or 40% of all values of the at least one usage pattern parameter related to the histogram. In this case, adjacent bins can be joined together or merged such that a new bin can be created, the new bin representing the range of values of the two bins together. Therefore, the heights of the merged bins can also be summed up to determine the height of the new bin. Additionally or alternatively, bins into which no values are classified can be deleted. Such empty bins can occur for example due to older values of the usage pattern parameter being deleted.

[0114] In addition to the ways of extracting histogram feature information as outlined above, other methods can be used for this purpose. For example, the method can comprise using an (artificial) intelligence engine or network or machine learning to extract the histogram feature information from the histogram and / or to control the aerosol-generating device based on the histogram feature information. For example, a convolutional neural network (CNN), a random forest, a decision forest, a decision tree, etc. can be used to extract the histogram feature information and / or to control the aerosol-generating device. These engines or networks can be trained beforehand on large datasets such that they are able to make accurate decisions based on the data available on each of the aerosol-generating devices. Organizing this data in a histogram can improve the performance of the (artificial) intelligence engine or intelligent network or machine learning.

[0115] According to another aspect of the disclosure, there is provided an aerosol-generating device configured to perform the steps of the method according to the disclosure (e.g. at least a subset of the steps of the method or all steps of the method). All features, effects and advantages described for the method are valid and equally applicable to the aerosol-generating device and vice versa.

[0116] The aerosol-generating device can comprise a battery for storing electrical energy and processing circuitry or control circuitry having one or more processors configured to perform the steps of the method as disclosed herein (e.g. at least a subset of the steps of the method or all steps of the method).

[0117] According to another aspect of the disclosure, there is provided an aerosol-generating system comprising a control device, wherein the control device is configured to perform the steps of the method according to the disclosure (e.g. at least a subset of the steps of the method or all steps of the method). The control device may, for example, comprise processing circuitry having one or more processors. Additionally or alternatively, the aerosol-generating system can comprise an aerosol-generating device and a companion device communicably coupled to the aerosol-generating device, wherein the companion device is configured to perform the steps of the method according to the disclosure (e.g. at least a subset of the steps of the method or all steps of the method). All features, effects and advantages described for the method are valid and equally applicable to the aerosol-generating system and vice versa.

[0118] The companion device can be, for example, a smartphone, a tablet, a personal computer, a computing device, a server, or a device configured to charge the aerosol-generating device. It can be advantageous to perform the method according to the present disclosure on a companion device, in particular in cases where the companion device can have more computational power than the aerosol-generating device. Additionally, in cases where a user owns and / or operates more than one aerosol-generating device, all of these devices can be communicably coupled to the companion device, so that the companion device can collect data (e.g., values of usage pattern parameters) from multiple aerosol-generating devices. In this way, control over all aerosol-generating devices can be improved, regardless of which aerosol-generating device the user uses at what time or at what location.

[0119] According to another aspect of the present disclosure, there is provided a computer program or software or computer executable code that, when executed on a processor of an aerosol-generating device and / or a companion device, performs the steps of the method according to the present disclosure (e.g., at least a subset of the steps of the method or all steps of the method). All features, effects and advantages described for the method are valid and equally applicable for the computer program or software or computer executable code and vice versa.

[0120] According to another aspect of the present disclosure, there is provided a computer readable medium having stored thereon a computer program or software or computer executable code that, when executed on a processor of an aerosol-generating device and / or a companion device, performs the steps of the method according to the present disclosure (e.g., at least a subset of the steps of the method or all steps of the method). All features, effects and advantages described for the method are valid and equally applicable for the computer readable medium and vice versa.

[0121] The application is defined in the claims. However, a non-exhaustive list of non-limiting examples is provided below. Any one or more of the features of these examples can be combined with any one or more features of another example, embodiment, or aspect described herein.

[0122] Example 1. A computer-implemented method of controlling an aerosol-generating device, the method comprising:

[0123] collecting a plurality of values of at least one usage pattern parameter related to usage of the aerosol-generating device;

[0124] creating a histogram by classifying each collected value of the usage pattern parameter into a bin of the histogram;

[0125] extracting histogram feature information from the histogram; and

[0126] controlling the aerosol-generating device with an operational constraint based on the histogram feature information.

[0127] Example 2. The method according to Example 1, wherein the at least one usage pattern parameter is selected from the following parameters:

[0128] - energy consumption per usage session,

[0129] - number of usage sessions for which the aerosol-generating device has been operated to generate aerosol, preferably per predefined time interval,

[0130] - duration of a usage session,

[0131] - rest time between consecutive usage sessions, preferably wherein the usage pattern parameter value related to the rest time between consecutive usage sessions only varies for rest times between subsequent usage sessions of 0 to 40 minutes,

[0132] - frequency of consecutive, in particular at least two, usage sessions, in particular without recharging the aerosol-generating device in between,

[0133] - ambient temperature during a usage session,

[0134] - ambient air pressure during a usage session,

[0135] - ambient humidity during a usage session,

[0136] - ambient temperature during recharging of a battery of the aerosol-generating device,

[0137] - temperature of a battery of the aerosol-generating device during a usage session,

[0138] - temperature of a heating element or heater arrangement of the aerosol-generating device within a predefined time period before the start of a usage session,

[0139] - number of puffs per usage session,

[0140] - puff volume,

[0141] - puff frequency,

[0142] - puff rhythm,

[0143] - time at which a pause mode is initiated at the aerosol-generating device,

[0144] - time at which a pause mode is terminated at the aerosol-generating device,

[0145] - duration of a pause mode at the aerosol-generating device,

[0146] - duration of a recharging event of the aerosol-generating device,

[0147] - rest time after recharging the aerosol-generating device,

[0148] - rest time when the battery charge state is less than 10%,

[0149] - rest time when the battery charge state is greater than 90%,

[0150] - density of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,

[0151] - weight of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,

[0152] - type of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,

[0153] - humidity of an aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device,

[0154] - temperature profile selected by a user.

[0155] Example 3. The method according to any one of the preceding examples, comprising collecting two or more usage pattern parameters, and creating a histogram for each of the usage pattern parameters, and controlling the aerosol-generating device based on histogram feature information extracted from the plurality of histograms.

[0156] Example 4. The method according to the previous example, wherein at least one histogram feature information extracted from the histograms is weighted differently from other histogram feature information; and / or

[0157] wherein histogram feature information extracted from different histograms is weighted differently.

[0158] Example 5. The method according to any one of the preceding examples, wherein the extracted histogram feature information comprises at least one of:

[0159] - one or more local maxima of the histogram,

[0160] - identity of one or more bins of the histogram corresponding to one or more local maxima of the histogram,

[0161] - one or more heights of bins of the histogram corresponding to one or more local maxima of the histogram, preferably wherein a height of a bin corresponds to or is proportional to a number of values of the use pattern parameter classified into this bin,

[0162] - a sum of heights of two or more bins of the histogram, preferably wherein a height of a bin corresponds to or is proportional to a number of values of the use pattern parameter classified into this bin,

[0163] - a mean of values of the use pattern parameter classified into one or more bins of the histogram,

[0164] - a median of values of the use pattern parameter classified into one or more bins of the histogram,

[0165] - a maximum of values of the use pattern parameter classified into one or more bins of the histogram,

[0166] - a minimum of values of the use pattern parameter classified into one or more bins of the histogram.

[0167] Example 6. The method according to any of the preceding examples, further comprising determining at least one of the following from the histogram feature information:

[0168] - a number of use sessions that can be provided to a user for generating aerosol by a maximum capacity of a battery of the aerosol-generating device, preferably wherein the maximum capacity of the battery is a nominal maximum capacity or a current maximum capacity of a battery of the aerosol-generating device,

[0169] - whether additional use sessions can be provided taking into account a current state of charge of a battery of the aerosol-generating device.

[0170] Example 7. The method according to the preceding example, the method preferably further comprising the step of changing operating constraints of the aerosol-generating device including limits of a battery and / or power consumption management based on the histogram feature information, and / or wherein controlling the aerosol-generating device based on the histogram feature information preferably comprises at least one of:

[0171] - limiting a total number of use sessions that can be provided to a user for generating aerosol before recharging a battery of the aerosol-generating device to a number of use sessions that can be provided within a predetermined determined degree,

[0172] - allowing or prohibiting additional use sessions before recharging a battery of the aerosol-generating device; and / or

[0173] - forcing and / or requesting recharging of the battery.

[0174] Example 8. The method according to any of the preceding examples, further comprising determining from the histogram feature information a total amount of battery capacity required for operating the aerosol-generating device between two consecutive recharging events of a battery of the aerosol-generating device.

[0175] Example 9. The method according to the previous example, wherein controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of battery and / or power and / or charge management, and / or preferably comprises terminating a recharging event of a battery of the aerosol-generating device at a state of charge below 100%, preferably below 95% or below 90% or below 85% or below 80%.

[0176] Example 10. The method according to any of the preceding examples, further comprising determining from the histogram feature information an amount of time for which a recharging event of a battery of the aerosol-generating device will last.

[0177] Example 11. The method according to the previous example, wherein controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of battery and / or power and / or charge management, and / or preferably comprises limiting a charging rate during a recharging event of a battery of the aerosol-generating device.

[0178] Example 12. The method according to any of the preceding examples, comprising collecting the at least one usage pattern parameter together with location information and / or time information related to where and / or when the aerosol-generating device is operated.

[0179] Example 13. The method according to the previous example, comprising identifying different usage patterns of the aerosol-generating device at different locations and / or in different time periods, and preferably creating separate histograms and / or bins for the locations and / or time periods.

[0180] Example 14. The method according to the previous example, comprising extracting histogram feature information from the histogram corresponding to a location and / or time of a current usage of the aerosol-generating device, and controlling the aerosol-generating device based on the histogram feature information extracted from the histogram.

[0181] Example 15. The method according to any of the examples 12 to 14, comprising stratifying collected values of the at least one usage pattern parameter into one or more categories according to the location information and / or time information.

[0182] Example 16. The method according to the previous example, comprising creating different categories for the collected values of the at least one usage pattern parameter related to the usage process of the aerosol-generating device occurring at

[0183] - at the user’s workplace,

[0184] - at the user’s home,

[0185] - during the user’s travels,

[0186] - at the user’s leisure place,

[0187] - during the user’s working hours,

[0188] - during the user’s free time,

[0189] - during the user’s holidays, or

[0190] - during spring or summer or autumn or winter.

[0191] Example 17. The method according to any of the previous examples, comprising dynamically adjusting the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter.

[0192] Example 18. The method according to any of the previous examples, comprising increasing the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter when the percentage of values of the at least one usage pattern parameter in one bin exceeds a predetermined threshold.

[0193] Example 19. The method according to any of the previous examples, comprising increasing the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter when the collected values of the at least one usage pattern parameter do not fit into any of the available bins.

[0194] Example 20. The method according to any of the previous examples, comprising decreasing the number of bins of the histogram used for classifying the values of the at least one usage pattern parameter when the percentage of values of the at least one usage pattern parameter in all bins falls below a predetermined threshold.

[0195] Example 21. The method according to any of the previous examples, wherein an intelligent engine or a network or machine learning is used to extract histogram feature information from the histogram and / or to control the aerosol-generating device based on the histogram feature information.

[0196] Example 22. An aerosol-generating device configured to perform the steps of the method according to any of the previous examples.

[0197] Example 23. The aerosol-generating device according to Example 22, comprising:

[0198] a battery for storing electrical energy; and

[0199] processing circuitry having one or more processors configured to perform the steps of the method according to any one of Examples 1 to 21.

[0200] Example 24. An aerosol-generating system comprising an aerosol-generating device and a companion device communicably coupled to the aerosol-generating device, wherein the companion device is configured to perform the steps of the method according to any one of Examples 1 to 21.

[0201] Example 25. The aerosol-generating system according to Example 24, wherein the companion device is a smartphone, a tablet, a personal computer, a server, or a device configured to charge the aerosol-generating device.

[0202] Example 26. A computer program that, when executed on a processor of an aerosol-generating device and / or a companion device, performs the steps of the method according to any one of Examples 1 to 21.

[0203] Example 27. A computer-readable medium having stored thereon a computer program that, when executed on a processor of an aerosol-generating device and / or a companion device, performs the steps of the method according to any one of Examples 1 to 21.

[0204] Example 28. An aerosol-generating system comprising a control device configured to

[0205] collecting a plurality of values of at least one usage pattern parameter related to the usage of the aerosol-generating device;

[0206] creating a histogram by classifying each collected value of the usage pattern parameter into a bin of the histogram;

[0207] extracting histogram feature information from the histogram; and

[0208] controlling the aerosol-generating device with operational constraints based on the histogram feature information.

[0209] Example 29. The aerosol-generating system according to the previous example, wherein the at least one usage pattern parameter is selected from the following parameters:

[0210] - energy consumption per usage session,

[0211] - number of usage sessions for which the aerosol-generating device has been operated to generate aerosol, preferably per predefined time interval,

[0212] - duration of a use session,

[0213] - break time between consecutive use sessions, preferably wherein the use pattern parameter value related to the break time between consecutive use sessions varies only for break times between 0 and 40 minutes,

[0214] - frequency of consecutive, in particular at least two use sessions without recharging of the aerosol-generating device in between,

[0215] - ambient temperature during a use session,

[0216] - ambient air pressure during a use session,

[0217] - ambient humidity during a use session,

[0218] - ambient temperature during a battery recharge of the aerosol-generating device,

[0219] - temperature of the battery of the aerosol-generating device during a use session,

[0220] - temperature of the heating element or heater arrangement of the aerosol-generating device within a predefined time period before the start of a use session,

[0221] - number of puffs per use session,

[0222] - puff volume,

[0223] - puff frequency,

[0224] - puff rhythm,

[0225] - time at which a pause mode is initiated at the aerosol-generating device,

[0226] - time at which a pause mode is terminated at the aerosol-generating device,

[0227] - duration of a pause mode at the aerosol-generating device,

[0228] - duration of a recharge event of the aerosol-generating device,

[0229] - break time after a recharge of the aerosol-generating device,

[0230] - break time when the battery charge state is less than 10%,

[0231] - break time when the battery charge state is greater than 90%,

[0232] - a density of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate an aerosol,

[0233] - a weight of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate an aerosol,

[0234] - a type of aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate an aerosol,

[0235] - a humidity of an aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device,

[0236] - a temperature profile selected by a user.

[0237] Example 30. Aerosol-generating system according to any one of Examples 28 to 29, wherein two or more usage pattern parameters are collected, and a histogram is created for each of the usage pattern parameters, and wherein the aerosol-generating device is controlled based on histogram feature information extracted from the plurality of histograms.

[0238] Example 31. Aerosol-generating system according to the previous example, wherein at least one histogram feature information extracted from the histograms is weighted differently from other histogram feature information; and / or

[0239] wherein histogram feature information extracted from different histograms is weighted differently.

[0240] Example 32. Aerosol-generating system according to any one of Examples 28 to 31, wherein the extracted histogram feature information comprises at least one of:

[0241] - one or more local maxima of the histogram,

[0242] - an identity of one or more bins of the histogram corresponding to one or more local maxima of the histogram,

[0243] - one or more heights of bins of the histogram corresponding to one or more local maxima of the histogram, preferably wherein a height of a bin corresponds to or is proportional to a number of values of the usage pattern parameter classified into this bin,

[0244] - a sum of heights of two or more bins of the histogram, preferably wherein a height of a bin corresponds to or is proportional to a number of values of the usage pattern parameter classified into this bin,

[0245] - an average of values of the usage pattern parameter classified into one or more bins of the histogram,

[0246] - a median of the values of the usage pattern parameter classified into one or more bins of the histogram,

[0247] - a maximum of the values of the usage pattern parameter classified into one or more bins of the histogram,

[0248] - a minimum of the values of the usage pattern parameter classified into one or more bins of the histogram.

[0249] Example 33. Aerosol-generating system according to any one of the Examples 28 to 32, wherein it is determined from the histogram characteristic information at least one of:

[0250] - the number of usage sessions that can be provided to a user to generate aerosol by a maximum capacity of a battery of the aerosol-generating device, preferably wherein the maximum capacity of the battery is a nominal maximum capacity or a current maximum capacity of a battery of the aerosol-generating device,

[0251] - whether additional usage sessions can be provided taking into account a current state of charge of a battery of the aerosol-generating device.

[0252] Example 34. Aerosol-generating system according to the preceding Example, the method preferably further comprising the step of changing operating constraints of the aerosol-generating device including limits of a battery and / or power consumption management based on the histogram characteristic information, and / or wherein controlling the aerosol-generating device based on the histogram characteristic information preferably comprises at least one of:

[0253] - limiting a total number of usage sessions that can be provided to a user to generate aerosol before recharging a battery of the aerosol-generating device to a number of usage sessions that can be provided within a predetermined determined degree,

[0254] - allowing or prohibiting additional usage sessions before recharging a battery of the aerosol-generating device; and / or

[0255] - forcing and / or requesting recharging of the battery.

[0256] Example 35. Aerosol-generating system according to any one of the Examples 28 to 34, wherein it is determined from the histogram characteristic information a total amount of battery capacity required to operate the aerosol-generating device between two consecutive recharging events of a battery of the aerosol-generating device.

[0257] Example 36. Aerosol-generating system according to the preceding example, wherein controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of the battery and / or power and / or charge management, and / or preferably comprises terminating a recharge event of the battery of the aerosol-generating device below 100%, preferably below 95% or below 90% or below 85% or below 80% state of charge.

[0258] Example 37. Aerosol-generating system according to any of the examples 28 to 36, further comprising determining an amount of time the recharge event of the battery of the aerosol-generating device will last according to the histogram feature information.

[0259] Example 38. Aerosol-generating system according to the preceding example, wherein controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of the battery and / or power and / or charge management, and / or preferably comprises limiting the charging rate during a recharge event of the battery of the aerosol-generating device.

[0260] Example 39. Aerosol-generating system according to any of the examples 28 to 38, wherein the at least one usage pattern parameter is collected together with location information and / or time information related to where and / or when the aerosol-generating device is operated.

[0261] Example 40. Aerosol-generating system according to the preceding example, wherein different usage patterns of the aerosol-generating device at different locations and / or in different time periods are identified, and wherein preferably separate histograms and / or bins are created for the locations and / or time periods.

[0262] Example 41. Aerosol-generating system according to the preceding example, wherein histogram feature information is extracted from a histogram corresponding to a current usage of the aerosol-generating device in terms of location and / or time, and wherein the aerosol-generating device is controlled based on the histogram feature information extracted from the histogram.

[0263] Example 42. Aerosol-generating system according to any of the examples 28 to 41, wherein the location information and / or time information is used to stratify collected values of the at least one usage pattern parameter into one or more categories.

[0264] Example 43. Aerosol-generating system according to the preceding example, wherein different categories are created for collected values of the at least one usage pattern parameter related to a usage process of the aerosol-generating device occurring

[0265] - at a work place of a user,

[0266] - at the user's home,

[0267] - during the user's travels,

[0268] - at the user's leisure location,

[0269] - during the user's working hours,

[0270] - during the user's free time,

[0271] - during the user's holidays, or

[0272] - during spring or summer or autumn or winter.

[0273] Example 44. Aerosol-generating system according to any of the Examples 28 to 43, wherein the number of bins of the histogram used to classify values of the at least one usage pattern parameter is dynamically adjusted.

[0274] Example 45. Aerosol-generating system according to any of the Examples 28 to 44, wherein the number of bins of the histogram used to classify values of the at least one usage pattern parameter is increased when the percentage of values of the at least one usage pattern parameter in one bin exceeds a predetermined threshold.

[0275] Example 46. Aerosol-generating system according to any of the Examples 28 to 45, wherein the number of bins of the histogram used to classify values of the at least one usage pattern parameter is increased when the collected values of the at least one usage pattern parameter do not fit into any of the available bins.

[0276] Example 47. Aerosol-generating system according to any of the Examples 28 to 46, wherein the number of bins of the histogram used to classify values of the at least one usage pattern parameter is decreased when the percentage of values of the at least one usage pattern parameter in all bins falls below a predetermined threshold.

[0277] Example 48. Aerosol-generating system according to any of the Examples 28 to 47, wherein an intelligence engine or a network or machine learning is used to extract histogram feature information from the histogram and / or to control the aerosol-generating device based on the histogram feature information.

[0278] Example 49. Aerosol-generating system according to any of the Examples 28 to 48, comprising an aerosol-generating device and a companion device, wherein the control device is arranged on the aerosol-generating device and / or the companion device. BRIEF DESCRIPTION OF DRAWINGS

[0279] Examples will now be further described with reference to the drawings in which:

[0280] Figure 1 An aerosol-generating system comprising an aerosol-generating device and a companion device is shown;

[0281] Figure 2 A histogram relating usage pattern parameter - energy consumption per use session is shown;

[0282] Figure 3 A histogram relating usage pattern parameter - number of use sessions for which the aerosol-generating device has been operated to generate aerosol per day is shown; and

[0283] Figure 4 A flowchart of a method is shown.

[0284] The drawings are merely schematic and are not drawn to scale. DETAILED DESCRIPTION

[0285] Figure 1 An aerosol-generating system 1 for generating aerosol for consumption, for example by a user in one or more use sessions is shown. The system 1 can comprise an aerosol-generating device 2 for generating aerosol and a companion device 3 for at least partially receiving the aerosol-generating device 2. The companion device 3 can be a charging device for charging the aerosol-generating device 2 and / or its energy storage device or battery.

[0286] The aerosol-generating device 2 can comprise an insertion opening 4 for at least partially inserting an aerosol-generating article 17. The aerosol-generating article 17 can comprise an aerosol-forming substrate, such as a tobacco-containing substrate, and / or a cartridge comprising a liquid, for example a liquid that can be aerosolized for inhalation.

[0287] The aerosol-generating device 2 can further comprise processing circuitry 5 or control circuitry 5 having one or more processors 6. For generating aerosol during use or consumption of the aerosol-generating article 17, the aerosol-generating device 2 can comprise at least one heating element 7 or heater device for applying heat to at least a portion of the aerosol-generating article 17. The processing circuitry 5 can be configured to control actuation, activation and / or deactivation of the at least one heating element 7. The processing circuitry 5 can be further configured to perform the steps of the methods described herein.

[0288] To power at least one heating element 7 with electrical power, the aerosol-generating device 2 can further comprise at least one energy storage device for storing electrical energy or power, e.g. in the form of a battery 15. The aerosol-generating device 2 can further comprise at least one electrical connector 12 for coupling to a corresponding at least one electrical connector 13 of the companion device 3. For example, when the aerosol-generating device 2 is at least partially inserted into the opening 14 of the companion device 3, one or more electrical connectors 12 of the aerosol-generating device 2 can couple with one or more electrical connectors 13 of the companion device 3 to charge at least one battery 15 of the aerosol-generating device 2.

[0289] The aerosol-generating device 2 can further comprise a user interface component, e.g. comprising an input element in the form of a button 8. The button 8 can serve as a power button to activate or deactivate the heating element 7 for aerosol generation, thereby activating or deactivating the aerosol-generating device 2. Upon activation of the aerosol-generating device 2, the heating element 7 can be activated and can apply heat to at least a portion of the aerosol-generating article 17 such that an aerosol can be generated for consumption by a user, e.g. during use.

[0290] The aerosol-generating device 2 can further comprise a communication device 9 or communication circuitry 9 having one or more communication interfaces 10 for communicatively coupling the aerosol-generating device 2 with the companion device 3, e.g. via an internet connection, a wireless LAN connection, a WiFi connection, a Bluetooth connection, a mobile phone network, a mobile data connection, e.g. but not limited to a 3G / 4G / 5G connection, an edge connection, an LTE connection, a BUS connection, a wireless connection, a wired connection, an optical data connection, such as, but not limited to, IrDa, a radio connection, a near field connection, and / or an IoT connection.

[0291] The aerosol-generating device 2 can further comprise a data storage device 11 for storing information or data, such as collected values of usage pattern parameters, battery decay data, and / or one or more mathematical functions or formulas, and for storing computer instructions that can be executed by the processing circuitry 5.

[0292] As described in detail herein above and herein below, the aerosol-generating device 2 is configured to collect, gather, and / or store values of at least one usage pattern parameter related to the usage of the aerosol-generating device 2. One or more sensors 16 can be arranged on the aerosol-generating device 2 to collect data, e.g. values of usage pattern parameters and / or battery capacity data and / or location information and / or time information.

[0293] Figure 2An example of a histogram relating to the usage pattern parameter - energy consumption of each usage process is shown. The histogram can comprise a total of five bins. The energy consumption of each usage process can be measured in terms of the total capacity of the battery used by each usage process. For each bin, the numerical range of the bin can be different. In Figure 2 In the example shown, the histogram can be designed to determine how many usage processes can be provided to the user by the energy stored in the battery 15 having a current maximum capacity of the exemplary value of 235 mAh in the range of 1 to 5 usage processes. The numerical range of the bins can be calculated by dividing the current maximum capacity of the battery 15 by the number of usage processes that can be provided in theory. The resulting number can represent the upper end of the numerical range of the respective bin, while the lower end of the numerical range of the respective bin can be 0 or determined by the upper end of the numerical range of the adjacent bin.

[0294] For example, the current maximum capacity of the battery 15 of 235 mAh divided by the maximum number of possible usage processes of 5 equals 47 mAh. This can be the upper end of the numerical range of the first bin, with the lower end being 0 mAh. The current maximum capacity of the battery 15 of 235 mAh divided by the next number of possible usage processes of 4 equals 59 mAh. This can be the upper end of the numerical range of the second bin, with the lower end starting at the end of the upper end of the previous bin. The current maximum capacity of the battery 15 of 235 mAh divided by the next number of possible usage processes of 3 equals 78 mAh. This can be the upper end of the numerical range of the third bin, with the lower end starting at the end of the upper end of the previous bin. The current maximum capacity of the battery 15 of 235 mAh divided by the next number of possible usage processes of 2 equals 117 mAh. This can be the upper end of the numerical range of the fourth bin, with the lower end starting at the end of the upper end of the previous bin. The current maximum capacity of the battery 15 of 235 mAh divided by the next number of possible usage processes of 1 equals 235 mAh. This can be the upper end of the numerical range of the fifth bin, with the lower end starting at the end of the upper end of the previous bin. Thus, the first bin can represent a numerical range of 0 to 47 mAh, the second bin can represent a numerical range of 48 to 59 mAh, the third bin can represent a numerical range of 60 to 78 mAh, the fourth bin can represent a numerical range of 79 to 117 mAh, and the fifth bin can represent a numerical range of 118 to 235 mAh.

[0295] During the operation of the aerosol generating device 2, the energy consumption value for each usage process can be collected and categorized into bins of a histogram. If the energy consumption of all usage processes of the aerosol generating device 2 is categorized into the first bin, it means that each usage process uses very little energy, and a single full charge of battery 15 can provide for a total of 5 usage processes. Similarly, if the energy consumption of all usage processes of the aerosol generating device 2 is categorized into the second bin, it means that a single full charge of battery 15 can provide for only 4 usage processes, and so on. In practice, the energy consumption of each usage process may not be so uniform. Figure 2 The histogram illustrates an exemplary, but more realistic, distribution of values ​​using the pattern parameter. Specifically, the number of values, n, in the first bin is 6, the number of values ​​in the second bin is 3, the number of values ​​in the third bin is 8, the number of values ​​in the fourth bin is 3, and the number of values ​​in the fifth bin is 0. Only the 20 most recent values ​​that have been collected can be represented in the histogram.

[0296] As by Figure 2 The represented histogram can be used to calculate how many usage sessions can be provided to the user within a predetermined degree of certainty using a single full charge of battery 15. 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 can be expressed as the percentage of the number n of values ​​classified into all bins of the histogram. For example, if the number n of values ​​classified into the first bin represents the percentage of all values ​​in the histogram of all bins equal to or greater than the percentage required for the predetermined degree of certainty, then a total of 5 usage sessions can be provided to the user. If this is not the case, then other bins must be considered. For example, if the sum of the number n of values ​​classified into the first and second bins represents the percentage of all values ​​in the histogram of all bins equal to or greater than the percentage required for the predetermined degree of certainty, then a total of 4 usage sessions can be provided to the user. If this is also not the case, then another bin can be considered. For example, the heights of the first, second, and third bins can be summed and checked against the predetermined degree of certainty explained above to check whether 3 usage sessions can be provided. Similarly, the heights of the first, second, third, and fourth boxes can be summed and checked against the predetermined certainty explained above to see if two usage processes can be provided. If this sum does not meet the predetermined certainty, then only one usage process can be provided.

[0297] exist Figure 2In the example, the first, second, and third boxes together contain or represent 17 of 20 most recent usage processes, where 20 is an exemplary, non-limiting value. This means that with 17 / 20 * 100% = 85% certainty, a single full charge of battery 15 can provide the user with 3 usage processes. Therefore, the method may include limiting the total number of usage processes provided to the user for generating aerosols before recharging battery 15 of aerosol generating device 2 to 3. This can also be used to determine whether additional usage processes are permitted based on the number of usage processes that have occurred since the last recharge event.

[0298] If a user is just starting to use aerosol generating device 2, there may not be enough data to make meaningful decisions based on the user's usage pattern parameters. In this case, it can be stipulated that aerosol generating device 2 is controlled in a predetermined manner until a sufficient dataset has been collected.

[0299] Figure 3 An example of a histogram is shown relating to the number of usage processes—a usage pattern parameter—that the aerosol generating device 2 has been operated to generate aerosols daily. This histogram may include a total of six bins, each representing one more usage process per day than the previous day. Figure 3 In the exemplary case, one value of the mode parameter has been classified into the first box, representing one usage process per day; three values ​​of the mode parameter have been classified into the second box, representing two usage processes per day; sixteen values ​​of the mode parameter have been classified into the third box, representing three usage processes per day; two values ​​of the mode parameter have been classified into the fourth box, representing four usage processes per day; and zero usage processes have been classified into the fifth and sixth boxes, representing five and six usage processes per day, respectively.

[0300] According to Figure 3 The histogram shown can determine how many usage sessions a user will require per day within a predetermined degree of certainty. The histogram feature information extracted from the histogram for this determination can still be represented by the height of the bins and the sum of these heights. For example, the first, second, and third bins together can contain or represent 20 of the total 22 collected values ​​of the usage pattern parameters. Therefore, it can be determined that the user will require a maximum of 3 usage sessions per day within a degree of certainty of 20 / 22 * 100% = 90.9%. If the user recharges the aerosol generating device 2 once a day, it can also be determined that the user will require 3 usage sessions between two consecutive recharge events of the aerosol generating device 2 within the same degree of certainty.

[0301] For example, we can assume that according to Figure 2 and Figure 3Both histograms of the same user are involved. As explained above, the maximum 78 mAh of battery capacity each use-process user will need within a certainty of 85% can be determined from the histogram in Figure 2 This means that, according to the histogram of Figure 3 , for 3 use-processes the user can need between recharging events, the user will need a total battery capacity of 3*78 mAh = 234 mAh. If the current maximum battery capacity of the battery 15 is 300 mAh, this required capacity can be provided with 234 / 300*100% = 78% of the state of charge of the battery 15. Thus, the battery 15 can be controlled in such a way that it is not recharged above a state of charge of e.g. 80% or 85% or 90%. This battery management can result in a lower battery degradation over time while still providing the required number of use-processes to the user within a high probability.

[0302] Figure 4 A flowchart of the method 18 of the present disclosure is shown. The method 18 can start with step 19, in which a plurality of values of at least one use-pattern parameter related to the use of the aerosol-generating device 2 can be collected, e.g. for a given number of use-processes. In step 20, a histogram can be created by classifying each collected value of the use-pattern parameter into a bin of the histogram. This can result in a histogram as shown, e.g. in Figure 2 and Figure 3 In step 21, histogram feature information can be extracted from the histogram. The histogram feature information can e.g. relate to the height of different bins of the histogram or the sum of the heights of adjacent bins. Finally, the method 18 can comprise step 22, in which the aerosol-generating device 2 can be controlled based on said histogram feature information. In particular, the method 18 can allow to adapt the operational constraints of the aerosol-generating device 2 according to the histogram feature information. The method 18 according to the present disclosure can allow to control the aerosol-generating device 2 taking into account individual user habits. Both battery management and / or the availability or duration of use-processes can be adapted in this way. At the same time, the method 18 requires only minimal memory or storage space and computational power and is thus suitable for implementation on the aerosol-generating device 2.

[0303] For purposes of this specification and appended claims, unless otherwise indicated, all numbers expressing amounts, quantities, percentages, and so forth, are to be understood as being modified in all instances by the term "about." Also, all ranges include the maximum and minimum points disclosed and include any intermediate ranges, which can not be expressly disclosed. Thus, in this context, a number A is understood as A ± 10% of A. In this context, the number A can be considered to include values within the general standard error of a measurement of the property modified by the number A. In certain instances in the appended claims, the number A can deviate from the percentage recited above, provided that the amount by which A deviates does not materially affect the basic characteristics and novel features of the claimed application. Also, all ranges include the maximum and minimum points disclosed and include any intermediate ranges, which can not be expressly disclosed.

Claims

1. A computer-implemented method of controlling an aerosol-generating device, the method comprising: collecting a plurality of values of at least one usage pattern parameter related to the usage of the aerosol-generating device; creating a histogram by classifying each collected value of the usage pattern parameter into a bin of the histogram; extracting histogram feature information from the histogram; and controlling the aerosol-generating device with operational constraints based on the histogram feature information.

2. The method according to claim 1, wherein the at least one usage pattern parameter is selected from the following parameters: - energy consumption per usage session, - number of usage sessions in which the aerosol-generating device has been operated to generate aerosol, preferably per predefined time interval, - duration of a usage session, - break time between consecutive usage sessions, preferably wherein the usage pattern parameter value related to the break time between consecutive usage sessions varies only for break times between 0 and 40 minutes, - frequency of consecutive, in particular at least two, usage sessions without recharging the aerosol-generating device in between, - ambient temperature during a usage session, - ambient air pressure during a usage session, - ambient humidity during a usage session, - ambient temperature during recharging of a battery of the aerosol-generating device, - temperature of a battery of the aerosol-generating device during a usage session, - temperature of a heating element or heater arrangement of the aerosol-generating device within a predefined time period before the start of a usage session, - number of puffs per usage session, - puff volume, - puff frequency, - puff rhythm, - time at which a pause mode is initiated at the aerosol-generating device, - time at which a pause mode is terminated at the aerosol-generating device, - duration of a pause mode at the aerosol-generating device, - duration of a recharging event of the aerosol-generating device, - break time after recharging the aerosol-generating device, - break time when the battery charge state is less than 10%, - break time when the battery charge state is more than 90%, - density of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol, - weight of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol, - type of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol, - humidity of an aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device, - temperature profile selected by a user.

3. The method according to claim 1, wherein the at least one usage pattern parameter is selected from the following parameters: - energy consumption per usage session, - number of usage sessions in which the aerosol-generating device has been operated to generate aerosol, preferably per predefined time interval. ​ 4. The method according to any one of the preceding claims, comprising collecting two or more usage pattern parameters and creating a histogram for each of the usage pattern parameters, and controlling the aerosol-generating device based on histogram feature information extracted from the plurality of histograms.

5. The method according to the preceding claim, wherein at least one histogram feature information extracted from the histograms is weighted differently than other histogram feature information; and / or wherein histogram feature information extracted from different histograms is weighted differently.

6. The method according to any one of the preceding claims, wherein the extracted histogram feature information comprises at least one of: - one or more local maxima of the histogram, - the identity of one or more bins of the histogram corresponding to one or more local maxima of the histogram, - one or more heights of bins of the histogram corresponding to one or more local maxima of the histogram, preferably wherein a height of a bin corresponds to or is proportional to the number of values of the usage pattern parameter classified into this bin, - the sum of the heights of two or more bins of the histogram, preferably wherein a height of a bin 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 of the histogram, - the median of the values of the usage pattern parameter classified into one or more bins of the histogram, - the maximum of the values of the usage pattern parameter classified into one or more bins of the histogram, - the minimum of the values of the usage pattern parameter classified into one or more bins of the histogram.

7. The method according to any one of the preceding claims, further comprising determining at least one of the following from the histogram feature information: - the number of usage sessions that can be provided to a user for generating aerosol by a maximum capacity of a battery of the aerosol-generating device, preferably wherein the maximum capacity of the battery is a nominal maximum capacity or a current maximum capacity of a battery of the aerosol-generating device, - whether an additional usage session can be provided taking into account a current state of charge of a battery of the aerosol-generating device, the method preferably further comprising the step of changing operating constraints of the aerosol-generating device including limits of a battery and / or power consumption management based on the histogram feature information, and / or wherein controlling the aerosol-generating device based on the histogram feature information preferably comprises at least one of: - limiting the total number of usage sessions that can be provided to a user for generating aerosol before recharging a battery of the aerosol-generating device to a number of usage sessions that can be provided within a predetermined determined degree, - allowing or prohibiting an additional usage session before recharging a battery of the aerosol-generating device; and / or - forcing and / or requesting a recharge of the battery. ​ 8. The method according to any one of the preceding claims, further comprising determining from the histogram feature information a total amount of battery capacity required for operating the aerosol-generating device between two consecutive recharging events of a battery of the aerosol-generating device, preferably wherein controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of battery and / or power and / or charge management, and / or preferably comprises terminating a recharging event of a battery of the aerosol-generating device at a state of charge below 100%, preferably below 95% or below 90% or below 85% or below 80%.

9. The method according to any one of the preceding claims, further comprising determining from the histogram feature information an amount of time for which a recharging event of a battery of the aerosol-generating device will last, preferably wherein controlling the aerosol-generating device based on the histogram feature information comprises adjusting operational constraints of the aerosol-generating device including limits of battery and / or power and / or charge management, and / or preferably comprises limiting a charging rate during a recharging event of a battery of the aerosol-generating device.

10. The method according to any one of the preceding claims, comprising collecting the at least one usage pattern parameter together with location information and / or time information related to where and / or when the aerosol-generating device is operated.

11. The method according to the preceding claim, comprising identifying different usage patterns of the aerosol-generating device at different locations and / or in different time periods, and preferably creating separate histograms and / or bins for the locations and / or time periods, preferably comprising extracting histogram feature information from the histogram corresponding to a location and / or time of a current usage of the aerosol-generating device, and controlling the aerosol-generating device based on the histogram feature information extracted from the histogram.

12. The method according to any one of claims 10 to 11, comprising stratifying 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 the preceding claims, comprising dynamically adjusting a number of bins of the histogram used for classifying values of the at least one usage pattern parameter.

14. An aerosol-generating device configured to perform the steps of the method according to any one of the preceding claims.

15. An aerosol-generating system comprising an aerosol-generating device and a companion device communicably coupled to the aerosol-generating device, wherein the companion device is configured to perform the steps of the method according to any one of claims 1 to 13.

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