Estimation of battery deterioration in aerosol generators

Abstract

A computer-implemented method for estimating capacity degradation of a battery of an aerosol generating device, the method comprising: collecting at least two usage pattern parameters related to use of the aerosol generating device; and calculating capacity degradation of the battery of the aerosol generating device based on the at least two usage pattern parameters.

Description

[Technical Field]

[0001] The present disclosure relates to a computer-implemented method for estimating capacity degradation of a battery in an aerosol generating device. The invention further relates to an aerosol generating device and an aerosol generating system configured to perform such a method. Furthermore, the invention relates to corresponding computer programs and corresponding non-transitory computer-readable media storing one or more of such computer programs. [Background technology]

[0002] Aerosol-generating devices are typically designed as handheld devices that a user can use to consume or experience the aerosol generated by heating an aerosol-generating substrate or aerosol-generating article, for example, in one or more use sessions. Aerosol-generating devices of interest in this disclosure are commonly referred to as heated tobacco products (HTPs), heat-not-burn devices, electronic cigarettes, and / or vaporizers.

[0003] Exemplary aerosol-generating substrates may comprise solid substrate materials, such as tobacco or tobacco cast leaf (TCL) materials. The substrate materials, for example, can often be assembled with other elements or components to form a substantially rod-shaped aerosol-generating article. Such rods or aerosol-generating articles may be configured in a shape and size to be at least partially inserted into an aerosol-generating device. The aerosol-generating system may also comprise a heating element or heater device for heating the aerosol-generating article and / or the aerosol-generating substrate. The heating element or heater device may be part of the aerosol-generating article and / or the aerosol-generating device. Alternatively or additionally, the aerosol-generating substrate may comprise one or more liquids and / or solids that can be supplied to the aerosol-generating device, for example, in the form of a cartridge or container. Corresponding exemplary aerosol-generating articles may comprise, for example, a cartridge containing or fillable with a liquid and / or solid substrate, which can vaporize during aerosol consumption by a user upon heating the substrate and / or liquid. Typically, such a cartridge or container can be coupled, attached, or at least partially inserted into the aerosol-generating device. Alternatively, the cartridge may be fixedly attached to the aerosol generating device and refilled by inserting liquids and / or solids into the cartridge.

[0004] To generate an aerosol during use or consumption, heat can be supplied by a heating element, heater device, or heat source to heat at least a portion or parts of the aerosol-generating substrate. The heating element, heater device, or heat source can be located in the handheld device or the handheld portion of the aerosol-generating device. Alternatively, or additionally, at least a portion or the entire heating element, heater device, or heat source can be fixedly associated with or located with the aerosol-generating article, for example in the form of a wand or cartridge that can be attached to and / or powered by the handheld device or the handheld portion of the aerosol-generating device.

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

[0006] Typically, the aerosol-generating device comprises a battery that provides the electrical energy necessary to operate the aerosol-generating device, in particular to heat the aerosol-generating substrate and / or articles, and to generate aerosol using, for example, one or more aerosol-generating articles, over one or more use sessions. The battery may, for example, be a lithium-ion battery.

[0007] As used herein, a use session may refer to a period of time during which a user may use an aerosol-generating device to generate, consume, experience, or inhale aerosol. A use session may be finite. In other words, a use session may have a beginning, an end, and a duration. The duration of a use session, as measured by time, may be affected by use during the use session. The duration of a use session may have a maximum duration determined by the longest time from the start of the use session. If one or more monitored parameters reach a predetermined threshold before the longest time from the start of the use session, the duration of the use session may be shorter than the maximum time. As an example, the one or more monitored parameters may include one or more of i) the cumulative number of puffs in a series of puffs taken by the user since the start of the use session, and ii) the cumulative volume of aerosol emitted from the aerosol-forming substrate since the start of the use session.

[0008] The battery capacity may typically be selected so that the aerosol generating device can provide a user with, for example, at least two or more consecutive use sessions or experiences without recharging the battery or the aerosol generating device. To improve the user experience, aerosol generating devices are typically designed to allow a user to initiate a use session only if the battery contains enough electrical energy to fully complete the use session. However, battery capacity may degrade over time with the accumulation of charge / discharge cycles. The rate and extent or degree of battery capacity degradation varies and may depend on many different factors, making it difficult to estimate or determine battery degradation. However, it may be advantageous to know in advance when the battery capacity of an aerosol generating device has degraded to the point where it can no longer provide a minimum number of consecutive use sessions without recharging the battery or the aerosol generating device. In this case, the user may be advised by a user interface signal to replace the battery in a timely manner so that limitations on use of the aerosol generating device do not occur. Additionally or alternatively, the device may be configured to output a signal indicating that the number of consecutive use sessions or experiences without recharging the battery or the aerosol generating device is decreasing.

[0009] Conventional battery degradation models typically include detailed information about the specific construction or design of the battery, which may not be available to aerosol generating device manufacturers. Furthermore, these models may lack the accuracy of predicting battery degradation in aerosol generating devices because battery capacity degradation may be strongly affected by the actual operation of the aerosol generating device. For example, temperature or heating cycles may be typical for aerosol generating devices but atypical for other applications. Furthermore, different users may have different habits or patterns in using aerosol generating devices, particularly continuous use with intermittent rest before charging, variable rest times, and different durations of use, which are considered as factors affecting conventional battery degradation models, but may result in insufficient accuracy in estimating battery degradation in aerosol generating devices.

[0010] It may therefore be desirable to provide an improved aerosol generating device and / or aerosol generating system that allows for improved estimation and / or determination of capacity degradation of the battery of the aerosol generating device, for example.

[0011] This is achieved by the subject matter of the independent claims. Optional features are provided by the dependent claims and the description. Summary of the Invention

[0012] According to one aspect of the present disclosure, a computer-implemented method for estimating and / or determining capacity degradation of a battery of an aerosol generating device is provided, the method including collecting at least two usage pattern parameters related to use of the aerosol generating device, and calculating capacity degradation of a battery of the aerosol generating device based on the at least two usage pattern parameters.

[0013] In other words, the capacity degradation of the battery of an aerosol generating device, which may generally refer to a decrease in the battery's capacity, can be determined directly from usage pattern parameters related to the use or operation of the aerosol generating device itself. As a result, the estimated or determined capacity degradation may reflect or include the actual operation of the aerosol generating device and, therefore, may be more accurate, particularly compared to traditional models of battery degradation that focus only on battery characteristics. Furthermore, traditional models of battery degradation may therefore not be suitable for a particular use case of the aerosol generating device and may not need to be employed.

[0014] The aerosol generating device may be designed or configured to collect usage pattern parameters during its operation, which can ensure that the collected usage pattern parameters relate to an actual individual user of the aerosol generating device. In this way, the predicted capacity degradation of the aerosol generating device's battery calculated from these usage pattern parameters can be tailored to the individual habits or usage pattern of the user. Note that the usage pattern parameters may also be referred to hereinafter as "parameters" for simplicity's sake.

[0015] As described in more detail below, the calculated capacity degradation of an aerosol generating device battery as used herein may relate to the degradation of the battery at a future time, e.g., after a predetermined period of time. Thus, the calculated capacity degradation may refer to estimated and / or predicted capacity degradation. Alternatively, or additionally, calculating capacity degradation may include, for example, estimating and / or predicting capacity degradation until a future time and / or after a predetermined period of time. Predicting capacity degradation may enable providing an early warning to a user of the aerosol generating device, for example, if the battery degradation will reach a certain level after a predetermined period of time has passed. The user may then replace the battery in a timely manner to avoid limiting the use of the aerosol generating device, which may improve the overall user experience.

[0016] The usage pattern parameters may be collected over a predetermined period of time. The predetermined period may be, for example, a certain number of hours, days, weeks, or months after the first use of the aerosol generating device. Alternatively, the predetermined period may be the entire time since the first use of the aerosol generating device. Optionally, the aerosol generating device may be designed or configured to collect the usage pattern parameters, preferably automatically and / or continuously. Collecting the usage pattern parameters may include storing corresponding data indicative of one or more usage pattern parameters, for example, in data storage on the aerosol generating device or another device communicatively coupleable to the aerosol generating device. Alternatively or additionally, the aerosol generating device may comprise means for determining the usage pattern parameters, preferably as numerical values, and / or for storing data indicative of the usage pattern parameters. These means may be or include, for example, counters and / or timers, and / or sensors such as temperature sensors, volume sensors, humidity sensors, etc.

[0017] In one example, the usage pattern parameters may be collected over the entire life of the aerosol generating device, which may mean from the first usage session to the last usage session of the aerosol generating device. The aerosol generating device preferably includes storage in which the collected parameters, parameter values, and / or corresponding data may be stored. The collected usage pattern parameters may also be stored in a user profile and / or transferred to another aerosol generating device or other device communicatively coupleable to the aerosol generating device.

[0018] In one embodiment, the usage pattern parameter may be an average value over a predetermined period of time. In other words, the aerosol generating device may be designed or configured to calculate an average value from all values ​​of at least two, preferably a single, specific collected usage pattern parameters. Thus, for each collected usage parameter, an average value may be calculated over a predetermined period of time. The predetermined period may be, for example, a certain number of hours, days, weeks, and / or months after the first use of the aerosol generating device. Alternatively, the predetermined period may be, for example, a certain number of hours, days, weeks, and / or months prior to the present, such that, for example, only recent values ​​of the usage pattern parameter may be collected and / or used. Alternatively, the predetermined period may be the entire time since the first use of the aerosol generating device. By providing average values ​​from usage pattern parameters collected, particularly over a longer period of time, future predictions of an individual user's usage pattern may be highly accurate, thereby making estimation of the capacity degradation of the aerosol generating device's battery more reliable.

[0019] The usage pattern parameters may indicate different usage and / or operational characteristics of the aerosol generating device by a user. When the methods described herein relate to more than one usage pattern parameter, e.g., at least two usage pattern parameters, these usage pattern parameters may differ from one another. Thus, each of the parameters may be one of the parameters further listed below, and each parameter may differ from the other parameters. In particular, as used herein, it should be noted that two usage pattern parameters may not describe or refer to different values, e.g., numerical values, of the same parameter, but may refer to values ​​of different parameters. For example, the usage pattern parameters may relate to parameters describing or relating to the use or operation of the aerosol generating device by a user, and in particular, may relate to how and / or how often and / or when and / or for how long and / or under what conditions the aerosol generating device is used or operated by the user. The usage pattern parameters may relate to or relate to one or both of usage sessions of the aerosol generating device and the time between usage sessions, e.g., aerosol generating device downtime or recharge events. Thus, the usage pattern parameters described herein may characterize the different preferences and / or habits of each individual user, which may vary between users and affect the rate and / or extent of battery capacity degradation. By employing the usage pattern parameters described herein in estimating such degradation, highly accurate predictions tailored to individual users can be achieved.

[0020] In one embodiment, at least one of the usage pattern parameters may indicate a user's use of the aerosol generating device to generate aerosol during one or more use sessions. For example, puff volume may be measured during one or more use sessions and collected as a usage pattern parameter. An average or mean value may be calculated from multiple puffs, such as all puffs from a single use session. Additionally or alternatively, puff volume may be measured during two or more use sessions. An average or mean value may be calculated from multiple puffs, such as all puffs from all use sessions. Alternatively or additionally, there may be parameters that can only be determined by observing two or more use sessions. For example, the pause time between use sessions can only be determined when two use sessions have occurred. Another example may be the frequency of at least two use sessions occurring consecutively, particularly without recharging the aerosol generating device in between. This parameter can also be determined by observing two or more use sessions.

[0021] Capacity degradation can be calculated as the relative decrease in the capacity of the battery relative to one or more of the battery's initial capacity, the battery's nominal capacity, and the battery's reference capacity. The capacity degradation of an aerosol generating device's battery can be a measure of the amount and / or quantity of electrical energy the battery can store at a particular point in time. This can be an absolute value expressed, for example, as ampere-hours or a similar unit of measure. Capacity degradation can also be expressed as a comparison to the original battery capacity, the initial battery capacity, the nominal battery capacity, or the reference capacity, for example, as a percentage. Capacity degradation can also be expressed in other units, for example, as the total number of usage sessions that a user may have or that can be provided to a user with a single fully charged battery. These other units can also be expressed as a comparison to an initial or reference value, for example, as a percentage.

[0022] A meaningful estimation of battery degradation can be achieved using at least two usage pattern parameters, although the accuracy of the estimation can increase when more usage pattern parameters are used in combination. In one embodiment, at least three, at least four or more usage pattern parameters can be collected and used to calculate and / or predict the capacity degradation of the battery of an aerosol generating device, each of which can optionally be indicative of a different usage characteristic of the aerosol generating device by the user.

[0023] As will be further explained below, a variety of different parameters can be advantageously used in the context of the present disclosure to estimate battery capacity degradation. However, the inventors have identified four parameters that may be particularly useful for simply and reliably estimating the capacity degradation of an aerosol generating device battery. Thus, in one embodiment, the usage pattern parameters are: the number of use sessions in which the aerosol generating device is operated to generate aerosol per given time interval, e.g., per day; the duration of one or more sessions of use; a pause time between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause time between successive use sessions only changes for pause times between subsequent use sessions of between 0 and 40 minutes; In particular, the frequency of at least two consecutive use sessions without recharging the aerosol generating device in between. The frequency of at least two consecutive use sessions may also be referred to as a back-to-back regime.

[0024] The number of usage sessions of an aerosol generating device may be a relevant parameter as it may characterize the intensity of the user's use of the device, and therefore may make it possible to distinguish between heavy users and may be used to explain trends in the lifespan of the device and / or battery.

[0025] The duration of one or more use sessions may vary from user to user and may affect the load on the battery. Because the aerosol generating device preferably maintains a heated temperature during this period, the amount of energy required for a use session may be highly correlated with its duration. The inventors have found that the longer the duration of a use session, the faster the battery capacity degradation.

[0026] The rest time between successive use sessions may be related to the temperature of the device, the device's heating element, and the battery. During a use session, the heating element, the device, and the battery may be heated by heating the aerosol-generating substrate or article. After a use session, the device and battery begin to cool. After about 40 minutes, the battery typically reaches ambient temperature, which may mean that different rest times of 40 minutes or more may have the same effect from a temperature perspective. For this reason, optionally, only rest times between 0 and 40 minutes may result in different values ​​for the corresponding use pattern parameter, while times greater than 40 minutes may have the same value. A shorter rest time, not long enough for the device to reach ambient temperature, may place less strain on the battery and therefore reduce battery degradation.

[0027] In particular, the frequency with which at least two consecutive use sessions occur without recharging the aerosol generating device or battery in between may also be referred to as a back-to-back regime. This parameter may be described, for example, as the percentage of two consecutive use sessions in which the aerosol generating device or battery is not recharged before the start of the second use session. For example, in an aerosol generating device designed or configured to provide two use sessions after a fully charged battery, recharging the aerosol generating device after each use session would result in a back-to-back regime of 0%, while recharging the device only after two use sessions have been performed would result in a back-to-back regime of 100%. A 50% back-to-back regime would then describe recharging the device after half the time of a single use session and only after the remaining two use sessions. Generally, the frequency of at least two consecutive use sessions may be determined by dividing the number of consecutive use sessions by the total number of use sessions.

[0028] The disclosed method may include collecting at least two, or at least three, or at least four usage pattern parameters selected from the parameters described above and using them to calculate, determine, compute, estimate, and / or predict capacity degradation of a battery in an aerosol generating device. Alternatively, the disclosed method may include collecting exclusively two, or exclusively three, or exclusively four usage pattern parameters selected from the parameters described above and using them to calculate capacity degradation of a battery in an aerosol generating device. Using only a selected set of parameters can simplify the model, data collection, and calculation, thereby reducing the need for high computing power and enabling the disclosed method to be easily implemented on a portable device.

[0029] There are several additional parameters that may be suitable for the method of the present disclosure, and therefore the present invention is not limited to the parameters mentioned above. In general, at least two, preferably at least three, or at least four usage pattern parameters are the following parameters: the number of use sessions in which the aerosol generating device was operated to generate aerosols per given time interval; the duration of one or more sessions of use; a pause between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause between subsequent use sessions only changes for pauses between subsequent use sessions of between 0 and 40 minutes; - frequency of at least two consecutive use sessions, particularly without recharging the aerosol generator in between; the amount of charge / discharge cycles per given time interval; - the downtime after recharging the aerosol generator; Rest time with battery state of charge (SOC) below 10%, Rest time with battery state of charge (SOC) above 90%, · Smoke intake amount, · Frequency of smoking, Smoking rhythm, the start time of the pause mode in the aerosol generator; the end time of the pause mode of the aerosol generator; the duration of the pause mode in the aerosol generating device; one or more ambient temperatures during one or more sessions of use; the temperature of the heating element or heater unit of the aerosol-generating device during a predetermined period before the start of a use session; Ambient temperature while recharging the battery, the density of the aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; the weight of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device to generate the aerosol; The type of aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; and the humidity of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device.

[0030] The number of charge / discharge cycles may relate to the number of times the aerosol generating device is used and then recharged per predetermined time interval, e.g., per day. The more such cycles, the more degradation the battery may undergo, making this parameter a suitable candidate for use in the methods of the present disclosure.

[0031] A puff in the sense of the present disclosure may describe inhaling and / or sucking on an aerosol-generating device while inhaling a mixture of air and aerosol by a user. A puff may describe the volume of said mixture inhaled in a single puff or inhalation. Puff frequency and rhythm may describe the corresponding pattern in the occurrence of puffs characteristic for an individual user.

[0032] A pause mode may refer to a special mode of an aerosol generating device that allows for pausing during a use session, and thus is not related to, and may be different from, the pause time between use sessions.

[0033] The aerosol generating device may be operated in at least two operating modes: an aerosol-emission mode and a pause mode. The aerosol generating device may be configured to heat the heating element, the aerosol-generating article, and / or the substrate at a plurality of different temperatures above a first temperature level or within a first temperature range in the aerosol-emission mode. The first temperature level and / or temperature within the first temperature range may correspond to a predetermined heating temperature or temperatures sufficient to generate an aerosol. The aerosol generating device may be further 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 may refer to, for example, a temperature above room temperature and below the first temperature level and / or within the first temperature range.

[0034] A user experience, also referred to herein as a use session or experience of an aerosol-generating article, may be interrupted, for example, by switching the device to a pause mode and later resumed by the user, and the aerosol-generating article or substrate may be maintained during the pause mode of the aerosol-generating device at a first temperature level and / or a temperature below a predetermined heating temperature used during normal use of the device (particularly during a user experience or use session), but still above room temperature or even much above room temperature. That is, the second temperature level is preferably selected to avoid degradation of the undepleted substrate or aerosol-generating article. In particular, the second temperature level may be selected to be sufficiently low to minimize depletion of the substrate or article during the pause mode, and at the same time sufficiently high to avoid condensation of vapor within the device, which could affect the quality of the undepleted aerosol-generating substrate or article.

[0035] During use of the device, particularly when a user experience or use session is taking place, the aerosol generating device may be operated in an aerosol emission mode, whereas during pauses in use of the device, i.e., when no user experience or use session is taking place and / or when a use session is interrupted by a pause, the aerosol generating device may be operated in a paused mode. During both the aerosol emission mode and the paused mode of the aerosol generating device, the heating element, heating circuit and / or heating arrangement may be in operation, particularly in heating operation, but at different temperature levels, i.e., a first temperature level during the aerosol emission mode, which is selected to be sufficiently high to generate an aerosol, and a second temperature level, lower than the first temperature level, during the paused mode, which is selected to be sufficiently low to minimize substrate depletion while avoiding degradation.

[0036] Depending on the type and composition of the particular aerosol-generating article or substrate used with the device, the first temperature level may be within the range of 200°C to 500°C, specifically 250°C to 450°C, specifically 270°C to 430°C, specifically 315°C to 355°C, or 240°C to 280°C. These temperatures may be suitable operating or heating temperatures sufficient to allow volatile compounds to be released from the aerosol-generating article or substrate, for example, during one or more use sessions and / or when the device is operated in an aerosol-emitting mode. For example, the first temperature level and / or heating temperature of a liquid aerosol-generating article or substrate may be lower than the first temperature level of a solid aerosol-generating article or substrate.

[0037] Generally, the second temperature level is selected to maintain the usefulness of the aerosol-generating article for an extended period of time. The second temperature level may also depend on the type and composition of the aerosol-generating article or substrate used with the device. As a result, the second temperature level may be within the range of 175°C to 225°C, specifically 185°C to 215°C, and more specifically 195°C to 205°C. These temperatures may be low enough to minimize substrate depletion during the pause mode, yet high enough to avoid vapor condensation within the device, which could lead to degradation of the aerosol-generating article or substrate.

[0038] To avoid condensation effects in the device, particularly to avoid condensation of substances within the aerosol-generating article or substrate, the second temperature level may be at least 150 degrees Celsius, particularly at least 175 degrees Celsius, preferably at least 185 degrees Celsius, and more preferably at least 195 degrees Celsius.

[0039] Conversely, to minimize depletion of the substrate or article during the pause mode, the second temperature level may be at most 220 degrees Celsius, specifically at most 225 degrees Celsius, preferably at most 215 degrees Celsius, and more preferably at least 205 degrees Celsius. Specifically, the second temperature level may be selected to reduce aerosol formation by at least 50 percent compared to the aerosol emission mode.

[0040] Relatively, the second temperature level may be, for example, at least 50 degrees Celsius, particularly at least 75 degrees Celsius, and more particularly at least 100 degrees Celsius lower than the first temperature level.

[0041] The above temperature values ​​given are preferably the average temperature of the aerosol-generating article or substrate during operation of the device. In addition, as already mentioned, the temperature values ​​may depend, among other things, on the type and composition of the aerosol-generating article or substrate used in the device.

[0042] As used herein, suspended mode may refer to a first operating mode of an aerosol generating device in which the heating element, heating circuit and / or heating arrangement may be operated during a suspended operation of the aerosol generating device, i.e., during a suspended use of the aerosol generating device, i.e., when the user experience or use session is suspended and aerosol generation does not occur or is at least reduced to a minimal level, i.e., in suspended mode, the aerosol generating device is in a suspended state of use.

[0043] Conversely, the aerosol emission mode may refer to a second mode of operation of the heating element, circuitry and / or arrangement, which is the normal heating mode of operation of the aerosol-generating device for aerosol generation, wherein the heating element, heating circuitry and / or heating arrangement may operate during use of the device by a user, i.e., when a user experience or use session occurs, specifically when aerosol generation occurs. Generally, aerosol generation may occur continuously or on demand, specifically on a puff basis, i.e., in response to a user request when taking a puff.

[0044] The density, weight, type, and / or humidity of the aerosol-generating substrate or aerosol-generating article may be detected by the aerosol-generating device, which recognizes, senses, and / or identifies the wand or cartridge, for example, via RFID or other means. These factors may affect the energy required for aerosol generation from the substrate or article, and therefore may affect battery degradation.

[0045] In one example, the usage pattern parameters collected and used to calculate the capacity degradation of the aerosol generating device battery may be selected exclusively from the parameters described above. This applies to all described embodiments of the method, e.g., having at least two, at least three, at least four, or more usage pattern parameters. Other parameters, e.g., parameters related to battery performance such as discharge or charge current rates or voltages, are preferably not used in the method. It is an advantage of the present invention that these parameters may not be required, and that the usage pattern parameters described above may be sufficient, or even superior, for estimating capacity degradation.

[0046] The inventors have found that mathematical functions using usage pattern parameters as input variables can be correlated with battery capacity degradation. In the method according to the present disclosure, usage pattern parameters may be combined in a linear, quadratic, or cubic polynomial to calculate capacity degradation. Thus, combining parameters may mean considering them, for example, as input variables, in a corresponding linear, quadratic, or cubic polynomial to calculate capacity degradation.

[0047] For example, as described in more detail below, high accuracy can be achieved with acceptable computational requirements by fitting a third-order polynomial to the test data. Thus, the usage pattern parameters may be combined in a third-order polynomial to calculate capacity degradation. Combining the usage pattern parameters in a polynomial may mean that the usage pattern parameters are used as variables or input variables of a polynomial function, and each usage pattern parameter may appear at least once in the polynomial. More preferably, each usage pattern parameter may appear at least once as a third-order factor in the polynomial.

[0048] As previously mentioned, calculating the capacity degradation of a battery in an aerosol generating device may include, for example, predicting the battery capacity or battery capacity degradation at a certain time in the future. For example, the methods disclosed herein may be used to predict the battery capacity or battery capacity degradation for a predetermined number of days in the future, such as 30, 90, 180, or 365 days. In this way, a user can replace the battery in a timely manner to avoid limitations on the use of the aerosol generating device.

[0049] To achieve this, the point in time to which the predicted capacity of the battery of the aerosol generating device pertains may be determined by or based on determining the total expected number of usage sessions of the aerosol generating device up to that point in time, which may refer to the total number of usage sessions the device is expected to operate up to that point in time.

[0050] The expected total number of such aerosol generating device use sessions may be calculated, for example, from the usage pattern parameter, the number of use sessions in which the aerosol generating device has operated to generate aerosol per predetermined time interval. Multiplying the value of this parameter by the time until the desired time point provides the expected number of aerosol generating device use sessions from the present to a future time point. For example, if the average amount of use sessions per day is known, this average amount may be multiplied by the number of days to be predicted to obtain the expected number of use sessions until the future time point is reached. The result may then be added to the number of use sessions that have already occurred to obtain the sum of all aerosol generating device use sessions up to the desired time point.

[0051] The expected total number of usage sessions of the aerosol generating device up to that point in time may be used to calculate the predicted capacity of the aerosol generating device's battery. Thus, the model, formula, or function, e.g., a polynomial, used to calculate the capacity degradation of the aerosol generating device's battery can optionally include a usage pattern parameter, such as the number of usage sessions the aerosol generating device has been operated to generate aerosol per predetermined time interval, multiplied by time as a factor. In this manner, meaningful results can be obtained for any point in time that may be of substantial interest. By using the expected total number of usage sessions of the aerosol generating device, battery degradation can be estimated for up to three years in the future. Thus, the method according to the present disclosure can be used to evaluate extended warranty times.

[0052] However, even shorter predicted times may be of practical value. By estimating capacity degradation, it is possible to determine when the battery capacity is expected to fall below a predetermined threshold. Such a threshold may be, for example, the total or relative capacity of the battery. Alternatively, such a threshold may be measured in terms of the number of usage sessions that can be provided by the battery when fully charged.

[0053] For example, the threshold may be defined as the average number of usage sessions that a user utilizes the device between two recharge events of the aerosol generating device or battery.

[0054] The method may optionally include notifying a user of the calculated capacity degradation of the battery, particularly when it is determined that the capacity of the battery falls below a threshold value over a predetermined period of time. The same may apply if it is determined that the capacity degradation of the battery increases above a threshold value over a predetermined period of time. The user may also be notified when the threshold value is reached. The user may then be informed that they should consider replacing the battery or expect a decrease in the availability of the aerosol generating device.

[0055] The notification may be presented to the user on the aerosol-generating device and / or the notification may be presented to the user on a companion device, such as a smartphone. In the latter case, the aerosol-generating device may be designed to have a data connection and / or be communicatively coupled to the companion device, so that notification of the calculated capacity degradation of the battery may be transmitted to and presented on the companion device, even if the data collection and / or calculations are performed on the aerosol-generating device.

[0056] The above-described method may be implemented using a predetermined model for the correlation between usage pattern parameters and battery capacity degradation, represented by a model, equation, or function (i.e., a mathematical function or formula), such as a polynomial, to calculate capacity degradation from the usage pattern parameters. Such a predetermined model, equation, or function may be determined as described in more detail below. It may be used without modification throughout the life of the aerosol generating device. However, it may be desirable for the aerosol generating device to either automatically determine an appropriate equation or function or to modify an existing equation or function, which may be implemented continuously or in an update cycle repeated at predetermined time intervals. The predetermined time interval may be, for example, one week, one month, three months, six months, or more. At this point, the aerosol generating device may collect additional usage pattern parameters, which may then be used to update the equation or function for calculating capacity degradation.

[0057] In one embodiment, the method may further include collecting battery capacity degradation data for an aerosol generating device, preferably a plurality of aerosol generating devices; performing a regression analysis, preferably a nonlinear regression analysis, thereby obtaining a model, equation, and / or function of the correlation between usage pattern parameters and the battery capacity degradation data; and calculating the capacity degradation of the aerosol generating device's battery from the current usage pattern parameters based on the model, equation, and / or function. The battery capacity degradation data may relate to measured capacity degradation occurring in the aerosol generating device's battery. This may be expressed by the total remaining capacity of a fully charged battery or as a percentage of the battery's capacity relative to its initial capacity, nominal capacity, or reference capacity. The battery capacity degradation data may be collected through actual use of the aerosol generating device by a user and necessary measurements. Alternatively, or additionally, the battery capacity degradation data may be collected from an accelerated life test (ALT). Measurement of such battery capacity degradation data is known to those skilled in the art and therefore need not be described in further detail. If a user uses more than one aerosol generating device, it may be advantageous to enable the aerosol generating devices to be at least intermittently communicatively linked so that battery capacity degradation data, and preferably also usage pattern parameters, can be collected from both, and preferably all, of the aerosol generating devices and used in the present method.

[0058] The battery capacity degradation data, and preferably also the usage pattern parameters, may be shared by multiple aerosol generating devices over a network, e.g., the Internet, In this way, a large amount of capacity degradation data, and preferably also the usage pattern parameters, may be provided to increase the accuracy of the method according to the present disclosure.

[0059] Through regression analysis, a model, formula, and / or function for calculating capacity degradation from the usage pattern parameters may be obtained, which may be, for example, a polynomial, preferably a third order polynomial, as already described herein above.

[0060] The model, formula, or function may be obtained and implemented in the device, for example in a control circuit of the aerosol generating device, which may use the current usage pattern parameters to calculate the capacity degradation of the aerosol generating device's battery. The current usage pattern parameters may relate to values ​​of the usage pattern parameters collected after the determination of the formula or function, preferably values ​​that were not used in the determination. From these values, an estimate of the capacity degradation of the aerosol generating device's battery may be calculated.

[0061] For example, the model represented by the determined equation or function may be further refined by establishing one or more probability density functions for the usage pattern parameters from the collected usage pattern parameters and using Monte Carlo simulation to generate additional data for the usage pattern parameters from these density functions. The model may then be validated using such additional data. Once sufficient values ​​for the usage pattern parameters have been collected, a distribution of values ​​for these parameters within the field will become apparent. This may allow the determination of a function, e.g., a probability density function, that describes the distribution.

[0062] Monte Carlo simulation is a method of algorithmically and repeatedly performing random sampling to obtain numerical results. This can then be used to randomly create new values ​​for usage pattern parameters according to their realistic distributions generated from field data. These realistic additional data may then be used to validate models, functions, and / or formulas, for example, by analyzing the sensitivity of each parameter to random variations that cannot be seen using field data alone.

[0063] According to another aspect of the present disclosure, there is provided an aerosol generating device configured to perform the steps of the methods disclosed herein, e.g., at least a subset or all of the method steps. The aerosol generating device preferably includes a battery for storing electrical energy and processing circuitry, also referred to herein as control circuitry, and one or more processors configured to perform the steps of the methods disclosed herein, e.g., at least a subset or all of the method steps. Accordingly, all of the features, effects, and advantages of the methods disclosed herein are valid and equally applicable to the aerosol generating device, and vice versa.

[0064] According to another aspect of the present disclosure, there is provided an aerosol generation system comprising an aerosol generation device and a companion device communicatively coupleable to the aerosol generation device, the companion device configured to perform steps of a method according to the present disclosure herein, e.g., at least a subset or all of the method steps.

[0065] In one embodiment, the companion device may be a smartphone, a tablet computer, a personal computer, a server, or a device configured to charge the aerosol generating device. Accordingly, all of the features, effects, and advantages of the methods or aerosol generating devices according to the present disclosure are valid and equally applicable to the aerosol generating system, and vice versa.

[0066] A further aspect of the present disclosure relates to a computer program which, when executed by an aerosol generating device or an aerosol generating system, instructs the aerosol generating device or system to perform the steps of the methods according to the present disclosure, as described herein above and below.

[0067] A further aspect of the present disclosure relates to a computer-readable medium, e.g., a non-transitory computer-readable medium storing a computer program, which, when executed by an aerosol generating device or an aerosol generating system, instructs the aerosol generating device or system to perform the steps of the methods according to the present disclosure, as described herein above and below. [Example]

[0068] The present invention is defined in the claims. However, below is provided a non-exhaustive list of non-limiting examples. Any one or more of the features of these examples may be combined with any one or more features of any other example, embodiment, or aspect described herein.

[0069] Example A: 1. A computer-implemented method for estimating capacity degradation of a battery of an aerosol generating device, comprising: collecting at least two usage pattern parameters associated with use of the aerosol generating device; and calculating, computing, determining, estimating and / or predicting capacity degradation of a battery of the aerosol generating device based on the at least two usage pattern parameters. Example B: The method of embodiment A, in which the usage pattern parameters are collected over a predetermined period of time. Example C: The method of any one of embodiments A-B, wherein the usage pattern parameter is an average value over a predetermined period of time. Example D: The method of any one of Examples A to C, wherein the usage pattern parameters are indicative of different usage characteristics of the aerosol generating device by users. Example E: The method of any one of Examples A to D, wherein at least one of the usage pattern parameters is indicative of a user's use of the aerosol generating device to generate aerosol in one or more use sessions. Example F: The method of any of embodiments A-E, wherein capacity degradation is calculated as a relative decrease in the capacity of the battery relative to one or more of the initial capacity of the battery, the nominal capacity of the battery, and the reference capacity of the battery. Example G: A method described in any of Examples A to F, wherein at least three, at least four or more usage pattern parameters are collected and used to calculate the capacity degradation of the battery of the aerosol generating device, each usage pattern parameter indicating a different usage characteristic of the aerosol generating device by the user. Example H: The usage pattern parameters are the following parameters: the number of use sessions during which the aerosol generating device is operated to generate aerosols per given time interval; the duration of one or more sessions of use; a pause time between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause time between successive use sessions only changes for pause times between subsequent use sessions of between 0 and 40 minutes; In particular, at least two consecutive use sessions are performed without recharging the aerosol generating device in between. Example I: At least, or exclusively, three usage pattern parameters are collected and used to calculate capacity degradation of the battery of the aerosol generating device, the at least, or exclusively, three usage pattern parameters being the following parameters: the number of use sessions during which the aerosol generating device is operated to generate aerosols per given time interval; the duration of one or more sessions of use; a pause between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause between subsequent use sessions only changes for pauses between subsequent use sessions of between 0 and 40 minutes; The method of any one of embodiments A-H, wherein the frequency is selected from the group consisting of at least two consecutive use sessions without recharging the aerosol generating device in between. Example J: At least or exclusively four usage pattern parameters are collected and used to calculate capacity degradation of a battery of the aerosol generating device, and the at least or exclusively four usage pattern parameters are: the number of use sessions during which the aerosol generating device is operated to generate aerosols per given time interval; the duration of one or more sessions of use; a pause between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause between subsequent use sessions only changes for pauses between subsequent use sessions of 0 to 40 minutes; and The method according to any one of Examples A to I, in particular at least two consecutive use sessions without recharging the aerosol generating device in between. Example K: At least two usage pattern parameters are: the number of use sessions during which the aerosol generating device is operated to generate aerosols per given time interval; the duration of one or more sessions of use; a pause between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause between subsequent use sessions only changes for pauses between subsequent use sessions of between 0 and 40 minutes; - frequency of at least two consecutive use sessions, particularly without recharging the aerosol generator in between; the amount of charge / discharge cycles per given time interval; - the downtime after recharging the aerosol generator; - Rest time with battery charge below 10% Rest time with battery charge greater than 90%; · Smoke intake amount, · Frequency of smoking, Smoking rhythm, the start time of the pause mode in the aerosol generator; the end time of the pause mode of the aerosol generator; the duration of the pause mode in the aerosol generating device; ambient temperature during one or more sessions of use; the temperature of the heating element or heater unit of the aerosol-generating device during a predetermined period before the start of a use session; Ambient temperature while recharging the battery, the density of the aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; the weight of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device to generate the aerosol; The type of aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; and the humidity of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device. Example L: The method of any one of embodiments A-K, wherein the usage pattern parameters are combined in a first order, second order, or third order polynomial to calculate capacity degradation. Example M: The method of any one of embodiments A-L, wherein the usage pattern parameters are combined in a third order polynomial to calculate capacity degradation. Example N: The method of any one of embodiments A-M, wherein calculating the capacity degradation of the battery of the aerosol generating device comprises predicting the capacity of the battery for a point in time. Example 0: The method of claim N, wherein the time point at which the predicted capacity of the battery of the aerosol generating device is relevant is determined by the expected total number of usage sessions of the aerosol generating device up to that time point. Example P: The method of example O, wherein the expected total number of usage sessions of the aerosol generating device to date is used to calculate the expected capacity of the battery of the aerosol generating device. Example Q: The method of any one of embodiments AP, including notifying a user of the calculated capacity degradation of the battery. Example R: collecting battery capacity degradation data for an aerosol generating device, preferably a plurality of aerosol generating devices; performing a regression analysis, preferably a non-linear regression analysis, to obtain a model of the correlation between the usage pattern parameters and the battery capacity degradation data; The method of any of Examples A-Q, further comprising: calculating capacity degradation of the battery of the aerosol generating device from current usage pattern parameters based on the model. Example S: The method of example R, wherein one or more probability density functions for the usage pattern parameters are established from the collected usage pattern parameters, Monte Carlo simulation is used to generate further data for the usage pattern parameters from these density functions, and the model is validated using said further data. Example Sa: The method of any one of embodiments AS, the method further comprising performing a function based on capacity degradation. Example Sb: The method of example embodiment Sa, in which the function includes generating an output signal indicative of capacitance degradation. Example Sc: The method of any one of claims Sa and Sb, wherein the function includes generating an output signal indicating the number of use sessions available to be performed by the aerosol generating device, the number of available use sessions being based on capacity degradation. Example Sd: The method of embodiment Sc, wherein the number of usage sessions available based on capacity degradation is less than the number of available usage sessions corresponding to one or more of the initial capacity of the battery, the nominal capacity of the battery, and the reference capacity of the battery. Example Se: The method of any one of embodiments Sa-Sd, wherein the function includes generating an output signal prompting a user to replace the battery. Example Sf: The method of any one of embodiments Sb-Se, wherein the output signal is communicated via a user interface output element of the aerosol generating device, a device configured to charge the aerosol generating device, and / or an external computing device. Example T: An aerosol generating device configured to carry out the steps of the method according to any one of embodiments A-Sf. Example U: a battery for storing electrical energy; An aerosol generating device as described in any one of embodiments A to S, comprising: a processing circuit having one or more processors configured to perform the steps of the method described in any one of embodiments A to S. Example V: An aerosol generation system comprising an aerosol generating device and a companion device communicatively coupleable to the aerosol generating device, the companion device configured to perform the steps of the method described in any one of Examples A to S. Example W: The aerosol generating system of Example V, wherein the companion device is a smartphone, tablet computer, personal computer, server, or device configured to charge the aerosol generating device. Example X: A computer program that, when executed by an aerosol generating device or aerosol generating system, instructs the aerosol generating device or system to perform the steps of the method according to any one of Examples A to S. Example Y: A non-transitory computer-readable medium storing a computer program according to Example X.

[0070] The embodiments will now be further described with reference to the figures. [Brief explanation of the drawings]

[0071] [Figure 1] FIG. 1 shows an aerosol generation system comprising an aerosol generating apparatus and a companion device. [Figure 2] FIG. 2 shows a probability density function of the usage pattern parameter amount of charge / discharge cycles per given time interval. [Figure 3] FIG. 3 shows the probability density function for the usage pattern parameter duration of a usage session. [Figure 4] FIG. 4 shows the probability density function of the usage pattern parameter pause time between successive usage sessions. [Figure 5] FIG. 5 shows a flow chart of the method. DETAILED DESCRIPTION OF THE INVENTION

[0072] These drawings are schematic only and are not to scale.

[0073] 1 shows an aerosol generation system 1 for generating an aerosol, for example, for consumption by a user in one or more use sessions. System 1 may include an aerosol generation device 2 for generating the aerosol, and a companion device 3 for at least partially receiving aerosol generation device 2. Companion device 3 may be a charging device for charging aerosol generation device 2 and / or its energy storage or battery.

[0074] The aerosol-generating device 2 may include an insertion opening 4 for at least partially inserting an aerosol-generating article 17. The aerosol-generating article 17 may include an aerosol-forming substrate, such as a tobacco-containing substrate, and / or a cartridge containing a liquid.

[0075] The aerosol-generating device 2 may further include a processing circuit 5 or control circuit 5 having one or more processors 6. To generate aerosol during use or consumption of the aerosol-generating article 17, the aerosol-generating device 2 may include at least one heating element 7 or heater device for heating at least a portion of the aerosol-generating article 17. The processing circuit 5 may be configured to control the activation, activation, and / or deactivation of the at least one heating element 7. The processing circuit 5 may further be configured to perform steps of the methods described herein.

[0076] In order to power the at least one heating element 7, the aerosol generation device 2 may further include at least one energy storage unit for storing electrical energy or power, for example in the form of a battery 15. The aerosol generation device 2 may further include at least one electrical connector 12 for connecting to at least one corresponding electrical connector 13 of the companion device 3. For example, when the aerosol generation device 2 is at least partially inserted into the opening 14 of the companion device 3, the one or more electrical connectors 12 of the aerosol generation device 2 may be connected to the one or more electrical connectors 13 of the companion device 3 to charge the at least one battery 15 of the aerosol generation device 2.

[0077] The aerosol generating device 2 may further include a user interface component including an input element, for example in the form of a push button 8. The push button 8 may be used 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 operation of the aerosol generating device 2, the heating element 7 may be activated, thereby applying heat to at least a portion of the aerosol-generating article 17, thereby generating an aerosol for consumption by a user, for example, in a use session.

[0078] The aerosol generating device 2 may further comprise a communication arrangement 9 or communication circuitry 9 having one or more communication interfaces 108 for communicatively linking the aerosol generating device 2 to the companion device 3, for example via an Internet connection, a wireless LAN connection, a WiFi connection, a Bluetooth connection, a cellular network, a 3G / 4G / 5G connection, an edge connection, an LTE connection, a BUS connection, a wireless connection, a wired connection, a radio connection, a short-range connection, and / or an IoT connection.

[0079] The aerosol generating device 2 may further comprise a data storage 11 for storing information or data such as collected usage pattern parameters, battery degradation data, and / or one or more mathematical functions or formulas, for example, for calculating battery capacity degradation.

[0080] As described in detail herein above and below, the aerosol generation device 2 is configured to collect, collect, and / or store at least two usage pattern parameters related to use of the aerosol generation device 2. Additionally, the aerosol generation device 2, e.g., the processing or control circuitry 5, is configured to calculate capacity degradation of the battery 15 of the aerosol generation device 2 based on the at least two usage pattern parameters.

[0081] One or more sensors 16 may be disposed on, at, or within the aerosol generation device 2 to collect data such as usage pattern parameters and / or battery degradation data.

[0082] The aerosol generating device 2 and the companion device 3 may each be provided with a user interface that includes one or more output elements, such as LEDs, for outputting signals to a user.

[0083] 2, 3 and 4 show exemplary probability density functions for selected usage pattern parameters.

[0084] Specifically, FIG. 2 shows a probability density function for the usage pattern parameter number of charge / discharge cycles per predetermined time interval, in this case, per day. The number n of charge / discharge cycles per day is shown on the abscissa (or "horizontal axis"), and the probability percentage for each number n is shown on the ordinate (or "vertical axis"). The distribution reaches its highest probability at approximately eight charge / discharge cycles per day. If a user recharges the aerosol generating device 2 after each use session, the number n of charge / discharge cycles per predetermined time interval, in this case, the number of charge / discharge cycles per day, is equal to the number of use pattern parameters for use sessions in which the aerosol generating device is operated to generate aerosol per predetermined time interval (in this case, per day). Also, in this case, the frequency of a further usage pattern parameter, specifically, at least two consecutive use sessions without recharging the aerosol generating device, is zero, which may alternatively be referred to as a back-to-back regime. Such a usage pattern with a back-to-back regime of zero is used in the following calculation examples.

[0085] 3 shows a probability density function for the use pattern parameter duration of a use session. The duration t1, in minutes, that a use session lasts is plotted on the abscissa (or "horizontal axis"), and the probability percentage for each duration is plotted on the ordinate (or "vertical axis"). Aerosol-generating devices 2 are typically designed to automatically terminate a use session after 6 minutes or 14 puffs, whichever comes first, and therefore, use sessions longer than 6 minutes are not recorded.

[0086] FIG. 4 shows the probability density function for the usage pattern parameter rest time between successive usage sessions. The rest time t2 in minutes is shown on the abscissa (or “horizontal axis”), and the probability percentage for each rest time is shown on the ordinate (or “vertical axis”). The effect of rest time on battery degradation is due to cooling of the aerosol generating device 2 between usage sessions. The longer the rest time, the closer the aerosol generating device 2 is to ambient temperature. It has been found that after approximately 40 minutes of rest time, the aerosol generating device 2 reaches ambient temperature, and rest times longer than 40 minutes have the same effect on battery degradation as a 40-minute rest time. This can be reflected in the calculation of estimated battery degradation by only varying the value of the usage pattern parameter rest time between successive usage sessions for rest times from 0 to 40 minutes, and keeping the value constant for rest times longer than 40 minutes.

[0087] 5 shows a flowchart of a method 18 of the present disclosure according to an exemplary implementation. Using a respective predetermined model or formula or function, the method 18 may only include step 19 of collecting at least two usage pattern parameters, the values ​​of which are determined during operation of the device 2, and step 20 of calculating the capacity degradation of the battery 15 of the aerosol generating device 2 based on these usage pattern parameters. Thus, only steps 19 and 20 are shown in solid boxes, while all other optional steps are shown in dashed boxes.

[0088] As non-limiting examples, usage pattern parameters such as the number of usage sessions operated to generate aerosol per predetermined time interval (P1), the duration of the usage sessions (P2), the rest time between successive usage sessions (P3), and in particular the frequency with which successive usage sessions occur without recharging the aerosol generating device 2 in between (back-to-back regime, P4) are collected. From these usage pattern parameters, the capacity degradation of the battery 15 of the aerosol generating device 2 can be calculated using the following formula:

number

[0089] During the ceremony, cap is the calculated capacity degradation of the battery 15 of the aerosol generator 2, expressed in mAh as the total remaining capacity when fully charged; C0 is the initial battery capacity in mAh, P1 is the number of usage sessions in which the aerosol generating device 2 is operated to generate aerosol per predetermined time interval; P2 is the duration of the usage session in minutes, P3 is the rest time in minutes between successive use sessions, P4 is the frequency of at least two consecutive use sessions without recharging the aerosol generating device 2 in between, k is the time period associated with the estimated capacity degradation of battery 15; C1~C 12 is a unit constant chosen so that each sum in the equation is expressed in mAh.

[0090] In particular, the numerical values ​​of the constants are: C1=-0.0008, C2=0.0003, C3=-0.0074, C4=101.6746, C5=4.807e-12, C6=-6.958e-05, C7=0.0012, C8=-0.0009, C9=0.0405, C 10 =-17.4189, C 11 = -0.0299, and C 12 =318.0644.

[0091] In a non-limiting calculation example, the initial battery capacity C0 is assumed to be 240 mAh, the number of use sessions the aerosol generator 2 is operated to generate aerosol per day P1 is 8, the duration of each use session P2 is 6.5 minutes, the pause between successive use sessions P3 is 7 minutes, and the frequency P4 of at least two consecutive use sessions without recharging the aerosol generator 2 is 0, meaning that the aerosol generator 2 is recharged after each use. Finally, the capacity degradation of the battery 15 after k = 90 days is calculated. Inserting these values ​​into the above-mentioned third-order polynomial equation results in a calculated capacity degradation of approximately 236 mAh for the battery 15 of the aerosol generator 2. This is the total capacity that a fully charged battery 15 will drop from its initial 240 mAh after 90 days of operation under the usage pattern described by the usage pattern parameters entered into the equation. This corresponds to a battery capacity loss of approximately 1.7%.

[0092] Selection of usage pattern parameters, model or formula or function, and constants C1 to C 12 It is important to note that the values ​​of are only exemplary. For example, the duration of usage session P2 may be 6 minutes or 5.5 minutes or another duration.

[0093] For example, they can be determined by regression analysis, as described in more detail below and above. However, the present invention can readily be implemented using a different number and / or selection of different usage pattern parameters, different models or formulas or functions, and / or different values ​​of the constants. While the given example may be a preferred way of implementing the invention, it may be desirable to adjust the calculations, for example, to provide greater accuracy over short-term, medium-term, or long-term time frames, or to place greater importance on usage pattern parameters that fall within a particular numerical range, etc. There may be many possibilities for implementing the present invention, which means that the invention is not strictly limited to the examples given above.

[0094] The model or formula or function used to calculate the capacity degradation of the battery 15 may be predetermined and stored in the aerosol generating device 2, for example in the data storage 11. The collection of usage pattern parameters and the calculation of the capacity degradation of the battery 15 of the aerosol generating device 2 may be performed by the processing circuitry 5 using its at least one processor 6, for example in conjunction with one or more sensors 16.

[0095] After the calculation step 20, the method 18 may include a step 27 in which the user is notified of the calculated capacity degradation of the battery 15. This notification may be output by the aerosol generating device 2 or the companion device 3, and may only be provided when the calculated capacity degradation of the battery 15 reaches a predetermined threshold. One such threshold may be, for example, a total remaining capacity of 190 mAh for the battery 15. This value may be of interest because this capacity is typically insufficient for two consecutive usage sessions, and values ​​below 190 mAh may be insufficient to provide the user with two usage sessions without recharging.

[0096] Method 18 may also include a step of providing or refining a model, equation, or function used in calculation step 20. To this end, in step 21, battery capacity degradation data representing the degradation of the battery capacity of battery 15 at the time of collection may be collected. This may be done during normal use of the aerosol generating device 2 in the field, or alternatively, the battery capacity degradation data may be collected by employing an accelerated life test (ALT) of the aerosol generating device 2. Step 22 may be performed simultaneously or in parallel, with usage pattern parameters collected from use of the aerosol generating device 2 in the field or from the ALT. From the data collected in steps 21 and 22, a regression analysis, preferably a nonlinear regression analysis, may be performed in step 23. This regression analysis is used to express the correlation between the battery capacity degradation data collected in step 21 and the usage pattern parameters collected in step 22 as a model, equation, or function, preferably a cubic or third-order polynomial. By way of example, the equations described above in the exemplary calculations were determined in this manner. After step 23, when the model or formula or function has been established, method 18 may calculate future battery degradation from the current usage pattern parameters collected in step 19, as described above.

[0097] In another aspect, the present disclosure may provide a method for validating a model, formula, or function, thus showing the effect of variation in each of the variables of the model, formula, or function more clearly than limited field and / or ALT data. To this end, in step 24, a probability density function is established for each of the usage pattern parameters. Examples of such functions for selected parameters are shown in FIGS. 2, 3, and 4. These functions have the advantage over a cloud of single data points and can be used to create a large number of randomly selected values ​​for the usage pattern parameter in question through the random sampling used by Monte Carlo simulation in step 25. The data generated in this manner still follows the distribution of usage pattern parameters observed in the field and / or ALT, and therefore presents a wealth of data that is still realistic for the particular use case. The large data set that can be created in this way can be used to validate the model, formula, or function in step 26. It is also envisioned that the validation in step 26 may result in adjustment or fine-tuning of the model, formula, or function, and that the validated or adjusted model, formula, or function may be used in the calculations according to step 20.

[0098] For purposes of this specification and the appended claims, unless otherwise indicated, all numbers expressing amounts, quantities, percentages, and the like are understood to be modified in all instances by the term "about." Also, all ranges include the disclosed maximum and minimum points, and include any intermediate ranges therein, which may or may not be specifically recited herein. Thus, in this context, the number A is understood as A ± 10% of A. Within this context, the number A can be considered to include a numerical value that is within the typical standard error for measurement of the property that the number A modifies. In some instances, as used in the appended claims, the number A may deviate by the percentages recited above, provided that the amount by which A deviates does not materially affect the basic and novel characteristics of the claimed invention. Also, all ranges include the disclosed maximum and minimum points, and include any intermediate ranges therein, which may or may not be specifically recited herein.

Claims

1. 1. A computer-implemented method for estimating capacity degradation of a battery of an aerosol generating device, comprising: collecting at least two usage pattern parameters associated with use of the aerosol generating device; calculating a capacity degradation of the battery of the aerosol generating device based on the at least two usage pattern parameters; A method comprising:

2. The method of claim 1 , wherein the usage pattern parameters are collected over a predetermined period of time and / or are average values ​​over a predetermined period of time.

3. 3. The method of claim 1, wherein at least one of the usage pattern parameters is indicative of a user's use of the aerosol generating device to generate aerosol in one or more use sessions.

4. A method according to any one of claims 1 to 3, wherein at least three, at least four or more usage pattern parameters are collected and used to calculate the capacity degradation of the battery of the aerosol generating device, each of the usage pattern parameters indicating different usage characteristics of the aerosol generating device by the user.

5. The usage pattern parameters include the following parameters: the number of use sessions during which the aerosol generating device is operated to generate aerosol per predetermined time interval; - the duration of one or more sessions of use; a pause time between successive use sessions, preferably such that the usage pattern parameter value associated with said pause time between successive use sessions only changes for pause times between subsequent use sessions of between 0 and 40 minutes; In particular, the frequency of at least two consecutive use sessions without recharging the aerosol generating device in between; The method according to any one of claims 1 to 4, wherein the compound is selected from the group consisting of:

6. At least or exclusively three usage pattern parameters are collected and used to calculate the capacity degradation of the battery of the aerosol generating device, the at least or exclusively three usage pattern parameters being the following parameters: the number of use sessions during which the aerosol generating device is operated to generate aerosol per predetermined time interval; - the duration of one or more sessions of use; a pause time between successive use sessions, preferably wherein the usage pattern parameter value associated with the pause time between subsequent use sessions only changes for pause times between subsequent use sessions of 0 to 40 minutes; - frequency of at least two consecutive use sessions, in particular without recharging the aerosol generating device in between; The method according to any one of claims 1 to 5, wherein the compound is selected from the group consisting of:

7. At least or exclusively four usage pattern parameters are collected and used to calculate the capacity degradation of the battery of the aerosol generating device, the at least or exclusively four usage pattern parameters comprising: the number of use sessions during which the aerosol generating device is operated to generate aerosol per predetermined time interval; - the duration of one or more sessions of use; a pause time between successive use sessions, preferably such that the usage pattern parameter value associated with the pause time between subsequent use sessions only changes for pause times between subsequent use sessions of 0 to 40 minutes; and - frequency of at least two consecutive use sessions, in particular without recharging the aerosol generating device in between; The method according to any one of claims 1 to 6, wherein

8. The at least two usage pattern parameters are: the number of use sessions during which the aerosol generating device is operated to generate aerosol per predetermined time interval; - the duration of one or more sessions of use; a rest time between successive use sessions, preferably wherein the usage pattern parameter value relating to the rest time between subsequent use sessions only changes for rest times between subsequent use sessions of 0 to 40 minutes; - frequency of at least two consecutive use sessions, in particular without recharging the aerosol generating device in between; the amount of charge / discharge cycles per given time interval; - the downtime after recharging the aerosol generating device; - Rest time with battery charge less than 10%; - Rest time with battery charge greater than 90%; ・Amount of smoke absorbed, ・Smoking frequency, Smoking rhythm, - the start time of a pause mode in the aerosol generating device; - the end time of the pause mode of the aerosol generating device; - the duration of the pause mode in the aerosol generating device; - ambient temperature during one or more sessions of use; the temperature of the heating element or heater device of the aerosol generating device within a predetermined period of time prior to the start of a session of use; - ambient temperature during recharging of said battery; the density of the aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; the weight of the aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; the type of aerosol-generating substrate or article used in the aerosol-generating device to generate the aerosol; and the humidity of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device; The method according to any one of claims 1 to 7, wherein the compound is selected from the group consisting of:

9. The method of any of claims 1 to 8, wherein the usage pattern parameters are combined in a first or second or third order polynomial to calculate the capacity degradation.

10. The method of any preceding claim, wherein the usage pattern parameters are combined in a third order polynomial to calculate the capacity degradation.

11. The method of any preceding claim, wherein calculating the capacity degradation of the battery of the aerosol generating device comprises predicting the capacity of the battery for a point in time.

12. The method of claim 11, wherein the time point to which the predicted capacity of the battery of the aerosol generating device relates is determined by the expected total number of usage sessions of the aerosol generating device up to the time point, and preferably the expected total number of usage sessions of the aerosol generating device up to the time point is used to calculate the predicted capacity of the battery of the aerosol generating device.

13. The method of any preceding claim, comprising notifying a user of the calculated capacity degradation of the battery.

14. An aerosol generating device configured to carry out the steps of the method according to any one of claims 1 to 13.

15. 14. An aerosol generation system comprising an aerosol generating device and a companion device communicatively coupleable to the aerosol generating device, the companion device configured to perform the steps of the method of any one of claims 1 to 13.

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