Estimating battery attenuation in aerosol-generating device

Abstract

A computer-implemented method of estimating capacity fade of a battery of an aerosol-generating device, the method comprising: collecting at least two usage pattern parameters relating to usage of the aerosol-generating device; and calculating a capacity fade of a 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 fade of a battery of an aerosol-generating device. The present disclosure also relates to an aerosol-generating device and an aerosol-generating system configured to perform this method. Furthermore, the present disclosure relates to corresponding computer programs and to corresponding non-transitory computer-readable media storing one or more of such computer programs. Background Art

[0002] Typically, an aerosol-generating device is designed as a handheld device that can be used by a user to consume or experience an aerosol generated by heating an aerosol-generating substrate or an aerosol-generating article, for example, during one or more use sessions. The aerosol-generating devices to which the present disclosure relates are generally referred to as heated tobacco products (HTPs), heat-not-burn devices, electronic cigarettes, and / or vaporizers.

[0003] An exemplary aerosol-generating substrate may include a solid substrate material, such as a tobacco material or a tobacco cast leaf (TCL) material. The substrate material may, for example, typically be assembled with other elements or components to form a substantially rod-shaped aerosol-generating article. The shape and size of such a rod or aerosol-generating article may be configured to be at least partially inserted into an aerosol-generating device. An aerosol-generating system may include 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 in addition, the aerosol-generating substrate may include one or more liquids and / or solids, which may be supplied to the aerosol-generating device, for example, in the form of a cartridge or container. A corresponding exemplary aerosol-generating article may, for example, include a cartridge containing or capable of being filled with a liquid and / or solid substrate, which may be evaporated during a user's consumption of the aerosol based on the heated substrate and / or liquid. Typically, such a cartridge or container may be coupled to, attached to, or at least partially inserted into an aerosol-generating device. Alternatively, the cartridge may be fixedly mounted to the aerosol generating device and refilled by inserting liquids and / or solids into the cartridge.

[0004] In order to generate an aerosol during use or consumption, heat may be supplied by a heating element, heater means or heat source to heat at least a portion or part of the aerosol-generating substrate. The heating element, heater means or heat source may be arranged in the handheld device or the handheld part of the aerosol-generating device. Alternatively or in addition, at least a portion or the entire heating element or heater means or heat source may be fixedly associated with the aerosol-generating article or arranged within the aerosol-generating article, for example in the form of a rod or cartridge that is attachable to and / or powered by the handheld device or the handheld part of the aerosol-generating device.

[0005] Exemplary heating elements or heater devices can be based on one or more of resistive heating, inductive heating, and microwave heating, which use electrical energy supplied via, drawn from, or stored in a battery of the aerosol generating device. As used herein, a battery of an aerosol generating device may generally refer to an energy storage device of the aerosol generating device, the energy storage device being 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 devices. Additionally, any reference to a battery herein may include a plurality of batteries.

[0006] Typically, the aerosol-generating device includes a battery that provides the electrical energy required to operate the aerosol-generating device, and in particular for heating the aerosol-generating substrate and / or article, for example to generate an aerosol during one or more uses using one or more aerosol-generating articles. For example, the battery may be a lithium-ion battery.

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

[0008] The battery capacity is typically selected so that the aerosol-generating device can provide the user with at least a minimum number, for example, at least two or more, of consecutive use sessions or experiences without having to recharge the battery or aerosol-generating device in between. To improve the user experience, aerosol-generating devices are typically designed to only allow the user to initiate a use session if the battery contains sufficient electrical energy to fully complete the use session. However, battery capacity may decay over time as charge / discharge cycles accumulate. The rate and extent or breadth of battery capacity decay can be variable and depend on many different factors, which can make estimating or determining battery degradation difficult. However, it may be advantageous to know in advance when the battery capacity of an aerosol-generating device will decay so much that it can no longer provide the minimum number of consecutive use sessions without having to recharge the battery or aerosol-generating device. In this case, a user interface signal can be used to advise the user to replace the battery promptly to avoid encountering any limitations in using the aerosol-generating device. Additionally or alternatively, the device may be configured to output a signal indicating that the number of consecutive use sessions or experiences without having to recharge the battery or aerosol-generating device has decreased.

[0009] Conventional models for battery degradation often involve detailed information about the specific build or design of the battery, which may not be available to the manufacturer of the aerosol-generating device. They may also lack predictive accuracy for batteries in aerosol-generating devices, as battery capacity degradation may be strongly affected by the actual operation of the aerosol-generating device. For example, temperature or heating cycles may be common in aerosol-generating devices but may be atypical in other applications. In addition, different users may have different habits or patterns when using their aerosol-generating devices, with, in particular, continuous use with intermittent rest before recharging, variable rest times, and varying durations of use being accounted for in conventional battery degradation models, which may, however, result in insufficient accuracy for battery degradation estimates in aerosol-generating devices. Summary of the Invention

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

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

[0012] According to aspects of the present disclosure, there is provided a computer-implemented method for estimating and / or determining capacity fade of a battery of an aerosol-generating device, the method comprising: collecting at least two usage pattern parameters related to usage of the aerosol-generating device; and calculating the capacity fade of the battery of the aerosol-generating device based on the at least two usage pattern parameters.

[0013] In other words, capacity fade of a battery of an aerosol-generating device may generally refer to a decrease in the capacity of the battery, which may be directly determined based on usage pattern parameters related to the use or operation of the aerosol-generating device itself. Thus, the estimated or determined capacity fade may reflect or include the actual operation of the aerosol-generating device and may therefore be accurate, particularly when compared to conventional models of battery fade that focus solely on the characteristics of the battery. Furthermore, it may therefore be unnecessary to employ conventional models of battery fade, which may not be appropriate for a particular use case of the aerosol-generating device.

[0014] The aerosol-generating device may be designed or configured to collect usage pattern parameters during its operation, which may ensure that the collected usage pattern parameters are relevant to the actual individual user of the aerosol-generating device. In this way, the predicted capacity fade of the battery of the aerosol-generating device calculated based on these usage pattern parameters may be tailored to the individual habits or usage patterns of the user. It should be noted that, for simplicity, usage pattern parameters may also be referred to as "parameters" hereinafter.

[0015] As explained in more detail below, as used herein, the calculated capacity decay of a battery of an aerosol generating device may relate to a point in time in the future, for example, relating to the decay of the battery after a predetermined time period. Thus, the calculated capacity decay may refer to an estimated and / or predicted capacity decay. Alternatively or in addition, calculating the capacity decay may include estimating and / or predicting the capacity decay, for example, at a point in time in the future and / or after a predetermined time period. Predicting capacity decay may allow for providing an early warning to a user of the aerosol generating device, for example, if the decay of the battery will reach a certain level after a predetermined time period has elapsed. The user may then promptly replace the battery to avoid limitations in using the aerosol generating device, which may improve the overall user experience.

[0016] The usage pattern parameters may be collected over a predetermined time period. The predetermined time period may be, for example, a fixed number of hours, days, weeks or months after the aerosol generating device is used for the first time. Alternatively, the predetermined time period may be the entire time since the aerosol generating device was first used. Optionally, the aerosol generating device may be designed or configured to collect usage pattern parameters, preferably automatically and / or continuously. Collecting usage pattern parameters may comprise, for example, storing corresponding data indicative of one or more usage pattern parameters in a data storage device of the aerosol generating device or another device communicatively coupled thereto. Alternatively or in addition, 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 may comprise, for example, counters and / or timers and / or sensors, such as temperature sensors, volume sensors, humidity sensors and others.

[0017] In an example, usage pattern parameters may be collected over the life of the aerosol-generating device, which may mean from the first use of the aerosol-generating device to the last use of the aerosol-generating device. The aerosol-generating device may preferably include a storage device 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 transmitted to another aerosol-generating device or other device communicatively coupled to the aerosol-generating device.

[0018] In an example, the usage pattern parameter may be a mean value over a predetermined time period. In other words, the aerosol generating device may be designed or configured to calculate a mean value from at least two, and preferably all, individual values of a particular collected usage pattern parameter. Thus, for each collected usage parameter, a mean value may be calculated over a predetermined time period. The predetermined time period may be, for example, a fixed number of hours, days, weeks, and / or months after the aerosol generating device was first used. Alternatively, the predetermined time period may be, for example, a fixed number of hours, days, weeks, and / or months before the present time, so that, for example, only the most recent values of the usage pattern parameter may be collected and / or used. Alternatively, the predetermined time period may be the entire time since the aerosol generating device was first used. By providing a mean value, particularly a mean value from a usage pattern parameter collected over a longer period of time, future predictions of an individual user's usage pattern may be highly accurate, which in turn may make the estimation of the capacity decay of the battery of the aerosol generating device more reliable.

[0019] A usage mode parameter may indicate different uses and / or operating characteristics of the aerosol generating device by a user. Where the methods described herein relate to more than one usage mode parameter, for example at least two usage mode parameters, these usage mode parameters may be different from one another. Thus, each parameter may be one of the parameters listed further below, wherein each parameter may be different from the other parameters. In particular, it should be noted that two usage mode parameters as used herein may not describe or refer to different values (e.g. numerical values) of the same parameter, but rather to values of different parameters. For example, a usage mode parameter may relate to a parameter that describes or relates to a user's use or operation of the aerosol generating device (specifically the manner and / or frequency and / or time and / or length of time and / or state in which the user uses or operates and / or has used or operated the aerosol generating device). A usage mode parameter may relate to or relate to one or both of a use of the aerosol generating device and the time between uses (e.g. a rest period or a recharging event for the aerosol generating device). Thus, the usage pattern parameters described herein can characterize the different preferences and / or habits of each individual user, which can vary between users and may have an impact on the rate and / or extent of battery capacity degradation. By using the usage pattern parameters described herein when estimating the degradation, a highly accurate prediction customized for the individual user can be achieved.

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

[0021] Capacity decay can be calculated as the relative decrease in the capacity of a 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. The capacity decay of a battery of an aerosol generating device can be a measure of how much electrical energy and / or the amount of electrical energy the battery can store at a specific point in time. For example, this can be an absolute value expressed as ampere hours or a similar unit of measurement. Capacity decay can also be expressed as a comparison to the original, initial or nominal battery capacity or a reference capacity, for example as a percentage. Capacity decay can also be expressed in other units, for example expressing the capacity decay as the total number of uses that are possible or permissible for a user on a single full charge of the battery. These other units can also be expressed as a comparison to an initial value or a reference value, for example as a percentage.

[0022] While a meaningful estimate of battery degradation can be achieved using at least two usage pattern parameters, the accuracy of the estimate can be increased when more usage pattern parameters are used in combination. In examples, at least three, at least four, or more usage pattern parameters can be collected and used to calculate and / or predict capacity fade of a battery of an aerosol-generating device, wherein each of the usage pattern parameters can optionally indicate a different characteristic of a user's use of the aerosol-generating device.

[0023] As will be explained further below, a variety of different parameters may be advantageously used in the context of the present disclosure to estimate battery capacity fade. However, the inventors have identified four parameters that may be particularly useful for easily and reliably estimating the capacity fade of a battery of an aerosol generating device. Thus, in an example, the usage mode parameter may be selected from the following parameters or parameter groups:

[0024] the number of usage sessions during which the aerosol generating device has been operated to generate aerosol per predefined time interval (e.g. per day),

[0025] the duration of one or more sessions of use,

[0026] a rest period between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest period between consecutive use sessions is changed only for a rest period of 0 to 40 minutes between subsequent use sessions,

[0027] • A frequency of at least two usage sessions in succession, in particular without recharging the aerosol generating device in between. A frequency of at least two usage sessions in succession may also be referred to as a back-to-back regime.

[0028] The number of usage sessions of an aerosol-generating device may be a relevant parameter as it may characterize the intensity with which the user uses the device. It may therefore allow light users to be distinguished from heavy users and may be used to describe the progression over the useful life of the device and / or battery.

[0029] The duration of one or more usage sessions may vary from user to user and have an impact on the strain on the battery. The amount of energy required within a usage session may be highly correlated with its duration, as the aerosol generating device should preferably maintain a heated temperature during this period. The inventors have found that longer durations of usage sessions are associated with faster battery capacity decay.

[0030] The rest period between consecutive uses may be related to the temperature of the device, the temperature of the device's heating element, and the temperature of the battery. During the use process, the heating element, the device, and the battery may be heated by heating the aerosol-generating substrate or article. After the use process, the device and the battery begin to cool down. After about 40 minutes, the battery typically reaches ambient temperature, which may mean that different rest periods of 40 minutes or longer may have the same effect from a temperature perspective. For this reason, optionally, a rest period between only 0 minutes and 40 minutes may produce different values for the corresponding use mode parameter, while 40 minutes and longer times may have the same value. A short rest period that is insufficient for the device to reach ambient temperature may be less stressful for the battery and therefore result in less battery degradation.

[0031] The frequency of at least two consecutive sessions of use, particularly without recharging the aerosol generating device or battery, may also be referred to as a back-to-back regimen. This parameter may, for example, be described by the percentage of two consecutive sessions of use that occurred without the aerosol generating device or battery being recharged before initiating a second session of use. For example, in an aerosol generating device designed or configured to provide two sessions of use after fully charging the battery, recharging the aerosol generating device after each session would result in a 0% back-to-back regimen, while recharging the device only after two sessions of use would result in a 100% back-to-back regimen. A 50% back-to-back regimen would then describe a situation where half the time the device is recharged after one session of use and the remaining half the time the device is recharged only after two sessions of use. Generally, the frequency of at least two consecutive sessions of use can be determined by dividing the number of consecutive sessions of use by the total number of sessions of use.

[0032] The method of the present disclosure may comprise collecting at least two, or at least three, or at least four usage pattern parameters selected from the parameters listed above, and using them to calculate, determine, estimate, approximate, and / or predict the capacity fade of the battery of the aerosol-generating device. Alternatively, the method of the present disclosure may comprise collecting only two, or only three, or only four usage pattern parameters selected from the parameters listed above, and using them to calculate the capacity fade of the battery of the aerosol-generating device. Using only a selected set of parameters may simplify the model, data collection, and calculations, which may reduce the need for high computing power and may make the method of the present disclosure easier to implement on a portable device.

[0033] There are many other parameters that may be suitable for the method of the present disclosure, so the present invention is not limited to the parameters mentioned above. In general, at least two and preferably at least three or at least four usage mode parameters may be selected from the following parameters:

[0034] the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval,

[0035] the duration of one or more sessions of use,

[0036] a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions,

[0037] the frequency of at least two consecutive uses, in particular without recharging the aerosol generating device,

[0038] the number of charge-discharge cycles per predefined time interval,

[0039] the rest period after recharging the aerosol generating device,

[0040] The rest time when the battery state of charge (SOC) is less than 10%,

[0041] The rest time when the battery state of charge (SOC) is greater than 90%,

[0042] · Aspiration volume,

[0043] Puffing frequency,

[0044] Suction rhythm,

[0045] the time at which the pause mode is activated at the aerosol generating device,

[0046] the time at which the pause mode is terminated at the aerosol generating device,

[0047] the duration of the pause mode at the aerosol generating device,

[0048] the ambient temperature during one or more periods of use,

[0049] the temperature of the heating element or heater means of the aerosol-generating device during a predefined period of time before the start of a use session,

[0050] ·Ambient temperature during battery recharging,

[0051] the density of the aerosol-generating substrate or aerosol-generating article used with an aerosol-generating device to generate an aerosol,

[0052] the weight of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol,

[0053] the type of aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol, and

[0054] • The humidity of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device.

[0055] The number of charge-discharge cycles may relate to the number of times the aerosol generating device is used or has been used and then recharged every predefined time interval (e.g., daily). The more such cycles, the more degraded the battery may be, making this parameter a suitable candidate for use in the methods of the present disclosure.

[0056] A puff, as defined herein, may describe a puff and / or draw on an aerosol generating device as a user inhales a mixture of air and aerosol. Puff volume may describe the volume of the mixture inhaled in a single puff or inhalation. Puff frequency and rhythm may describe the corresponding pattern of puff characteristics occurring for an individual user.

[0057] The pause mode may refer to a special mode of the aerosol generating device that allows for a pause during a use session.Thus, the pause mode may not relate to a rest time between use sessions and may be different from a rest time between use sessions.

[0058] The aerosol generating device can operate in at least two operating modes, namely an aerosol release mode and a 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 or at a plurality of different temperatures above the first temperature level or within a first temperature range in the aerosol release mode. Wherein, the temperature at the first temperature level and / or within the first temperature range can correspond to a predetermined heating temperature or a temperature above it, which can be sufficient to generate an aerosol. The aerosol generating device can also 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 and / or at a temperature within the first temperature range 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 and / or a temperature within the first temperature range.

[0059] The user experience (also referred to herein as the process of using or experiencing the aerosol-generating article) may be interrupted (e.g., by switching the device to a pause mode) and later resumed by the user, wherein the aerosol-generating article or substrate may be maintained in the pause mode of the aerosol-generating device at a temperature that is 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 process of use), but still higher than or significantly higher than room temperature. That is, preferably the second temperature level may be selected, for example, to avoid degradation of unconsumed substrate or aerosol-generating article. In particular, the second temperature level may be selected, for example, to be low enough to minimize consumption of the substrate or article during the pause mode, while being high enough to avoid condensation of vapor in the device, which may otherwise affect the quality of the unconsumed aerosol-generating substrate or article.

[0060] During use of the device, in particular when a user experience or use process is about to take place, the aerosol generating device may be operated in an aerosol release mode, and during pauses in use of the device, i.e. when no user experience or use process is taking place and / or when the use process is interrupted by a pause, the aerosol generating device may be operated in a pause mode. In both the aerosol release mode and the pause mode of the aerosol generating device, the heating element, the heating circuit system and / or the heating device may be in operation, in particular in heating operation, but at different temperature levels, i.e. at a first temperature level during the aerosol release mode that may be selected to be sufficiently high to generate an aerosol, and at a second temperature level, lower than the first temperature level, during the pause mode, the second temperature level being selected to be sufficiently low to minimize consumption of the substrate while avoiding degradation.

[0061] Depending on the type and composition of the specific aerosol-generating article or substrate to be used with the device, the first temperature level may be between 200 and 500 degrees Celsius, particularly between 250 and 450 degrees Celsius, particularly between 270 and 430 degrees Celsius, more particularly between 315 and 355 degrees Celsius, or within the range of 240 and 280 degrees Celsius. 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 processes and / or when the device is operated in an aerosol release 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.

[0062] In general, the second temperature level can be selected to maintain the usability of the aerosol-generating article or substrate 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 to be used with the device. Thus, the second temperature level may be in the range of between 175 degrees Celsius and 225 degrees Celsius, particularly between 185 degrees Celsius and 215 degrees Celsius, and more particularly between 195 degrees Celsius and 205 degrees Celsius. These temperatures may be low enough to minimize consumption of the substrate during pause mode, but high enough to avoid condensation of vapor in the device, which could lead to degradation of the aerosol-generating article or substrate.

[0063] In order to avoid condensation effects in the device, in particular to avoid condensation of substances in the aerosol-generating article or substrate, the second temperature level may 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.

[0064] Conversely, in order to minimize consumption of the substrate or product during the pause mode, the second temperature level may 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 may be selected to reduce aerosol formation by at least 50%, for example, compared to the aerosol release mode.

[0065] Relatively speaking, the second temperature level may be, for example, at least 50 degrees Celsius lower, particularly at least 75 degrees Celsius lower, more particularly at least 100 degrees Celsius lower than the first temperature level.

[0066] The temperature values given above may 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 may depend inter alia on the type and composition of the aerosol-generating article or substrate to be used with the device.

[0067] As used herein, pause mode may refer to a first operating mode of the aerosol generating device, in which the heating element, heating circuitry and / or heating device may be operated during a pause in operation (i.e. a pause in use of the aerosol generating device), i.e. when the user experience or use process is paused and aerosol generation may not occur or may at least be reduced to a minimal level. That is, in pause mode, the aerosol generating device is in a pause in use.

[0068] Conversely, the aerosol release mode may refer to a second operating mode of the aerosol generating device, which is a normal heating operating mode of the heating element, circuit system and / or device for aerosol generation, in which the heating element, heating circuit system and / or heating device may operate during use of the device by a user (i.e., when a user experience or use process occurs, in particular, when aerosol generation occurs). In general, aerosol generation may occur continuously, or on demand (in particular, based on a puff), i.e., on demand when a user takes a puff.

[0069] The density, weight, type and / or humidity of the aerosol-generating substrate or aerosol-generating article can be detected by the aerosol-generating device recognition, sensing and / or identification wand or cartridge (e.g., by RFID or other means). Since these factors may affect the energy required to generate an aerosol from the substrate or article, they may also affect battery degradation.

[0070] In an example, the usage pattern parameters collected and used to calculate the capacity fade of the battery of the aerosol-generating device can be selected exclusively from the parameters described above. This applies to all described embodiments of the method, e.g., with at least two, at least three, at least four, or more usage pattern parameters. Preferably, no other parameters are used in the method, e.g., parameters related to the performance of the battery, such as discharge current rate or charge current rate or voltage. One of the advantages of the present invention is that these parameters may not be required, and the mentioned usage pattern parameters may be sufficient for the estimation of capacity fade, or even better.

[0071] The inventors have discovered that mathematical functions that use usage pattern parameters as input variables can be correlated with battery capacity fade. In the methods according to the present disclosure, usage pattern parameters can be combined linearly or as quadratic or cubic polynomials to calculate capacity fade. Combining these parameters can mean, for example, treating them as input variables in corresponding linear, quadratic, or cubic polynomials to calculate capacity fade.

[0072] For example, a high degree of accuracy with acceptable computational requirements can be achieved by fitting a third-order polynomial to the test data, as explained in further detail below. Thus, the usage pattern parameters can be combined as a cubic or third-order polynomial to calculate capacity fade. Combining the usage pattern parameters as a polynomial can mean that the usage pattern parameters are used as variables or input variables in a polynomial function, where each usage pattern parameter can appear at least once in the polynomial. It is also preferred that each usage pattern parameter appear at least once as a third-order factor in the polynomial.

[0073] As already mentioned, calculating the capacity decay of the battery of the aerosol generating device may include predicting the capacity of the battery or the capacity decay of the battery at a certain point in time (e.g., in the future). For example, the method according to the present disclosure can be used to predict the capacity of the battery or the capacity decay of the battery at a certain point in time (e.g., a predetermined number of days in the future, such as 30 days, 90 days, 180 days, or 365 days). In this way, the user can replace the battery in a timely manner to avoid restrictions when using the aerosol generating device.

[0074] To achieve this, the point in time associated with the predicted capacity of the battery of the aerosol-generating device may be determined by, or based on, determining an expected total number of uses of the aerosol-generating device up to that point in time. The expected total number of uses of the aerosol-generating device may refer to the total number of uses that the device is expected to have been operated up to that point in time.

[0075] This expected total number of usage sessions of the aerosol generating device can be calculated, for example, based on a usage pattern parameter (i.e., the number of usage sessions during which the aerosol generating device has been operated to generate aerosol per predefined time interval). By multiplying the value of this parameter by the time until the desired time point, the expected number of usage sessions of the aerosol generating device from now until the future time point can be obtained. For example, when the average number of usage sessions per day is known, the expected number of usage sessions until the future time point can be obtained by multiplying this average number by the number of days for which the prediction is made. In addition, this result can be added to the number of usage sessions that have occurred to obtain the total number of all usage sessions of the aerosol generating device until the desired time point.

[0076] The expected total number of uses of the aerosol generating device up to that point in time can be used to calculate the predicted capacity of the battery of the aerosol generating device. Thus, a model, formula, or function (e.g., a polynomial) for calculating the capacity decay of the battery of the aerosol generating device can optionally include time as a factor that is multiplied by the usage pattern parameter (i.e., the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval). In this way, meaningful results can be obtained for any point in time that may be of practical interest. By using the expected total number of uses of the aerosol generating device, the decay of the battery can be extrapolated up to three years into the future. Thus, the method according to the present disclosure can be used to assess extended warranty times.

[0077] However, even shorter prediction times can be valuable: by estimating capacity fade, it is possible to determine when the expected or projected battery capacity may drop below a predetermined threshold. This threshold could be, for example, the total or relative capacity of the battery. Alternatively, it could be measured in terms of the number of uses the battery could provide when fully charged.

[0078] For example, the threshold may be defined as the average number of usage sessions that a user makes with the device between two recharging events of the aerosol generating device or battery.

[0079] The method may optionally include notifying the user of the calculated capacity decay of the battery, particularly when it is determined that the capacity of the battery will drop below a threshold within a predetermined time period. The same may apply when it is determined that the capacity decay of the battery will increase above a threshold within a predetermined time period. The user may also be notified of the point in time at which the threshold is reached. The user may then be advised that they should consider replacing the battery or anticipate a reduction in the availability of the aerosol generating device.

[0080] 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 be data connected and / or communicatively coupled to the companion device, such that the notification of the calculated capacity fade of the battery may be transmitted to and presented on the companion device even while data collection and / or calculations are being performed on the aerosol generating device.

[0081] The method described above can be implemented using a predetermined model of the correlation between usage pattern parameters and battery capacity fade, the predetermined model being represented by a model, formula or function (i.e., a mathematical function or formula), such as a polynomial, for calculating capacity fade based on the usage pattern parameters. Such a predetermined model, formula or function can be determined as described in more detail below. It can be used without modification throughout the life of the aerosol generating device. However, it may also be desirable for the aerosol generating device to automatically determine a suitable formula or function, or for the aerosol generating device to modify an existing formula or function continuously or in repeated update cycles, which can be implemented with predetermined time intervals between them. The predetermined time intervals may be, for example, one week or one month or three months or six months or longer. In this time, the aerosol generating device may have collected further usage pattern parameters, which can then be used to update the formula or function used to calculate capacity fade.

[0082] In an example, the method may further comprise: collecting battery capacity decay data for an aerosol generating device (preferably a plurality of aerosol generating devices); performing a regression analysis (preferably a nonlinear regression analysis) to obtain a model, formula and / or function for the correlation between usage pattern parameters and the battery capacity decay data; and calculating the capacity decay of the battery of the aerosol generating device from the current usage pattern parameters based on the model, formula and / or function. The battery capacity decay data may relate to the measured capacity decay occurring in the battery of the aerosol generating device. This may be represented by the total remaining capacity of a fully charged battery, or as a percentage of the battery capacity relative to an initial, nominal or reference capacity. The battery capacity decay data may be collected by a user actually using the aerosol generating device and taking the necessary measurements. Alternatively or in addition, the battery capacity decay data may be collected from accelerated life testing (ALT). The measurement of such battery capacity decay data is known to the skilled person and therefore need not be explained in further detail. If the user uses more than one aerosol generating device, it may be advantageous to have the aerosol generating devices at least intermittently communicatively coupled so that battery capacity decay data and preferably also usage pattern parameters can be collected from both, and preferably all, aerosol generating devices and used in the present method.

[0083] Battery capacity fade data and preferably also usage pattern parameters can also be shared by multiple aerosol generating devices via a network such as the Internet. In this way, a large amount of capacity fade data and preferably also usage pattern parameters can be provided to improve the accuracy of the method according to the present disclosure.

[0084] By regression analysis, a model, formula and / or function for calculating capacity fade from usage pattern parameters can be obtained. The model, formula or function can be, for example, a polynomial, preferably third order, as discussed above.

[0085] Once the model, formula, or function has been obtained, it can be implemented at the device, for example in the control circuitry of the aerosol-generating device, to calculate the capacity fade of the battery of the aerosol-generating device using the current usage mode parameters. The current usage mode parameters may relate to values of usage mode parameters collected after determining the formula or function, and preferably not used in this determination. Based on these values, an estimate of the capacity fade of the battery of the aerosol-generating device can be calculated.

[0086] For example, a model represented by a determined formula or function can be further optimized by constructing one or more probability density functions of 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 can then be validated using this additional data. When sufficient values of the usage pattern parameters are collected, the distribution of the values of these parameters in the field becomes apparent. This can enable the determination of a function that describes this distribution, such as a probability density function.

[0087] Monte Carlo simulation involves a method that algorithmically and repeatedly performs random sampling to obtain numerical results. This can then be used to randomly create new values for usage pattern parameters based on realistic distributions generated from field data. This additional realistic data can then be used to validate models, functions, and / or formulas, for example, by analyzing their sensitivity to random variations in each parameter, which cannot be demonstrated using field data alone.

[0088] According to another aspect of the present disclosure, an aerosol generating device is provided, which is configured to perform the steps of the method disclosed herein, such as at least a subset of the steps of the method or all of the steps. The aerosol generating device preferably includes a battery for storing electrical energy and a processing circuit system having one or more processors, which processing circuit system is also referred to as control circuit system in this document, and the one or more processors are configured to perform the steps of the method disclosed herein (e.g., at least a subset of the steps of the method or all of the steps). Therefore, all features, effects and advantages of the method according to the present disclosure are also valid for the aerosol generating device and are equally applicable to the aerosol generating device, and vice versa.

[0089] According to another aspect of the present disclosure, an aerosol generating system is provided, which includes an aerosol generating device and a supporting device that can be communicatively coupled to the aerosol generating device, wherein the supporting device is configured to perform the steps of the method disclosed herein (for example, at least a subset of the steps or all the steps of the method).

[0090] In an example, the companion device may be a smartphone, a tablet, a personal computer, a server, or a device configured to charge the aerosol-generating device. Therefore, all features, effects, and advantages of the method or aerosol-generating device according to the present disclosure are also valid and applicable to the aerosol-generating system, and vice versa.

[0091] Yet another 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 the system to perform the steps of the method according to the present disclosure as described above and below.

[0092] Yet another 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 a method according to the present disclosure as described above and below.

[0093] The present invention is defined in the claims. However, a non-exhaustive list of non-limiting examples is provided below. Any one or more features of these examples may be combined with any one or more features of another example, embodiment or aspect described herein.

[0094] Example A: A computer-implemented method of estimating capacity fade of a battery of an aerosol-generating device, the method comprising:

[0095] collecting at least two usage pattern parameters related to usage of the aerosol generating device; and

[0096] A capacity fade of a battery of the aerosol generating device is calculated, estimated, determined, estimated and / or predicted based on the at least two usage pattern parameters.

[0097] Example B: The method of example A, wherein the usage pattern parameters are collected over a predetermined period of time.

[0098] Example C: The method of any one of the preceding examples, wherein the usage pattern parameter is an average over a predetermined time period.

[0099] Example D: The method of any preceding example, wherein the usage pattern parameter indicates different characteristics of usage of the aerosol generating device by the user.

[0100] Example E: The method according to any one of the preceding examples, wherein at least one of the usage mode parameters indicates usage of the aerosol generating device by the user to generate aerosol in one or more usage sessions.

[0101] Example F: The method of any of the preceding examples, wherein the capacity fade is calculated as a relative decrease in the capacity of the battery relative to one or more of an initial capacity of the battery, a nominal capacity of the battery, and a reference capacity of the battery.

[0102] Example G: The method according to any of the preceding examples, wherein at least three, at least four or more usage pattern parameters are collected and used to calculate the capacity fade of the battery of the aerosol generating device, each of the usage pattern parameters indicating a different usage characteristic of the aerosol generating device by the user.

[0103] Example H: The method according to any one of the preceding examples, wherein the usage mode parameter is selected from the following parameters:

[0104] the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval,

[0105] the duration of one or more sessions of use,

[0106] a rest period between consecutive use sessions, preferably wherein the usage pattern parameter value relating to the rest period between consecutive use sessions is changed only for a rest period of 0 to 40 minutes between subsequent use sessions,

[0107] • A frequency of at least two consecutive uses, in particular without recharging the aerosol generating device.

[0108] Example 1: The method according to any one of the preceding examples, wherein at least or only three usage pattern parameters are collected and used to calculate the capacity fade of the battery of the aerosol generating device, the at least or only three usage pattern parameters being selected from the following parameters:

[0109] the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval,

[0110] the duration of one or more sessions of use,

[0111] a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions,

[0112] • A frequency of at least two consecutive uses, in particular without recharging the aerosol generating device.

[0113] Example J: The method according to any one of the preceding examples, wherein at least or only four usage pattern parameters are collected and used to calculate the capacity fade of the battery of the aerosol generating device, the at least or only four usage pattern parameters being:

[0114] the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval,

[0115] the duration of one or more sessions of use,

[0116] a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions, and

[0117] • A frequency of at least two consecutive uses, in particular without recharging the aerosol generating device.

[0118] Example K: The method according to any of the preceding examples, wherein the at least two usage mode parameters are selected from the following parameters

[0119] the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval,

[0120] the duration of one or more sessions of use,

[0121] a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions,

[0122] the frequency of at least two consecutive uses, in particular without recharging the aerosol generating device,

[0123] the number of charge-discharge cycles per predefined time interval,

[0124] the rest period after recharging the aerosol generating device,

[0125] · Rest time when the battery state of charge is less than 10%,

[0126] · Rest time when battery state of charge is greater than 90%,

[0127] · Aspiration volume,

[0128] Puffing frequency,

[0129] Suction rhythm,

[0130] the time at which pause mode is initiated at the aerosol generating device,

[0131] the time at which the pause mode is terminated at the aerosol generating device,

[0132] the duration of the pause mode at the aerosol generating device,

[0133] the ambient temperature during one or more periods of use,

[0134] the temperature of the heating element or heater means of the aerosol generating device during a predefined period of time before the start of a use process,

[0135] the ambient temperature during recharging of the battery,

[0136] the density of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol,

[0137] the weight of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol,

[0138] the type of aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol, and

[0139] • The humidity of the aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device.

[0140] Example L: The method of any one of the preceding examples, wherein the usage pattern parameters are combined linearly or quadratically or cubically to calculate the capacity fade.

[0141] Example M: The method of any of the preceding examples, wherein the usage pattern parameters are combined using a cubic or third-order polynomial to calculate the capacity fade.

[0142] Example N: The method of any one of the preceding examples, wherein calculating the capacity fade of a battery of the aerosol-generating device comprises predicting the capacity of the battery at a point in time.

[0143] Example O: The method of example N, wherein the time point associated with the predicted capacity of the battery of the aerosol-generating device is determined by an expected total number of uses of the aerosol-generating device up to that time point.

[0144] Example P: The method of example O, wherein an expected total number of uses of the aerosol-generating device up to the time point is used to calculate a predicted capacity of a battery of the aerosol-generating device.

[0145] Example Q: The method of any preceding example, comprising notifying a user of the calculated capacity fade of the battery.

[0146] Example R: The method according to any of the preceding examples, further comprising:

[0147] collecting battery capacity decay data of an aerosol generating device, preferably a plurality of aerosol generating devices,

[0148] performing a regression analysis, preferably a nonlinear regression analysis, to obtain a model of the correlation between the usage pattern parameters and the battery capacity decay data, and

[0149] A capacity fade of a battery of the aerosol generating device is calculated from current usage mode parameters based on the model.

[0150] Example S: A method according to Example R, wherein one or more probability density functions for the usage pattern parameters are established based on the collected usage pattern parameters, and further data for the usage pattern parameters are generated from these density functions using Monte Carlo simulation, and wherein the model is validated using the further data.

[0151] Example Sa: The method of any of the preceding examples, further comprising executing a function based on the capacity fade.

[0152] Example Sb: The method of example Sa, wherein the function comprises generating an output signal indicative of the capacity fade.

[0153] Example Sc: The method of example Sa or example Sb, wherein the function comprises generating an output signal indicative of a number of available uses performed by the aerosol generating device, wherein the number of available uses is based on the capacity decay.

[0154] Example Sd: A method according to example Sc, wherein the number of available usage processes based on the capacity fade is less than the number of available usage processes 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.

[0155] Example Se: The method of any of Examples Sa to Sd, wherein the function includes generating an output signal prompting a user to replace the battery.

[0156] Example Sf: The method of any of Examples Sb to Se, wherein the output signal is transmitted 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.

[0157] Example T: An aerosol-generating device configured to perform the steps of the method according to any of the preceding examples.

[0158] Example U: An aerosol generating device according to Example T, comprising:

[0159] a battery for storing electrical energy; and

[0160] Processing circuitry having one or more processors configured to perform the steps of the method according to any of Examples A to S.

[0161] Example V: An aerosol-generating system comprising an aerosol-generating device and an accessory communicatively coupled to the aerosol-generating device, wherein the accessory is configured to perform the steps of the method according to any one of Examples A to S.

[0162] Example W: An aerosol generating system according to example V, wherein the companion device is a smartphone, a tablet computer, a personal computer, a server, or a device configured to charge the aerosol generating device.

[0163] Example X: 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 method according to any one of Examples A to S.

[0164] Example Y: A non-transitory computer-readable medium storing a computer program according to example X. BRIEF DESCRIPTION OF THE DRAWINGS

[0165] Examples will now be further described with reference to the accompanying drawings, in which:

[0166] Figure 1 An aerosol generating system including an aerosol generating device and an associated device is shown;

[0167] Figure 2 shows a probability density function of a usage pattern parameter, the number of charge-discharge cycles per predefined time interval;

[0168] Figure 3 shows the probability density function of the usage pattern parameter, duration of the usage process;

[0169] Figure 4 shows the probability density function of the usage pattern parameter, namely, the rest time between consecutive uses; and

[0170] Figure 5 A flow chart of the method is shown.

[0171] The drawings are merely schematic and not drawn to scale. DETAILED DESCRIPTION

[0172] Figure 1 An aerosol generating system 1 for generating an aerosol for consumption, for example, by a user during one or more sessions is shown. The system 1 may comprise an aerosol generating device 2 for generating an aerosol and an accessory 3 for at least partially receiving the aerosol generating device 2. The accessory 3 may be a charging device for charging the aerosol generating device 2 and / or its energy storage device or battery.

[0173] The aerosol-generating device 2 may comprise an insertion opening 4 for at least partially inserting an aerosol-generating article 17. The aerosol-generating article 17 may comprise an aerosol-forming substrate (eg a tobacco-containing substrate) and / or a cartridge comprising a liquid.

[0174] The aerosol-generating device 2 may further include processing circuitry 5 or control circuitry 5 having one or more processors 6. To generate an 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 arrangement for applying heat to at least a portion of the aerosol-generating article 17. The processing circuitry 5 may be configured to control the actuation, activation, and / or deactivation of the at least one heating element 7. The processing circuitry 5 may also be configured to perform the steps of the methods described herein.

[0175] In order to power the at least one heating element 7 with electricity, the aerosol generating device 2 may further include at least one energy storage device (e.g., in the form of a battery 15) for storing electrical energy or electricity. The aerosol generating device 2 may further include at least one electrical connector 12 for coupling to a corresponding at least one electrical connector 13 of the accessory device 3. For example, when the aerosol generating device 2 is at least partially inserted into the opening 14 of the accessory device 3, the one or more electrical connectors 12 of the aerosol generating device 2 may be coupled to the one or more electrical connectors 13 of the accessory device 3 to charge the at least one battery 15 of the aerosol generating device 2.

[0176] The aerosol-generating device 2 may further comprise user interface components, for example comprising an input element in the form of a button 8. The button 8 may function 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 may be activated and may apply heat to at least a portion of the aerosol-generating article 17, such that an aerosol may be generated for consumption by a user, for example during use.

[0177] The aerosol generating device 2 may also include a communication device 9 or a communication circuit system 9, which has one or more communication interfaces 10 for communicatively coupling the aerosol generating device 2 with the supporting device 3, for example via an Internet connection, a wireless LAN connection, a WiFi connection, a Bluetooth connection, a mobile phone 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 near-field connection and / or an IoT connection.

[0178] The aerosol generating device 2 may further comprise a data storage device 11 for storing information or data, such as collected usage pattern parameters, battery decay data and / or one or more mathematical functions or formulas, for example to calculate battery capacity decay.

[0179] As described in detail herein above and below, the aerosol generating device 2 is configured to collect, acquire and / or store at least two usage pattern parameters related to the use of the aerosol generating device 2. Furthermore, the aerosol generating device 2 (e.g., the processing or control circuitry 5) is configured to calculate the capacity fade of the battery 15 of the aerosol generating device 2 based on the at least two usage pattern parameters.

[0180] One or more sensors 16 may be arranged on, at or in the aerosol generating device 2 to collect data, such as usage mode parameters and / or battery decay data.

[0181] The aerosol generating device 2 and the companion device 3 may each comprise a user interface comprising one or more output elements, such as LED(s), for outputting signals to a user.

[0182] Figure 2 、 3 and 4 show exemplary probability density functions for selected usage pattern parameters.

[0183] Specifically, Figure 2The probability density function for the usage pattern parameter, namely the number of charge-discharge cycles per predefined time interval (in this case, per day), is shown. The number n of charge-discharge cycles per day is shown on the abscissa (or "horizontal axis"), while the probability percentage for each number n is shown on the ordinate (or "vertical axis"). The distribution reaches its highest probability around eight charge-discharge cycles per day. If the user recharges the aerosol generating device 2 after each use session, the number n of charge-discharge cycles per predefined time interval (in this case, per day) is equal to the usage pattern parameter, namely the number of use sessions in which the aerosol generating device has been operated to generate aerosol per predefined time interval (in this case, per day). Furthermore, in this case, another usage pattern parameter, namely the frequency of at least two consecutive use sessions, in particular without recharging the aerosol generating device in between (this can alternatively be referred to as a back-to-back scenario), is zero. This usage pattern with a back-to-back scenario of zero will be used in the following calculation examples.

[0184] Figure 3 The probability density function of the usage pattern parameter, duration of a usage session, is shown. The duration t1 of the usage session is shown in minutes on the abscissa (or "horizontal axis"), and the probability percentage of each duration is shown on the ordinate (or "vertical axis"). The aerosol generating device 2 is typically designed to automatically end a usage session after six minutes or fourteen puffs (whichever occurs first), which is why usage sessions exceeding six minutes cannot be recorded.

[0185] Figure 4 The probability density function for the usage pattern parameter, rest time between consecutive uses, is shown. The rest time t2 is shown in minutes 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 stems from the effect of the aerosol generating device 2 cooling down between uses. The longer the rest time, the closer the aerosol generating device 2 is to ambient temperature. It has been determined that after approximately forty minutes of rest time, the aerosol generating device 2 has reached ambient temperature, and any rest time exceeding forty minutes has the same effect on battery degradation as a rest time of forty minutes. This can be reflected in the calculation of the estimated battery degradation by varying the value of the usage pattern parameter, rest time between consecutive uses, only for rest times between zero and forty minutes, and keeping this value constant for rest times of forty minutes or more.

[0186] Figure 5A flow chart of a method 18 of the present disclosure according to an exemplary embodiment is shown. Using a predetermined model or formula or function, respectively, the method 18 may comprise only a step 19 of collecting at least two usage mode parameters, which means determining the values of these parameters during operation of the device 2, and a step 20 of calculating the capacity decay of the battery 15 of the aerosol generating device 2 based on these usage mode parameters. Therefore, only steps 19 and 20 are shown in solid-line boxes, while all other optional steps are shown in dashed-line boxes.

[0187] As a non-limiting example, usage pattern parameters are collected, namely the number of usage sessions during which the aerosol generating device 2 has been operated to generate aerosol per predefined time interval (P1), the duration of the usage session (P2), the rest time between consecutive usage sessions (P3), and the frequency of at least two consecutive usage sessions (back-to-back scenario; P4), in particular without recharging the aerosol generating device 2. Based on these usage pattern parameters, the capacity fade of the battery 15 of the aerosol generating device 2 can be calculated using the following equation:

[0188] Cap=C0+C1·(P1·k)·P2+C2·(P1·k)·P3+C3·(P1·k)·P4+C4·P3·P4+

[0189] C5·(P1·k) 3 +C6·(P1·k)·P2·P3+C7·(P1·k)·P2·P4+C8·(P1·k)·P3·P4+C9·(P2) 3 +C 10 ·P2·P3·P4+C 11 (P3) 3 +C 12 (P4) 3

[0190] in:

[0191] Cap is the calculated capacity decay of the battery 15 of the aerosol generating device 2 , expressed as the total remaining capacity when fully charged in mAh;

[0192] C0 is the initial battery capacity in mAh;

[0193] P1 is the number of times the aerosol generating device 2 has been operated to generate aerosol per predefined time interval;

[0194] P2 is the duration of the usage process in minutes;

[0195] P3 is the rest time between consecutive uses in minutes;

[0196] P4 is the frequency of at least two consecutive, in particular, use sessions during which the aerosol generating device 2 is not recharged;

[0197] k is a time period associated with the estimated capacity fade of the battery 15; and

[0198] C1 to C 12 is a constant whose units are chosen so that each sum in the equation is expressed in mAh.

[0199] Specifically, the values of the constants may be: 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.

[0200] For a non-limiting example calculation, it is assumed that the initial battery capacity C0 is 240 mAh, the number of usage sessions P1 during which the aerosol generating device 2 has been operated to generate aerosol per day is 8, the duration P2 of the usage session is 6.5 minutes, the rest period P3 between consecutive usage sessions is 7 minutes, and the frequency P4 of at least two consecutive usage sessions, in particular, during which the aerosol generating device 2 is not recharged, is 0, meaning that the aerosol generating device 2 is recharged after each use. Finally, the capacity decay of the battery 15 after k = 90 days is calculated. Inserting these values into the above third-order polynomial yields a calculated capacity decay of the battery 15 of the aerosol generating device 2 of approximately 236 mAh. This is the total capacity that a fully charged battery 15 drops to from the 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 reduction of approximately 1.7% in battery capacity.

[0201] It is important to note that the above embodiments, including the selection of the parameters, models or formulas or functions used in the model and the constants C1 to C 12 The value of is only exemplary. For example, the duration P2 of the use process may be 6 minutes or 5.5 minutes, or another duration.

[0202] For example, they can be determined by regression analysis, as described below and above in more detail. However, the present invention can be easily implemented using different numbers and / or different selected usage pattern parameters, different models or formulas or functions and / or different values of constants. Although given examples can be preferred modes for implementing the present invention, it is even possible to expect that adjustment calculations are provided, for example, in short, medium or long time ranges, or to attach more importance to usage pattern parameters within certain numerical ranges, or the like. There may be multiple possibilities for implementing the present invention, which means that the present invention is not limited to the exact examples given above.

[0203] The model or formula or function for calculating the capacity fade of the battery 15 may be predetermined and stored in the aerosol generating device 2, for example in the data storage device 11. Collecting the usage pattern parameters and calculating the capacity fade 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 combination with one or more sensors 16.

[0204] After the calculation step 20, the method 18 may include a step 27 in which the user is notified of the calculated capacity decay of the battery 15. This notification may be output at the aerosol generating device 2 or the companion device 3 and may only be provided when the calculated capacity decay of the battery 15 reaches a predetermined threshold. One such threshold may be, for example, 190 mAh of the total remaining capacity of the battery 15. This value may be of interest because this capacity is typically barely enough for two consecutive sessions of use, and values below 190 mAh may not be sufficient to provide the user with two sessions of use without further recharging.

[0205] Method 18 may also include the step of providing or refining the model or formula or function used in calculation step 20. For this purpose, it may be provided that in step 21, battery capacity decay data is collected, which represents the battery capacity decay of the battery 15 at the collection time. This may be done during normal use of the aerosol generating device 2 in the field, or the battery capacity decay data may alternatively be collected by an accelerated life test (ALT) using the aerosol generating device 2. Step 22 may be performed simultaneously or in parallel, with the usage pattern parameters being collected from the use of the aerosol generating device 2 in the field or from the ALT. Based on 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 represent the correlation between the battery capacity decay data collected in step 21 and the usage pattern parameters collected in step 22 in a model or formula or function, preferably a third-order or cubic polynomial. As an example, the equations given above in the exemplary calculations are determined in this way. After step 23 , when the model or formula or function is built, the method 18 can calculate the future battery degradation from the current usage pattern parameters collected in step 19 , as explained above.

[0206] In another aspect, the present disclosure can provide a way to validate a model or formula or function and thereby more clearly illustrate the impact of changes in each variable of the model or formula or function compared to 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. Figure 2 、 3 Examples of such functions of selected parameters are shown in and 4. These functions have the advantage over clouds of single data points that they can be used to create a large number of randomly selected values for the usage pattern parameter in question by random sampling employed by the Monte Carlo simulation in step 25. The data thus generated still conforms to the distribution of usage pattern parameters observed in the field and / or in the ALT and therefore presents rich data that remains realistic for the specific use case. The large data set that can be created in this way can then be used to validate the model or formula or function in step 26. It is also envisaged that the validation in step 26 can result in adjustments or fine-tuning of the model or formula or function and that the validated or adjusted model or formula or function can be employed in the calculations according to step 20.

[0207] For the purpose of this specification and the appended claims, unless otherwise indicated, all numbers representing amounts, quantities, percentages, etc. should be understood to be modified by the term "about" in all cases. Moreover, all ranges include the disclosed maximum and minimum points, and include any intermediate ranges therein that may be specifically listed or may not be listed in this article. Therefore, in this context, the number A is understood to be 10% of A±A. In this context, the number A can be considered to include a numerical value within the general standard error for the measurement of the attribute modified by the number A. In some cases used in the appended claims, the number A may deviate from the percentages listed above, provided that the amount of A deviation does not substantially affect the basic characteristics and novel features of the claimed invention. Moreover, all ranges include the disclosed maximum and minimum points, and include any intermediate ranges therein that may be specifically listed or may not be listed in this article.

Claims

1. A computer-implemented method for estimating capacity fade of a battery of an aerosol generating device, the method comprising: collecting at least two usage pattern parameters related to usage of the aerosol generating device; as well as A capacity fade of a battery of the aerosol generating device is calculated based on the at least two usage pattern parameters. 2 . The method according to claim 1 , wherein the usage pattern parameter is collected within a predetermined time period and / or the usage pattern parameter is an average value within a predetermined time period.

3. A method according to any one of the preceding claims, wherein at least one of the usage mode parameters indicates usage of the aerosol generating device by the user to generate aerosol in one or more usage sessions.

4. A method according to any one of the preceding claims, wherein at least three, at least four or more usage pattern parameters are collected and used to calculate the capacity fade of the battery of the aerosol generating device, each of the usage pattern parameters being indicative of a different characteristic of usage of the aerosol generating device by the user.

5. The method according to any one of the preceding claims, wherein the usage mode parameter is selected from the following parameters: the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval, the duration of one or more sessions of use, a rest period between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest period between consecutive use sessions is changed only for a rest period of 0 to 40 minutes between subsequent use sessions, • A frequency of at least two consecutive uses, in particular without recharging the aerosol generating device.

6. A method according to any one of the preceding claims, wherein at least or only three usage pattern parameters are collected and used to calculate the capacity fade of the battery of the aerosol generating device, the at least or only three usage pattern parameters being selected from the following parameters: the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval, the duration of one or more sessions of use, a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions, • A frequency of at least two consecutive uses, in particular without recharging the aerosol generating device.

7. A method according to any preceding claim, wherein at least or only four usage pattern parameters are collected and used to calculate the capacity fade of the battery of the aerosol generating device, the at least or only four usage pattern parameters being: the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval, the duration of one or more sessions of use, a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions, and • A frequency of at least two consecutive uses, in particular without recharging the aerosol generating device.

8. The method according to any one of the preceding claims, wherein the at least two usage mode parameters are selected from the following parameters the number of uses during which the aerosol generating device has been operated to generate aerosol per predefined time interval, the duration of one or more sessions of use, a rest time between consecutive use sessions, preferably wherein the value of the usage pattern parameter relating to the rest time between subsequent use sessions is changed only for a rest time between 0 and 40 minutes between subsequent use sessions, the frequency of at least two consecutive uses, in particular without recharging the aerosol generating device, the number of charge-discharge cycles per predefined time interval, the rest period after recharging the aerosol generating device, · Rest time when the battery state of charge is less than 10%, · Rest time when battery state of charge is greater than 90%, · Aspiration volume, Puffing frequency, Suction rhythm, the time at which pause mode is initiated at the aerosol generating device, the time at which the pause mode is terminated at the aerosol generating device, the duration of the pause mode at the aerosol generating device, the ambient temperature during one or more periods of use, the temperature of the heating element or heater means of the aerosol generating device during a predefined period of time before the start of a use process, the ambient temperature during recharging of the battery, the density of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol, the weight of the aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate the aerosol, the type of aerosol-generating substrate or aerosol-generating article used with 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.

9. The method according to any one of the preceding claims, wherein the usage pattern parameters are combined linearly or as a quadratic or cubic polynomial to calculate the capacity fade.

10. The method according to any one of the preceding claims, wherein the usage pattern parameters are combined with a cubic polynomial or a third-order polynomial to calculate the capacity fade.

11. A method according to any preceding claim, wherein calculating the capacity fade of a battery of the aerosol generating device comprises predicting the capacity of the battery at a point in time.

12. A method according to claim 11, wherein a time point related to the predicted capacity of the battery of the aerosol generating device is determined by an expected total number of usage processes of the aerosol generating device up to the time point, preferably wherein the expected total number of usage processes 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. A method according to any preceding claim, comprising informing a user of the calculated capacity fade of the battery.

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 an accessory device communicatively coupled to the aerosol generating device, wherein the accessory device is configured to perform the steps of the method according to any one of claims 1 to 13.

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