EP4651749A1

EP4651749A1 - Estimation of battery degradation in aerosol-generating devices

Info

Publication number: EP4651749A1
Application number: EP23707861.3A
Authority: EP
Inventors: Thomas CIMPRICH; Laxman PANGENI; Hongjie XU; Guoqiang CAI; Yiu Chi CHEUNG
Original assignee: Philip Morris Products SA
Current assignee: Philip Morris Products SA
Priority date: 2023-01-20
Filing date: 2023-01-20
Publication date: 2025-11-26
Also published as: WO2024152338A1; WO2024152338A9; CN120456844A; KR20250134238A

Abstract

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

Description

ESTIMATION OF BATTERY DEGRADATION IN AEROSOL-GENERATING DEVICES

The present disclosure relates to a computer-implemented method of estimating capacity degradation of a battery of an aerosol-generating device. The invention further relates to an aerosol-generating device and an aerosol-generating system configured to perform such method. Further, the invention relates to a corresponding computer program and to corresponding non-transitory computer-readable medium storing one or more of such computer programs
Aerosol-generating devices are typically designed as handheld devices that can be used by a user for consuming or experiencing, for instance in one or more usage sessions, aerosol generated by heating an aerosol-generating substrate or an aerosol-generating article. The aerosol-generating devices the present disclosure pertains to are commonly referred to as heated tobacco products (HTP) , heat-not-burn devices, electronic cigarettes and/or vaporisers.
Exemplary aerosol-generating substrates can comprise solid substrate material, such as tobacco material or tobacco cast leaves (TCL) material. The substrate material can, for example, be assembled, often with other elements or components, to form a substantially stick-shaped aerosol-generating article. Such a stick or aerosol-generating article can be configured in shape and size to be inserted at least partially into the aerosol-generating device. The aerosol-generating system may 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, aerosol-generating substrates can comprise one or more liquids and/or solids, which can, for example, be supplied to the aerosol-generating device in the form of a cartridge or container. Corresponding exemplary aerosol-generating articles can, for example, comprise a cartridge containing or fillable with the liquid and/or solid substrate, which can be vaporized during aerosol consumption by the user based on heating the substrate and/or liquid. Usually, such cartridge or container can be coupled to, attached to or at least partially inserted into the aerosol-generating device. Alternatively, the cartridge may be fixedly mounted to the aerosol-generating device and refilled by inserting liquid and/or solid into the cartridge.
For generating the 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 part of the aerosol-generating substrate. The heating element, heater device or heat source can be arranged in the handheld device or a handheld part of the aerosol-generating device. Alternatively or additionally, at least a part of or the entire heating element or heater device or heat source can be fixedly associated with or arranged within an aerosol-generating article, for instance in the form of a stick or cartridge, which can be attached to and/or powered by the handheld device or handheld part of the aerosol-generating device.
Exemplary heating elements or heater devices can be based on one or more of resistive heating, inductive heating and microwave heating using electrical energy supplied via, drawn from or stored in battery of the aerosol-generating device. As used herein, a battery of the aerosol-generating device can generally refer to an energy storage of the aerosol-generating device configured to store electrical energy. Accordingly, the term battery can include one or more capacitors, one or more accumulators or other types of energy storage. Also, any reference to a battery herein can include a plurality of batteries.
Typically, aerosol-generating devices comprise a battery providing the electrical energy needed to operate the aerosol-generating device and especially for heating the aerosol-generating substrate and/or article, for example to generate aerosol in one or more usage sessions using one or more aerosol-generating articles. The battery may, for example, be a lithium-ion battery.
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 aerosol using the aerosol-generating device. Therein, a usage session may be finite. In other words, a usage session may have a start, an end and a duration. The duration of the usage session as measured by time may be influenced by 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. The duration of the usage session may be less than the maximum time if one or more monitored parameters reaches a predetermined threshold before the maximum time from the start of the usage session. By way of example, the one or more monitored parameters may comprise one or more of: i) a cumulative puff count of a series of puffs drawn by a user since the start of the usage session, and ii) a cumulative volume of aerosol evolved from the aerosol-forming substrate since the start of the usage session.
A battery capacity may typically be chosen so that the aerosol-generating device can provide a user with at least a minimum number, for example at least two or more, consecutive usage sessions or experiences without having to recharge the battery or the aerosol-generating device in between. To improve user experience, aerosol-generating devices are usually designed to only allow a user to start a usage session if the battery contains enough electrical energy to fully complete the usage session. However, battery capacity can degrade over time with accumulating charge/discharge-cycles. The speed and degree or extent of battery capacity degradation can be variable and dependent on many different factors, which can make an estimation or determination of the degradation of the battery difficult. However, it may be advantageous, for example, to know beforehand when the battery capacity of the aerosol-generating device will have degraded so much that the minimum number of consecutive usage sessions without having to recharge the battery or the aerosol-generating device in between cannot be provided any more. In this case, the user could be advised by a user interface signal to replace the battery timely enough not to experience any limitation in the use of the aerosol-generating device. Additionally or alternatively, the device may be configured to output a signal indicative that the number of consecutive usage sessions or experiences without having to recharge the battery, or the aerosol-generating device in between has been reduced.
Conventional models for battery degradation typically involve detailed information about the specific build or design of the battery which may not be available to a manufacturer of aerosol-generating devices. They may also lack prediction accuracy for batteries of aerosol-generating devices because the battery capacity degradation can be strongly influenced 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 can have different habits or patterns in using their aerosol-generating device, wherein especially continuous usage with intermittent resting before charging, variable resting time, and different usage durations factor into conventional battery degradation models, thereby however potentially delivering insufficient accuracy for battery degradation estimation in aerosol-generating devices.
It may therefore be desirable to provide for an improved aerosol-generating device and/or aerosol-generating system, for example allowing for an improved estimation and/or determination of capacity degradation of a battery of an aerosol-generating device.
This is achieved by the subject-matter of the independent claims. Optional features are provided by the dependent claims and by the description.
According to an aspect of the present disclosure, there is provided a computer-implemented method of estimating and/or determining capacity degradation of a battery of an aerosol-generating device, the method comprising: collecting at least two usage pattern parameters related to a usage of the aerosol-generating device; and calculating a capacity degradation of the battery of the aerosol-generating device based on said at least two usage pattern parameters.
In other words, the capacity degradation of the battery of the aerosol-generating device, which may generally refer to a decrease in capacity of the battery, can be determined directly from usage pattern parameters pertaining to the use or operation of the aerosol-generating device itself. As a consequence, the estimated or determined capacity degradation may reflect or include the actual operation of the aerosol-generating device, and thus may be accurate, in particular when compared to conventional models for battery degradation focusing on characteristics of the battery alone. Also, it may therefore not be required to employ a conventional model for battery degradation, which may be unsuitable to the specific use case of aerosol-generating devices.
The aerosol-generating device may be designed or configured to collect the usage pattern parameters during its operation, which can ensure that the collected usage pattern parameters pertain to the actual, individual user of the aerosol-generating device. In this way, the predicted capacity degradation of the battery of the aerosol-generating device which is calculated from these usage pattern parameters can be tailored to the individual habits or usage pattern of said user. It is noted that the usage pattern parameters may also be referred to in the following as “parameters” for reasons of simplicity.
As explained in more detail below, the calculated capacity degradation of the battery of the aerosol-generating device, as used herein, may pertain to a point of time in the future, for example to a degradation of the battery after a predetermined time period. Accordingly, the calculated capacity degradation may refer to an estimated and/or predicted capacity degradation. Alternatively or additionally, calculating the capacity degradation can include estimating and/or predicting the capacity degradation, for example to a point of time in the future and/or after a predetermined period of time. Predicting the capacity degradation may allow to provide a user of the aerosol-generating device with an early warning, for example if the degradation of the battery is going to reach a particular extent after the predetermined time period has elapsed. The user may then timely replace the battery to avoid limitations in the use of the aerosol-generating device, which may improve overall user experience.
The usage pattern parameters may be collected over a predetermined period of time. The predetermined period of time may be, for example, a fixed number of hours, days, weeks or months after the first use of the aerosol-generating device. Alternatively, the predetermined period of time may be the whole time since the first use of the aerosol-generating device. Optionally, the aerosol-generating device maybe 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 the one or more usage pattern parameters, for example in a data storage of the aerosol-generating device or other device communicatively couplable thereto. 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 may comprise, for example, counters and/or timers and/or sensors, such as temperature sensors, volume sensors, humidity sensors and others.
In an example, the usage pattern parameters may be collected over the entire life of the aerosol-generating device, which may mean from a first to a last usage session of the aerosol-generating device. The aerosol-generating device may preferably comprise a 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 couplable to the aerosol-generating device.
In an example, the usage pattern parameters may be mean values over a predetermined period of time. In other words, the aerosol-generating device may be designed or configured to calculate a mean value from at least two and preferably from all single values of a particular collected usage pattern parameter. Accordingly, for each collected usage parameter, a mean value may be computed over the predetermined period of time. The predetermined period of time may be, for example, a fixed amount of hours, days, weeks and/or months after the first use of the aerosol-generating device. The predetermined period of time may alternatively be, for example, a fixed amount of hours, days, weeks and/or months before the present, so that for example only recent values of the usage pattern parameters may be collected and/or employed. Alternatively, the predetermined period of time may be the whole time since the first use of the aerosol-generating device. By providing mean values, especially from usage pattern parameters collected over a longer period of time, future predictions of the usage pattern of the individual user may be highly accurate, which in turn can make the estimation of the capacity degradation of the battery of the aerosol-generating device more reliable.
The usage pattern parameters may be indicative of different usage and/or operational characteristics of the aerosol-generating device by the user. In cases in which the method described herein pertains to more than one usage pattern parameter, for example at least two usage pattern parameters, these usage pattern parameters may differ from each other. Each of the parameters may thus be one of the parameters listed further below, wherein each parameter may be different from the others. In particular, it is noted that two usage pattern parameters as used herein may not describe or refer to different values, for example numerical values, of the same parameter, but rather to values of different parameters. For example, usage pattern parameters may pertain to parameters describing or related to the use or operation of an aerosol-generating device by a user, in particular how and/or how often and/or when and/or how long and/or in what state the aerosol-generating device is and/or has been used or operated by the user. The usage pattern parameters may pertain or relate to one or both the usage sessions of the aerosol-generating device and the times between usage sessions, for example resting time or recharging events of the aerosol-generating device. Thus, the usage pattern parameters described herein may characterise the different preferences and/or habits of each individual user, which may differ between users, and which may have an impact on the speed and/or the extent of battery capacity degradation. By employing the usage pattern parameters as described herein in the estimation of said degradation, highly accurate predictions tailored to individual users can be achieved.
At least one of the usage pattern parameters may, in an example, be indicative of the usage of the aerosol-generating device by the user to generate aerosol in one or more usage sessions. For example, the puff volume may be measured during one or more usage sessions and collected as usage pattern parameter. An average or a mean value may be calculated from multiple, for example all, puffs from one usage session. Additionally or alternatively, puff volume may be measured during more than one usage sessions. An average or a mean value may be calculated from multiple, for example all, puffs from all usage sessions. Alternatively or additionally, there may also be parameters that can only be determined by observing more than one usage session. For example, the resting time between usage sessions can only be determined when two usage sessions occur. Another example may be the frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between. This parameter can also only be determined by observing more than one usage sessions.
The capacity degradation may be calculated as relative decrease in the capacity of the battery with respect to one or more of an initial capacity of the battery, a nominal capacity of the battery, and a reference capacity of the battery. The capacity degradation of the battery of the aerosol-generating device may be a measure of how much and/or an amount of electrical energy the battery is able to store at a specific point in time. This can, for example, be an absolute value expressed as ampere hours or a similar unit of measurement. The capacity degradation can also be expressed as a comparison to an original, initial or nominal battery capacity or a reference capacity, for example as a percentage. It is also possible to express the capacity degradation in other units, for example as the total number of usage sessions that may be possible for the user or granted to the user with one full charge of the battery. These other units can also be expressed as a comparison, for example a percentage, of an initial or reference value.
While a meaningful estimation of the battery degradation can be achieved with at least two usage pattern parameters, the accuracy of the estimation may increase when more usage pattern parameters are used in combination. In an example, 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 the aerosol-generating device, wherein each of the usage pattern parameters may optionally be indicative of different usage characteristics of the aerosol-generating device by the user.
As will be further explained below, various different parameters can advantageously be used in the context of the present disclosure for estimating the battery capacity degradation. However, the inventors have identified four parameters that may be particularly useful for easily and reliably estimating capacity degradation of a battery of an aerosol-generating device. Accordingly, in an example, the usage pattern parameters may be selected from the parameters or group of parameters consisting of:
● number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval, for example per day,
● duration of one or more usage sessions,
● resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between consecutive usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,
● frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between. The frequency of at least two usage sessions in a row may also be called back-to-back regime.
The number of usage sessions of the aerosol-generating device may be a relevant parameter because it may characterise the intensity of use of the device by the user. It therefore may allow to differentiate casual from heavy users and may be used to describe the progression through the lifetime of the device and/or the battery.
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 for a usage session may be highly correlated to its duration, as the aerosol-generating device should preferably maintain the heating temperature during this period. The inventors have found that a longer duration of usage sessions correlates with faster battery capacity degradation.
The resting time between consecutive usage sessions may be related to the temperature of the device, a heating element of the device and the battery. During a usage session, the heating element, the device and the battery may be heated up by heating the aerosol-generating substrate or article. After a usage session, the device and the battery start to cool off. After around 40 minutes, the battery typically reaches ambient temperature, which may mean that different resting times of 40 minutes or more may have the same effect, from the point of view of temperature. For this reason, optionally, only resting times between 0 and 40 minutes may result in different values for the corresponding usage pattern parameter, whereas times of 40 minutes and more may have the same value. Short resting times that are not long enough for the device to reach ambient temperature may be less stressful for the battery and therefore cause less battery degradation.
The frequency of at least two usage sessions in a row, especially without recharging of the aerosol-generating device or the battery in between, may also be referred to as back-to-back regime. This parameter may, for example, be described by the percentage of two consecutive usage sessions which occur without the aerosol-generating device, or the battery having been recharged before initiation of the second usage session. For example, in an aerosol-generating device designed or configured to provide two usage sessions after fully charging the battery, recharging the aerosol-generating device after each usage session would result in a back-to-back regime of 0 %, whereas recharging the device only after two usage sessions have been performed would result in a back-to-back regime of 100 %. A back-to-back regime of 50 %would then describe recharging the device after one usage session half the time and only after two usage sessions the rest of the time. Generally, the frequency of at least two usage sessions in a row may be determined by dividing the number of consecutive usage sessions by the total number of usage sessions.
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, compute, estimate and/or predict the capacity degradation of the battery of the aerosol-generating device. Alternatively, the method of the present disclosure may comprise collecting exclusively two or exclusively three or exclusively four usage pattern parameters selected from the parameters listed above and using them to calculate the capacity degradation of the battery of the aerosol-generating device. Using only a selected set of parameters can simplify the model, the data collection and the calculation, which can reduce the need for high computational power and may make the method of the present disclosure easily implementable on portable devices.
There are a number of further parameters that may be suitable for the method of the present disclosure, and the invention is therefore not limited to the parameters mentioned above. All in all, the at least two and preferably the at least three or the at least four usage pattern parameters may be selected from the parameters:
● number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,
● duration of one or more usage sessions,
● resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,
● frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between,
● amount of charge-discharge cycles per predefined time interval,
● resting time after recharging the aerosol-generating device,
● resting time with a battery state of charge (SOC) of less than 10 %,
● resting time with a battery state of charge (SOC) of more than 90 %,
● puff volume,
● puff frequency,
● puff rhythm,
● time of initiation of a pause mode at the aerosol-generating device,
● time of termination of a pause mode at the aerosol-generating device,
● duration of a pause mode at the aerosol-generating device,
● ambient temperature during one or more usage sessions,
● temperature of a heating element or heater device of the aerosol-generating device within a predefined period of time before start of a usage session,
● ambient temperature during recharging of the battery,
● density of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,
● weight of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,
● type of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol, and
● humidity of an aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device.
The number of charge-discharge cycles may pertain to the number of times the aerosol-generating device is or has been used and then recharged per predefined time interval, for example per day. The more such cycles, the more the battery may degrade, making this parameter a suitable candidate to be used in the method of the present disclosure.
A puff in the sense of the present disclosure may describe a pull and/or draw on the aerosol-generating device while inhaling a mixture of air and aerosol by a user. The puff volume may describe the volume of said mixture inhaled in one pull or inhalation. Puff frequency and rhythm may describe corresponding patterns in the occurrence of puffs characteristic for individual users.
A pause mode may refer to a special mode of the aerosol-generating device allowing a pause during a usage session. Pause mode therefore may not pertain to and may be distinct from resting times between usage sessions.
The aerosol-generating device may be operated in at least two operation modes, an aerosol-releasing 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 or above a first temperature level, or at a plurality of different temperatures within a first temperature range in the aerosol-releasing mode. Therein, the first temperature level, and/or the temperatures in the first temperature range, may correspond to predetermined heating temperatures or temperatures above, which may be sufficient to generate aerosol. The aerosol-generating device may further be configured to heat the heating element, the aerosol-generating article and/or the substrate at a second temperature level below the first temperature level, and/or the temperatures in the first temperature range, in a pause mode of the aerosol-generating device. The second temperature level may, for example, refer to a temperature above room temperature and below the first temperature level, and/or the temperatures in the first temperature range.
A user experience, also referred to as usage session or experience of an aerosol-generating article herein, may be interrupted, for example by switching the device into the pause mode, and resumed by a user at a later, wherein the aerosol-generating article or substrate may be kept in pause mode of the aerosol-generating device at a temperature below the first temperature level and/or below the predetermined heating temperature used during normal use of the device (in particular during a user experience or usage session) , but still above or well above room temperature. That is, the second temperature level preferably may be chosen such as to avoid degradation of the non-depleted substrate or aerosol-generating article. In particular, the second temperature level may be chosen such as to be sufficiently low in order to minimize depletion of the substrate or article during the pause mode, and at the same time to be sufficiently high in order to avoid vapor to condensate in the device which otherwise could affect the quality of the non-depleted aerosol-generating substrate or article.
During use of the device, in particular when a user experience or usage session is to take place, the aerosol-generating device may be operated in the aerosol-releasing mode, whereas during a use pause of the device, that is, when no user experience or usage session is to take place and/or when a usage session is interrupted by a pause, the aerosol-generating device may be operated in the pause mode. During both, the aerosol-releasing mode and the pause mode of the aerosol-generating device, the heating element, a heating circuitry and/or a heating arrangement may be in operation, in particular in heating operation, yet at different temperature levels, namely, at a first temperature level during the aerosol-releasing mode, which may be chosen to be sufficiently high in order to generate an aerosol, and at a second temperature level below the first temperature level during the pause mode, which may be chosen to be sufficiently low in order to minimize depletion of the substrate, whilst avoiding degradation.
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 in a range between 200 degree Celsius and 500 degree Celsius, particularly between 250 degree Celsius and 450 degree Celsius, particularly between 270 degree Celsius and 430 degree Celsius, particularly between 315 degree Celsius and 355 degree Celsius, or between 240 degree Celsius and 280 degree 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 usage sessions and/or when operating the device in the aerosol releasing mode. For example, the first temperature level and/or heating temperature for liquid aerosol-generating articles or substrates may be lower than the first temperature level for solid aerosol-generating articles or substrates.
In general, the second temperature level may be chosen to maintain a usability of the aerosol-generating article or substrate for a prolonged 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. Accordingly, the second temperature level may be in a range between 175 degree Celsius and 225 degree Celsius, particularly between 185 degree Celsius to 215 degree Celsius, more particularly between 195 degree Celsius and 205 degree Celsius. These temperatures may be sufficiently low in order to minimize depletion of the substrate during the pause mode but at the same time sufficiently high in order to avoid vapor to condensate in the device, which could lead to degradation of the aerosol-generating article or substrate.
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 degree Celsius, in particular at least 175 degree Celsius, preferably at least 185 degree Celsius, more preferably at least 195 degree Celsius.
Vice versa, in order to minimize depletion of the substrate or article during the pause mode the second temperature level may be at most 220 degree Celsius, in particular at most 225 degree Celsius, preferably at most 215 degree Celsius, more preferably at least 205 degree Celsius. In particular, the second temperature level may be chosen such as to reduce the formation of aerosols by at least 50 percent compared to the aerosol-releasing mode.
In relative terms, the second temperature level may be lower than the first temperature level, for example by at least 50 degree Celsius, in particular at least 75 degree Celsius, more particularly at least 100 degree Celsius.
The temperature values given above preferably may be average temperatures 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.
As used herein, the pause mode may refer to a first operational mode of aerosol-generating device, in which the heating element, the heating circuitry and/or a heating arrangement may be operated during an operation pause, that is, a use pause of the aerosol-generating device, that is, when a user experience or usage session is paused and aerosol generation may not take place, or at least may be reduced to a minimum level. That is, in the pause mode the aerosol-generating device is in a use pause.
Vice versa, the aerosol-releasing mode may refer to a second operational mode of the aerosol-generating device, which is the normal heating operational mode of the heating element, circuitry, and/or arrangement for aerosol generation, in which heating element, the heating circuitry and/or a heating arrangement may be operated during use of the device by a user, that is, when a user experience or usage session takes place, in particular when aerosol generation takes place. In general, aerosol generation may take place continuously or on demand, in particular on a puff basis, that is, on demand of a user when taking a puff.
The density, weight, type and/or humidity of an aerosol-generating substrate or aerosol-generating article may be detected by the aerosol-generating device recognising, sensing and/or identifying the stick or cartridge for example through RFID or other means. As these factors may influence the energy needed for aerosol generation from the substrate or article, they may also influence battery degradation.
In an example, the usage pattern parameters collected and used in calculating the capacity degradation of the battery of the aerosol-generating device may be exclusively selected from the parameters as described above. This pertains to all described embodiments of the method, for example with at least two, at least three, at least four or more usage pattern parameters. Preferably no other parameters, for example parameters pertaining to the performance of the battery such as discharge current rate or charge current rate or voltage are employed in the method. It is one of the advantages of the invention that these parameters may not be needed, and the mentioned usage pattern parameters may be sufficient and even superior for the estimation of capacity degradation.
It has been found by the inventors that mathematical functions using the usage pattern parameters as input variables can be correlated to the battery capacity degradation. In the method according to the present disclosure, the usage pattern parameters may be combined in a linear or a quadratic or a cubic polynomial to calculate the capacity degradation. Accordingly, combining the parameters may mean considering them, for example as input variables, in a corresponding linear or a quadratic or a cubic polynomial to calculate the capacity degradation.
For instance, high accuracy with acceptable computational requirements can be achieved by fitting a third order polynomial to test data, as is explained in further detail below. Accordingly, the usage pattern parameters may be combined in a cubic polynomial or third order polynomial to calculate the capacity degradation. That the usage pattern parameters are combined in a polynomial may mean that the usage pattern parameters are used as variables or input variables in a polynomial function, wherein each usage pattern parameter may appear at least once in the polynomial. It is further preferred that each usage pattern parameter may appear at least once as a factor of the third order in the polynomial.
As already mentioned, calculating the capacity degradation of the battery of the aerosol-generating device may include predicting the capacity of the battery or the degradation of the capacity of the battery for a point in time, for example in the future. For example, the method according to the present disclosure may be used to predict the capacity of the battery or the degradation of the capacity of the battery for a point in time in the future, such as a predetermined number of days, for example 30 days or 90 days or 180 days or 365 days, in the future. In this way, the user can timely replace the battery to avoid limitations in the use of the aerosol-generating device.
To realise 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 an expected total number of usage sessions of the aerosol-generating device up to said point in time. The expected total number of usage sessions of the aerosol-generating device may refer to the total number of usage sessions the device has expectedly been operated up to said point in time.
Such an expected total number of usage sessions of the aerosol-generating device may, for example, be calculated from the usage pattern parameter number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval. Multiplying the value of this parameter by the time until the desired point in time, the expected number of usage sessions of the aerosol-generating device from the present to the point in time in the future may be obtained. For example, when the average amount of usage sessions per day is known, by multiplying this average amount by the number of days the prediction is aimed at, the expected number of usage sessions until the point in time in the future is reached may be obtained. Additionally, the result may be added to the number of usage sessions which already occurred to obtain a total of all the usage sessions of the aerosol-generating device up to the desired point in time.
The expected total number of usage sessions of the aerosol-generating device up to said point in time may be used in calculating the predicted capacity of the battery of the aerosol-generating device. The model, formula or function, for example the polynomial, used to calculate the capacity degradation of the battery of the aerosol-generating device, may therefore optionally contain time as a factor multiplied with the usage pattern parameter number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval. In this way, a meaningful result can be obtained for arbitrary points of time which may be of practical interest. By using the expected total number of usage sessions of the aerosol-generating device, the degradation of the battery may be extrapolated up to three years into the future. The method according to the present disclosure may therefore be used to evaluate extended warranty times.
However, even much shorter prediction times can be of practical value: By estimating capacity degradation, it can be determined when the battery capacity may expectedly or is expected to fall below a predetermined threshold. Such a threshold may be, for example, a total capacity or a relative capacity of the battery. Such a threshold may alternatively be measured in the number of usage sessions that can be provided by the battery when fully charged.
For example, the threshold may be defined as the average number of usage sessions a user utilises the device between two recharging events of the aerosol-generating device or the battery.
The method may optionally comprise notifying a user of the calculated capacity degradation of the battery, in particular when it is determined that the capacity of the battery will fall below a threshold in a predetermined period of time. The same may apply when it is determined that the capacity degradation of the battery will increase above a threshold in a predetermined period of time. The user may also be notified of the point in time at which the threshold will be reached. The user may then be advised that they should consider replacing the battery or to expect reduced availability of the aerosol-generating device.
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, for example a smartphone. In the latter case, the aerosol-generating device may be designed to enter into a data connection and/or to be communicatively coupled with the companion device so that the notification of the calculated capacity degradation of the battery may be transmitted to the companion device and presented on the companion device even if data collection and/or calculation is done on the aerosol-generating device.
The method as described above may be implemented using a predetermined model for the correlation between the usage pattern parameters and battery capacity degradation, represented by a model, a formula or a function (i.e. a mathematical function or formula) , such as a polynomial, for calculating the capacity degradation from usage pattern parameters. Such a predetermined model, formula or function may be determined as described in more detail below. It may be used without modifications for the whole lifetime of the aerosol-generating device. However, it may also be desirable to either have the aerosol-generating device determine a suitable formula or function automatically or to have the aerosol-generating device modify an existing formula or function, either continuously or in repeating update cycles which may be implemented with a predetermined time interval in between them. The predetermined time interval may be, for example, a week or a month or three months or six months or more. 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 for calculating the capacity degradation.
In an example, the method may further comprise: collecting battery capacity degradation data of an aerosol-generating device, preferably of a plurality of aerosol-generating devices, performing a regression analysis, preferably a nonlinear regression analysis, thereby obtaining a model, formula and/or function of a correlation between the usage pattern parameters and the battery capacity degradation data, and calculating the capacity degradation of the battery of the aerosol-generating device from current usage pattern parameters based on said model, formula and/or function. The battery capacity degradation data may pertain to measured capacity degradation that occurs in the battery of the aerosol-generating device. This may be expressed by a total remaining capacity of a fully charged battery or as a percentage of the battery capacity in relation to an initial, a nominal or a reference capacity. The battery capacity degradation data may be collected through actual use of the aerosol-generating device by a user and taking the necessary measurements. Alternatively or additionally, battery capacity degradation data may be collected from accelerated life testing (ALT) . The measurement of such battery capacity degradation data is known to the skilled person and thus does not have to be explained in further detail. If a user uses more than one aerosol-generating device, it may be advantageous to make the aerosol-generating devices at least intermittently communicatively couplable 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.
Battery capacity degradation data and preferably also usage pattern parameters may also be shared by a plurality of aerosol-generating devices across a network, for example the internet. In this way, a large amount of capacity degradation data and preferably also usage pattern parameters may be provided to increase the accuracy of the method according to the disclosure.
Through the regression analysis, the model, formula and/or function for calculating the capacity degradation from usage pattern parameters may be obtained. This model, formula or function may, for example, be the polynomial, preferably of the third order, as already discussed hereinabove.
When the model, formula or function has been obtained, it may be implemented at the device, for example in a control circuitry of the aerosol-generating device, to calculate the capacity degradation of the battery of the aerosol-generating device using current usage pattern parameters. Current usage pattern parameters may pertain to values of usage pattern parameters collected after the determination of the formula or function and which preferably were not used in this determination. From these values, the estimation of capacity degradation of the battery of the aerosol-generating device may be calculated.
The model, for example represented by the determined formula 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 further data for the usage pattern parameters from these density functions. The model may then be validated using said further data. When enough values for 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 describing said distribution, for example a probability density function.
Monte Carlo simulation relates to a method of algorithmically and repeatedly performing random sampling to obtain numerical results. This may then be used to randomly create new values for the usage pattern parameters according to their realistic distribution generated from field data. These realistic additional data may then be used to validate the model, the function and/or the formula, for example by analysing the sensitivity to each parameter’s random variation, which cannot be shown using field data alone.
According to another aspect of the present disclosure, there is provided an aerosol-generating device configured to perform steps of the method according to the disclosure herein, for example at least a subset or all of the steps of the method. The aerosol-generating device preferably comprises a battery for storing electrical energy and processing circuitry, also referred to herein as control circuitry, with one or more processors configured to perform steps of the method according to the disclosure herein, for example at least a subset or all of the steps of the method. All of the features, effects and advantages of the method according to the present disclosure are therefore also valid for and equally apply to the aerosol-generating device and vice versa.
According to another aspect of the present disclosure, there is provided an aerosol-generating system, comprising an aerosol-generating device and a companion device communicatively couplable to the aerosol-generating device, wherein the companion device is configured to perform steps of the method according to the disclosure herein, for example at least a subset or all of the steps of the method.
In an example, 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. All of the features, effects and advantages of the method or the aerosol- generating device according to the present disclosure are therefore also valid for and equally apply to the aerosol-generating system and vice versa.
A further aspect of the 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 steps of the method according to the present disclosure, as described hereinabove and hereinbelow.
A further aspect of the disclosure relates to a computer-readable medium, for example 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 steps of the method according to the present disclosure, as described hereinabove and hereinbelow.
The invention is defined in the claims. However, below there 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 another example, embodiment, or aspect described herein.
Example A: A computer-implemented method of estimating capacity degradation of a battery of an aerosol-generating device, the method comprising:
collecting at least two usage pattern parameters related to a usage of the aerosol-generating device; and
calculating, computing, determining, estimating and/or predicting a capacity degradation of the battery of the aerosol-generating device based on said at least two usage pattern parameters.
Example B: The method according to example A, wherein the usage pattern parameters are collected over a predetermined period of time.
Example C: The method according to any of the preceding examples, wherein the usage pattern parameters are mean values over a predetermined period of time.
Example D: The method according to any of the preceding examples, wherein the usage pattern parameters are indicative of different usage characteristics of the aerosol-generating device by the user.
Example E: The method according to any of the preceding examples, wherein at least one of the usage pattern parameters is indicative of the usage of the aerosol-generating device by the user to generate aerosol in one or more usage sessions.
Example F: The method according to any of the preceding examples, wherein the capacity degradation is calculated as relative decrease in the capacity of the battery with respect to one or more of an initial capacity of the battery, a nominal capacity of the battery, and a reference capacity of the battery.
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 degradation of the battery of the aerosol-generating device, each of the usage pattern parameters being indicative of different usage characteristics of the aerosol-generating device by the user.
Example H: The method according to any of the preceding examples, wherein the usage pattern parameters are selected from the parameters:
● a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,
● a duration of one or more usage sessions,
● a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between consecutive usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,
● a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between.
Example I: The method according to any of the preceding examples, wherein 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 selected from the parameters:
● a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,
● a duration of one or more usage sessions,
● a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,
● a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between.
Example J: The method according to any of the preceding examples, wherein 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 being:
● a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,
● a duration of one or more usage sessions,
● a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes, and
● a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between.
Example K: The method according to any of the preceding examples, wherein the at least two usage pattern parameters are selected from the parameters
● a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,
● a duration of one or more usage sessions,
● a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,
● a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between,
● an amount of charge-discharge cycles per predefined time interval,
● a resting time after recharging the aerosol-generating device,
● a resting time with a battery state of charge of less than 10 %,
● a resting time with a battery state of charge of more than 90 %,
● a puff volume,
● a puff frequency,
● a puff rhythm,
● a time of initiation of a pause mode at the aerosol-generating device,
● a time of termination of a pause mode at the aerosol-generating device,
● a duration of a pause mode at the aerosol-generating device,
● an ambient temperature during one or more usage sessions,
● a temperature of a heating element or heater device of the aerosol-generating device within a predefined period of time before start of a usage session,
● an ambient temperature during recharging of the battery,
● a density of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,
● a weight of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol,
● a type of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol, and
● a humidity of an aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device.
Example L: The method according to any of the preceding examples, wherein the usage pattern parameters are combined in a linear or a quadratic or a cubic polynomial to calculate the capacity degradation.
Example M: The method according to any of the preceding examples, wherein the usage pattern parameters are combined in a cubic polynomial or third order polynomial to calculate the capacity degradation.
Example N: The method according to any of the preceding examples, wherein calculating the capacity degradation of the battery of the aerosol-generating device includes predicting the capacity of the battery for a point in time.
Example O: The method according to example N, wherein the point in time to which the predicted capacity of the battery of the aerosol-generating device pertains is determined by an expected total number of usage sessions of the aerosol-generating device up to said point in time.
Example P: The method according to example O, wherein the expected total number of usage sessions of the aerosol-generating device up to said point in time is used in calculating the predicted capacity of the battery of the aerosol-generating device.
Example Q: The method according to any of the preceding examples, comprising notifying a user of the calculated capacity degradation of the battery.
Example R: The method according to any of the preceding examples, further comprising:
collecting battery capacity degradation data of an aerosol-generating device, preferably of a plurality of aerosol-generating devices,
performing a regression analysis, preferably a nonlinear regression analysis, thereby obtaining a model of a correlation between the usage pattern parameters and the battery capacity degradation data, and
calculating the capacity degradation of the battery of the aerosol-generating device from current usage pattern parameters based on said model.
Example S: The method according to example R, wherein one or more probability density functions for the usage pattern parameters are established from the collected usage pattern parameters and Monte Carlo simulation is used to generate further data for the usage pattern parameters from these density functions, and wherein the model is validated using said further data.
Example Sa: The method according to any one of the preceding examples wherein the method further comprises executing a function based on the capacity degradation.
Example Sb: The method according to example Sa wherein the function comprises generating an output signal indicative of the capacity degradation.
Example Sc: The method according to example Sa or example Sb wherein the function comprises generating an output signal indicative of a number of usage sessions available to be performed by the aerosol-generating device, wherein the number of usage sessions available is based on the capacity degradation.
Example Sd: The method according to example Sc wherein the number of usage sessions available based on the capacity degradation is less than a number of usage sessions available corresponding to one or more of an initial capacity of the battery, a nominal capacity of the battery, and a reference capacity of the battery.
Example Se: The method according to any one of examples Sa to Sd wherein the function comprises generating an output signal prompting a user to replace the battery.
Example Sf: The method according to any one of examples Sb to Se wherein the output signal is communicated via a user interface output element of an 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 perform steps of the method according to any one of the preceding examples.
Example U: The aerosol-generating device according to example T, comprising:
a battery for storing electrical energy; and
processing circuitry with one or more processors configured to perform steps of the method according to any one of examples A to S.
Example V: Aerosol-generating system, comprising an aerosol-generating device and a companion device communicatively couplable to the aerosol-generating device, wherein the companion device is configured to perform steps of the method according to any one of examples A to S.
Example W: The 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.
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 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.
Examples will now be further described with reference to the figures in which:
Figure 1 shows an aerosol-generating system comprising an aerosol-generating device and a companion device;
Figure 2 shows a probability density function for the usage pattern parameter amount of charge-discharge cycles per predefined time interval;
Figure 3 shows a probability density function for the usage pattern parameter duration of a usage session;
Figure 4 shows a probability density function for the usage pattern parameter resting time between consecutive usage sessions; and
Figure 5 shows a flow chart of the method.
The figures are schematic only and not to scale.
Figure 1 shows an aerosol-generating system 1 for generating aerosol, for example for consumption by a user in one or more usage sessions. The system 1 may comprise an aerosol-generating device 2 for generating aerosol and a companion device 3 for at least partially receiving the aerosol-generating device 2. The companion device 3 may be a charging device for charging the aerosol-generating device 2 and/or an energy storage or battery thereof.
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, such as a tobacco containing substrate, and/or a cartridge comprising a liquid.
The aerosol-generating device 2 may further include processing circuitry 5 or control circuitry 5 with one or more processors 6. For generating the aerosol during use or consumption of the aerosol-generating article 17, the aerosol-generating device 2 may comprise at least one heating element 7 or heater device for applying heat to at least a portion of the aerosol-generating article 17. The processing circuitry 5 may be configured to control actuation, activation and/or deactivation of at least one heating element 7. The processing circuitry 5 may further be configured to perform steps of the method described herein.
For powering the at least one heating element 7 with electrical power, the aerosol-generating device 2 may further comprise at least one energy storage, for example in the form of a battery 15, for storing electrical energy or power. The aerosol-generating device 2 may further comprise at least one electrical connector 12 for coupling to a corresponding at least one electrical connector 13 of the companion device 3. For example, when the aerosol-generating device 2 is at least partially inserted into the opening 14 of the companion device 3, the one or more electrical connectors 12 of the aerosol-generating device 2 may be coupled with the one or more electrical connectors 13 of the companion device 3 to charge the at least one battery 15 of the aerosol-generating device 2.
The aerosol-generating device 2 may further comprise user interface components, for example comprising an input element in the form of a pushbutton 8. The pushbutton 8 may be used as a power button to activate or deactivate the heating element 7 for aerosol generation thereby to activate or deactivate the aerosol-generating device 2. Upon activation of the aerosol-generating device 2, the heating element 7 may be activated and heat may be applied to at least a part of the aerosol-generating article 17, such that aerosol can be generated for consumption by the user, for example in a usage sessions.
The aerosol-generating device 2 may further comprise a communications arrangement 9 or communication circuitry 9 with one or more communications interfaces 10 for communicatively coupling the aerosol-generating device 2 with the companion 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.
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 to calculate the battery capacity degradation.
As described in detail hereinabove and hereinbelow, the aerosol-generating device 2 is configured to collect, gather and/or store at least two usage pattern parameters related to a usage of the aerosol-generating device 2. Further, the aerosol-generating device 2, for example the processing or control circuitry 5, is configured to calculate the capacity degradation of the battery 15 of the aerosol-generating device 2 based on said at least two usage pattern parameters.
One or more sensors 16 may be arranged on, at or in the aerosol-generating device 2 to collect data, for example usage pattern parameters and/or battery degradation data.
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 a signal to a user.
Figures 2, 3 and 4 show exemplary probability density functions for selected usage pattern parameters.
Specifically, figure 2 shows a probability density function for the usage pattern parameter number of charge-discharge cycles per predefined time interval, in this case per day. The number n of charge-discharge cycles per day is shown on the abscissa (or “horizontal-axis” ) , while the probability percentage of each number n is shown on the ordinate (or “vertical-axis” ) . The distribution reaches its highest probability around the amount of eight charge-discharge cycles per day. If the user recharges the aerosol-generating device 2 every time after a usage session, the number n of charge-discharge cycles per predefined time interval, in this case per day, is equivalent to the usage pattern parameter number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval (in this case per day) . Also in this case, the further usage pattern parameter frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between, which may alternatively be referred to as back-to-back regime, is zero. Such a usage pattern with a back-to-back regime of zero will be used in the calculation example below.
Figure 3 shows a probability density function for the usage pattern parameter duration of a usage session. The duration t₁ a usage session lasts in minutes is shown on the abscissa (or “horizontal-axis” ) with the probability percentage of each duration 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 comes first, which is why no usage sessions longer than six minutes may be recorded.
Figure 4 shows a probability density function for the usage pattern parameter resting time between consecutive usage sessions. The resting time t₂ in minutes is shown on the abscissa (or “horizontal-axis” ) with the probability percentage of each resting time shown on the ordinate (or “vertical-axis” ) . The effect of the resting time on battery degradation stems from the influence of the aerosol-generating device 2 cooling off between usage sessions. The longer the resting time, the more the aerosol-generating device 2 nears ambient temperature. It has been identified that after around forty minutes of resting time, the aerosol-generating device 2 has reached ambient temperature and any resting time longer than forty minutes has the same effect on battery degradation as a resting time of forty minutes. This may be reflected in calculating the estimated battery degradation by only changing the value of the usage pattern parameter resting time between consecutive usage sessions for resting times from zero to forty minutes and keeping the value constant for resting times of forty minutes or more.
Figure 5 shows a flow chart of the method 18 of the present disclosure according to an exemplary implementation. Using a predetermined model or formula or function respectively, the method 18 may only comprise step 19 of collecting at least two usage pattern parameters, meaning that numerical values for these parameters 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. Therefore, only steps 19 and 20 are shown in solid boxes, whereas all other optional steps are shown in dashed line boxes.
As a non-limiting example, the usage pattern parameters number of usage sessions the aerosol-generating device 2 has been operated to generate aerosol per predefined time interval (P₁) , duration of a usage session (P₂) , resting time between consecutive usage sessions (P₃) and frequency of at least two usage sessions in a row, in particular without recharging of 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 may be calculated by using the following equation:
Cap = C₀ + C₁· (P₁·k) ·P₂ + C₂· (P₁·k) ·P₃ + C₃· (P₁·k) ·P₄+C₄·P₃·P₄+C₅· (P₁·k) ³ + C₆· (P₁·k) ·P₂·P₃+C₇· (P₁·k) ·P₂·P₄ + C₈· (P₁·k) ·P₃·P₄+C₉· (P₂) ³ + C₁₀·P₂·P₃·P₄+C₁₁· (P₃) ³ + C₁₂· (P₄) ³
Wherein:
Cap is the calculated capacity degradation of the battery 15 of the aerosol-generating device 2, expressed as total remaining capacity when fully charged in mAh;
C₀ is the initial battery capacity in mAh;
P₁ is the number of usage sessions the aerosol-generating device 2 has been operated to generate aerosol per predefined time interval;
P₂ is the duration of a usage session in minutes;
P₃ is the resting time between consecutive usage sessions in minutes;
P₄ is the frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device 2 in between;
k is the period of time to which the estimated capacity degradation of the battery 15 pertains; and
C₁ to C₁₂ are constants the units of which are chosen so that each summand of the equation is expressed in mAh.
In particular, the numerical 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, C₁₀ = -17.4189, C₁₁ = -0.0299, and C₁₂ = 318.0644.
For a non-limiting example calculation, it is assumed that the initial battery capacity C₀ is 240 mAh, that the number of usage sessions the aerosol-generating device 2 has been operated to generate aerosol per day P₁ is 8, that the duration of a usage session P₂ is 6.5 minutes, that the resting time between consecutive usage sessions P₃ is 7 minutes and that the frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device 2 in between P₄ is 0, meaning that the aerosol-generating device 2 is recharged after each use. Lastly, the capacity degradation of the battery 15 after k = 90 days is calculated. Inserting these values in the above-described third order polynomial gives the calculated capacity degradation of the battery 15 of the aerosol-generating device 2 as about 236 mAh. This is the total capacity to which the fully charged battery 15 drops from the initial 240 mAh after 90 days of operation under the usage pattern described by the usage pattern parameters as entered into the equation. This is equivalent to a decrease in battery capacity of about 1.7 %.
It is important to note that the above described implementation, including the selection of usage pattern parameters, the model or formula or function and the values of the constants C₁ to C₁₂ are exemplary only. For instance, the duration of a usage session P₂ may be 6 minutes or 5.5 minutes, or another duration.
For instance, they can be determined by regression analysis, as described in more detail below and above. However, the invention could easily be implemented using a different number and/or a different selection of usage pattern parameters, a different model or formula or function and/or different values of the constants. While the given example may be a preferred way of implementing the invention, it may even be desirable to adjust the calculation to, for example, provide a higher precision in short, medium or long time frames, or to place a higher importance on usage pattern parameters that are in certain numerical value ranges and so on. There may be a multitude of possibilities of implementing the invention, meaning that the invention is not limited to the exact example given above.
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 collecting of usage pattern parameters and the calculation of the capacity degradation of the battery 15 of the aerosol-generating device 2 may be implemented by the processing circuitry 5 with its at least one processor 6, for example in conjunction with the one or more sensors 16.
After the calculation step 20, the method 18 may comprise a step 27 in which the user is notified of the calculated capacity degradation 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 degradation of the battery 15 reaches a predetermined threshold. One such threshold may be, for example, a total remaining capacity of the battery 15 of 190 mAh. This value may be of interest, as this capacity is typically barely enough for two consecutive usage sessions and values below 190 mAh may not be enough to provide two usage sessions without recharging to the user.
The method 18 may also comprise steps to provide or refine the model or formula or function used in the calculation step 20. For this purpose, it may be provided that, in a step 21, battery capacity degradation data is collected, which is representative of the battery capacity degradation of battery 15 at the time of collection. This may be done in normal usage of the aerosol-generating device 2 in the field or the battery capacity degradation data may alternatively be collected by employing accelerated life testing (ALT) of the aerosol-generating device 2. A step 22 may be performed simultaneously or in parallel, in which usage pattern parameters are collected either from the usage of the aerosol-generating device 2 in the field or from ALT. From the data collected in steps 21 and 22, a regression analysis, preferably a non-linear regression analysis, may be performed in a 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 in a model or formula or function, preferably a third order or cubic polynomial. As an example, the equation given above in the example calculation was determined in this way. After step 23, when the model or formula or function is established, the method 18 may calculate future battery degradation from current usage pattern parameters collected in step 19 as explained above.
In another aspect, the disclosure may provide a way of validating the model or formula or function and therefore showing the effects of the variations of each of the variables of the model or formula or function more clearly than with limited field and/or ALT data. For this purpose, in a step 24, probability density functions for each of the usage pattern parameters are established. Examples of such functions for selected parameters are shown in figures 2, 3 and 4. These functions have the advantage over clouds of single data points that they may be used to create a large number of randomly selected values for the usage pattern parameter in question through random sampling employed by the Monte Carlo simulation in step 25. The data thus generated still adheres to the distributions of the usage pattern parameters observed in the field and/or ALT and therefore presents plentiful data that is still realistic for the specific use case. The large data set that can be created in this way may then, in a step 26, be used to validate the model or formula or function. It is also envisioned that the validation in step 26 may lead to an adjustment or fine tuning of the model or formula or function, and that the validated or adjusted model or formula or function may be employed in the calculation according to step 20.
For the purpose of the present description and of the appended claims, except where otherwise indicated, all numbers expressing amounts, quantities, percentages, and so forth, are to be understood as being modified in all instances by the term "about". Also, all ranges include the maximum and minimum points disclosed and include any intermediate ranges therein, which may or may not be specifically enumerated herein. In this context, therefore, a number A is understood as A ± 10 %of A. Within this context, a number A may be considered to include numerical values that are within general standard error for the measurement of the property that the number A modifies. The number A, in some instances as used in the appended claims, may deviate by the percentages enumerated above provided that the amount by which A deviates does not materially affect the basic and novel characteristic (s) of the claimed invention. Also, all ranges include the maximum and minimum points disclosed and include any intermediate ranges therein, which may or may not be specifically enumerated herein.

Claims

A computer-implemented method of estimating capacity degradation of a battery of an aerosol-generating device, the method comprising:

collecting at least two usage pattern parameters related to a usage of the aerosol-generating device; and

calculating a capacity degradation of the battery of the aerosol-generating device based on said at least two usage pattern parameters.
The method according to claim 1, wherein the usage pattern parameters are collected over a predetermined period of time and/or are mean values over a predetermined period of time.
The method according to any of the preceding claims, wherein at least one of the usage pattern parameters is indicative of the usage of the aerosol-generating device by the user to generate aerosol in one or more usage sessions.
The method according to any of the preceding claims, 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 being indicative of different usage characteristics of the aerosol-generating device by the user.
The method according to any of the preceding claims, wherein the usage pattern parameters are selected from the parameters:

· a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,

· a duration of one or more usage sessions,

· a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between consecutive usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,

· a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between.
The method according to any of the preceding claims, wherein 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 selected from the parameters:

· a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,

· a duration of one or more usage sessions,

· a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,

· a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between.
The method according to any of the preceding claims, wherein 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 being:

· a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,

· a duration of one or more usage sessions,

· a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes, and

· a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between.
The method according to any of the preceding claims, wherein the at least two usage pattern parameters are selected from the parameters

· a number of usage sessions the aerosol-generating device has been operated to generate aerosol per predefined time interval,

· a duration of one or more usage sessions,

· a resting time between consecutive usage sessions, preferably wherein the usage pattern parameter value pertaining to the resting time between subsequent usage sessions only varies for resting times between subsequent usage sessions of from 0 to 40 minutes,

· a frequency of at least two usage sessions in a row, in particular without recharging of the aerosol-generating device in between,

· an amount of charge-discharge cycles per predefined time interval,

· a resting time after recharging the aerosol-generating device,

· a resting time with a battery state of charge of less than 10 %,

· a resting time with a battery state of charge of more than 90 %,

· a puff volume,

· a puff frequency,

· a puff rhythm,

· a time of initiation of a pause mode at the aerosol-generating device,

· a time of termination of a pause mode at the aerosol-generating device,

· a duration of a pause mode at the aerosol-generating device,

· an ambient temperature during one or more usage sessions,

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

· an ambient temperature during recharging of the battery,

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

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

· a type of an aerosol-generating substrate or aerosol-generating article used with the aerosol-generating device to generate aerosol, and

· a humidity of an aerosol-generating substrate or aerosol-generating article used in the aerosol-generating device.
The method according to any of the preceding claims, wherein the usage pattern parameters are combined in a linear or a quadratic or a cubic polynomial to calculate the capacity degradation.
The method according to any of the preceding claims, wherein the usage pattern parameters are combined in a cubic polynomial or third order polynomial to calculate the capacity degradation.
The method according to any of the preceding claims, wherein calculating the capacity degradation of the battery of the aerosol-generating device includes predicting the capacity of the battery for a point in time.
The method according to claim 11, wherein the point in time to which the predicted capacity of the battery of the aerosol-generating device pertains is determined by an expected total number of usage sessions of the aerosol-generating device up to said point in time, preferably wherein the expected total number of usage sessions of the aerosol-generating device up to said point in time is used in calculating the predicted capacity of the battery of the aerosol-generating device.
The method according to any of the preceding claims, comprising notifying a user of the calculated capacity degradation of the battery.
An aerosol-generating device configured to perform steps of the method according to any one of the preceding claims.
Aerosol-generating system, comprising an aerosol-generating device and a companion device communicatively couplable to the aerosol-generating device, wherein the companion device is configured to perform steps of the method according to any one of claims 1 to 13.