JPWO2022013386A5 - - Google Patents
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- JPWO2022013386A5 JPWO2022013386A5 JP2023501263A JP2023501263A JPWO2022013386A5 JP WO2022013386 A5 JPWO2022013386 A5 JP WO2022013386A5 JP 2023501263 A JP2023501263 A JP 2023501263A JP 2023501263 A JP2023501263 A JP 2023501263A JP WO2022013386 A5 JPWO2022013386 A5 JP WO2022013386A5
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- 238000010438 heat treatment Methods 0.000 claims 47
- SNICXCGAKADSCV-JTQLQIEISA-N (-)-Nicotine Chemical compound CN1CCC[C@H]1C1=CC=CN=C1 SNICXCGAKADSCV-JTQLQIEISA-N 0.000 claims 31
- 229960002715 nicotine Drugs 0.000 claims 31
- SNICXCGAKADSCV-UHFFFAOYSA-N nicotine Natural products CN1CCCC1C1=CC=CN=C1 SNICXCGAKADSCV-UHFFFAOYSA-N 0.000 claims 31
- 238000013528 artificial neural network Methods 0.000 claims 12
- 238000000034 method Methods 0.000 claims 9
- 238000012544 monitoring process Methods 0.000 claims 5
- 238000009472 formulation Methods 0.000 claims 4
- 239000000203 mixture Substances 0.000 claims 4
- 230000003044 adaptive effect Effects 0.000 claims 2
- 230000006978 adaptation Effects 0.000 claims 1
Claims (20)
ニコチンプレベイパー製剤を含有する貯蔵部と、
前記貯蔵部から引き出されたニコチンプレベイパー製剤を加熱するように構成された発熱体と、
制御回路であって、
前記ニコチンＥＶＤへの陰圧の第一の印加後の第一の期間にわたって、前記発熱体の抵抗値をモニターするように、
訓練されたニューラルネットワークを使用して、前記モニターされた抵抗値に基づいて、前記第一の陰圧の印加に対する前記発熱体の推定最小定常状態抵抗値を決定するように、かつ
前記第一の陰圧の印加に対する前記推定最小定常状態抵抗値に基づいて、前記発熱体への電力を制御するように構成された制御回路と、を備えるニコチンＥＶＤ。 1. A nicotine electronic vaping device (EVD), comprising:
A reservoir containing a nicotine prevapor formulation;
a heating element configured to heat the nicotine pre-vapor formulation drawn from the reservoir;
A control circuit comprising:
monitoring a resistance value of the heating element for a first period of time following a first application of a negative pressure to the nicotine EVD;
a control circuit configured to determine, using a trained neural network, an estimated minimum steady state resistance value of the heating element in response to application of the first negative pressure based on the monitored resistance value; and a control circuit configured to control power to the heating element based on the estimated minimum steady state resistance value in response to application of the first negative pressure.
前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値に基づいて、前記ニコチンＥＶＤでのドライ吸煙状態を検出するように、かつ
前記検出されたドライ吸煙状態に応答して前記発熱体への電力を無効にするようにさらに構成されている、請求項１に記載のニコチンＥＶＤ。 The control circuit,
The nicotine EVD of claim 1, further configured to detect a dry puff state in the nicotine EVD based on the estimated minimum steady state resistance value of the heating element to the application of the first negative pressure; and to disable power to the heating element in response to the detected dry puff state.
前記ニコチンＥＶＤへの陰圧の第二の印加の検出に応答して前記発熱体に電力が印加されることを防止するようにさらに構成されている、請求項２に記載のニコチンＥＶＤ。 The control circuit
The nicotine EVD of claim 2 , further configured to prevent power from being applied to the heating element in response to detecting a second application of negative pressure to the nicotine EVD.
前記発熱体の前記抵抗値を、
前記第一の期間中に前記発熱体のピーク抵抗値を決定することと、
前記第一の期間中に前記決定されたピーク抵抗値の後の時点にて、前記発熱体の少なくとも一つの追加的な抵抗値を決定することと、によってモニターするように、かつ
前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を、
前記ピーク抵抗値および前記少なくとも一つの追加的な抵抗値に基づいて、前記訓練されたニューラルネットワークを使用して前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を推定することによって決定するように構成されている、請求項１、請求項２または請求項３に記載のニコチンＥＶＤ。 The control circuit,
The resistance value of the heating element is
determining a peak resistance of the heating element during the first period of time;
determining at least one additional resistance value of said heating element at a time subsequent to said determined peak resistance value during said first period of time; and
the estimated minimum steady state resistance of the heating element in response to application of the first negative pressure;
The nicotine EVD of claim 1, claim 2 or claim 3, configured to determine by estimating the estimated minimum steady-state resistance value of the heating element in response to application of the first negative pressure using the trained neural network based on the peak resistance value and the at least one additional resistance value.
前記ピーク抵抗値および前記少なくとも一つの追加的な抵抗値を入力値として受信するように、
前記第一の期間にわたる前記入力値の減衰を決定するように、かつ
前記第一の期間にわたる前記発熱体の前記抵抗値の前記決定された減衰の結果に基づいて、前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を出力するように構成された機能適合ネットワークである、請求項４に記載のニコチンＥＶＤ。 The trained neural network comprises:
receiving the peak resistance value and the at least one additional resistance value as input values;
The nicotine EVD of claim 4, wherein the functionally adaptive network is configured to determine a decay of the input value over the first period of time, and to output the estimated minimum steady state resistance value of the heating element in response to application of the first negative pressure based on the determined decay of the resistance value of the heating element over the first period of time.
前記第二の抵抗値が、前記ピーク抵抗値が決定される前記時点に続く時点にて、かつ前記第三の抵抗値が決定される前に決定され、
前記第三の抵抗値が、前記第二の抵抗値が決定される前記時点に続く時点にて、かつ陰圧の第二の印加を検出する前に決定される、請求項６に記載のニコチンＥＶＤ。 the at least one additional resistance value includes at least a second resistance value and a third resistance value;
the second resistance value is determined at a time subsequent to the time at which the peak resistance value is determined and before the third resistance value is determined;
The nicotine EVD of claim 6, wherein the third resistance value is determined at a time subsequent to the time at which the second resistance value is determined and prior to detecting a second application of negative pressure.
前記制御回路が、
前記第一の期間にわたって前記発熱体に対応する可変抵抗値を検出するように、
前記第一の期間にわたって前記ホイートストンブリッジ回路に対応する抵抗値を検出するように、かつ
前記発熱体に対応する前記検出された可変抵抗値と、前記ホイートストンブリッジ回路に対応する前記検出された抵抗値とに基づいて、前記訓練されたニューラルネットワークを使用して前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を推定するようにさらに構成されている、請求項１～７のいずれかに記載のニコチンＥＶＤ。 the heating element is connected to a Wheatstone bridge circuit, and the control circuit is
detecting a variable resistance value corresponding to the heating element over the first time period;
The nicotine EVD of any one of claims 1 to 7, further configured to detect a resistance value corresponding to the Wheatstone bridge circuit over the first time period, and to estimate the estimated minimum steady state resistance value of the heating element in response to application of the first negative pressure using the trained neural network based on the detected variable resistance value corresponding to the heating element and the detected resistance value corresponding to the Wheatstone bridge circuit.
前記ニコチンＥＶＤの制御回路を使用して、前記ニコチンＥＶＤへの陰圧の第一の印加後の第一の期間にわたって、前記ニコチンＥＶＤ内に含まれる発熱体の抵抗値をモニターすることと、
前記制御回路を使用して、訓練されたニューラルネットワークを使用して、前記モニターされた抵抗値に基づいて、前記第一の陰圧の印加に対する前記発熱体の推定最小定常状態抵抗値を決定することと、
前記制御回路を使用して、前記第一の陰圧の印加に対する前記推定最小定常状態抵抗値に基づいて、前記発熱体への電力を制御することと、を含む方法。 1. A method of operating a nicotine electronic vaping device (EVD), comprising:
monitoring a resistance value of a heating element contained within the nicotine EVD for a first period of time following a first application of a negative pressure to the nicotine EVD using a control circuit of the nicotine EVD;
determining, using the control circuitry, an estimated minimum steady state resistance value of the heating element in response to application of the first negative pressure based on the monitored resistance value using a trained neural network;
and controlling power to the heating element based on the estimated minimum steady state resistance value to the application of the first negative pressure using the control circuit.
前記制御回路を使用して、前記検出されたドライ吸煙状態に応答して前記発熱体への電力を無効にすることと、をさらに含む、請求項９に記載の方法。 detecting a dry puff state with the nicotine EVD based on the estimated minimum steady state resistance of the heating element to the application of the first negative pressure using the control circuit;
10. The method of claim 9, further comprising: using the control circuitry to disable power to the heating element in response to the detected dry puff condition.
前記制御回路を使用して、前記ニコチンＥＶＤへの陰圧の前記第二の印加を検出することに応答して前記発熱体に電力が印加されることを防止することと、をさらに含む、請求項１０に記載の方法。 detecting a second application of negative pressure to the nicotine EVD using the control circuit;
The method of claim 10, further comprising: using the control circuit to prevent power from being applied to the heating element in response to detecting the second application of negative pressure to the nicotine EVD.
前記第一の期間中に前記発熱体のピーク抵抗値を決定することと、
前記第一の期間中に前記決定されたピーク抵抗値の後の時点にて、前記発熱体の少なくとも一つの追加的な抵抗値を決定することと、を含み
前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を決定することが、前記ピーク抵抗値および前記少なくとも一つの追加的な抵抗値に基づいて、前記訓練されたニューラルネットワークを使用して前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を推定することを含む、請求項９、請求項１０、または請求項１１に記載の方法。 monitoring the resistance of the heating element,
determining a peak resistance of the heating element during the first period of time;
determining at least one additional resistance value of the heating element at a time subsequent to the determined peak resistance value during the first time period.
12. The method of claim 9, claim 10, or claim 11, wherein determining the estimated minimum steady state resistance value of the heating element in response to the application of the first negative pressure comprises estimating the estimated minimum steady state resistance value of the heating element in response to the application of the first negative pressure using the trained neural network based on the peak resistance value and the at least one additional resistance value.
前記方法が、
前記制御回路を使用して、前記ピーク抵抗値および前記少なくとも一つの追加的な抵抗値を入力値として受信することと、
前記制御回路を使用して、前記第一の期間にわたる前記発熱体の前記抵抗値の減衰を決定することと、
前記制御回路を使用して、前記第一の期間にわたる、前記発熱体の前記抵抗値の前記決定された減衰の結果に基づいて、前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を出力することと、をさらに含む、請求項１２に記載の方法。 the trained neural network is a functional adaptation network, and the method comprises:
receiving, using the control circuit, the peak resistance value and the at least one additional resistance value as input values;
determining, using the control circuitry, a decay in the resistance of the heating element over the first period of time;
13. The method of claim 12, further comprising: using the control circuitry to output the estimated minimum steady state resistance value of the heating element in response to application of the first negative pressure based on the determined decay in the resistance value of the heating element over the first time period.
前記第二の抵抗値が、前記ピーク抵抗値が決定される前記時点に続く時点にて、かつ前記第三の抵抗値が決定される前に決定され、
前記第三の抵抗値が、前記第二の抵抗値が決定される前記時点に続く時点にて、かつ陰圧の第二の印加を検出する前に決定される、請求項１４に記載の方法。 the at least one additional resistance value includes at least a second resistance value and a third resistance value;
the second resistance value is determined at a time subsequent to the time at which the peak resistance value is determined and before the third resistance value is determined;
15. The method of claim 14, wherein the third resistance value is determined at a time subsequent to the time the second resistance value is determined and prior to detecting a second application of negative pressure.
前記制御回路を使用して、前記第一の期間にわたってホイートストンブリッジ回路に対応する抵抗値を検出することと、
前記制御回路を使用して、前記発熱体に対応する前記検出された可変抵抗値と、前記ホイートストンブリッジ回路に対応する前記検出された抵抗値とに基づいて、前記訓練されたニューラルネットワークを使用して前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を推定することと、をさらに含む、請求項９～１５のいずれかに記載の方法。 detecting a variable resistance value corresponding to the heating element over the first period of time using the control circuit;
detecting a resistance value corresponding to a Wheatstone bridge circuit over the first time period using the control circuit;
16. The method of claim 9, further comprising: using the control circuit to estimate the estimated minimum steady state resistance value of the heating element in response to application of the first negative pressure using the trained neural network based on the detected variable resistance value corresponding to the heating element and the detected resistance value corresponding to the Wheatstone bridge circuit.
ニコチンプレベイパー製剤を含有する貯蔵部と、
前記貯蔵部から引き出されたニコチンプレベイパー製剤を加熱するように構成された発熱体と、
ヒーター抵抗モニタリング回路であって、
前記ニコチンＥＶＤへの陰圧の第一の印加後の第一の期間中の前記発熱体のピーク抵抗値を決定するように、かつ
前記第一の期間中の前記発熱体の少なくとも一つの追加的な抵抗値を決定するように構成されたヒーター抵抗モニタリング回路と、
訓練されたニューラルネットワークであって、
前記決定されたピーク抵抗値と前記決定された少なくとも一つの追加的な抵抗値とに基づいて、前記第一の期間中の前記第一の陰圧の印加に対する前記発熱体の最小定常状態抵抗値を推定するように構成された訓練されたニューラルネットワークと、
前記第一の陰圧の印加に対する前記推定最小定常状態抵抗値に基づいて、前記発熱体への電力を無効にするように構成された制御回路と、を備える、ニコチンＥＶＤ。 1. A nicotine electronic vaping device (EVD), comprising:
A reservoir containing a nicotine prevapor formulation;
a heating element configured to heat the nicotine pre-vapor formulation drawn from the reservoir;
1. A heater resistance monitoring circuit, comprising:
a heater resistance monitoring circuit configured to determine a peak resistance value of the heating element during a first time period after a first application of negative pressure to the nicotine EVD; and to determine at least one additional resistance value of the heating element during the first time period.
A trained neural network,
a trained neural network configured to estimate a minimum steady state resistance value of the heating element for application of the first negative pressure during the first time period based on the determined peak resistance value and the determined at least one additional resistance value;
A control circuit configured to disable power to the heating element based on the estimated minimum steady state resistance value to the application of the first negative pressure.
前記制御回路が、前記検出されたドライ吸煙状態に応答して前記発熱体への前記電力を無効にするようにさらに構成されている、請求項１７に記載のニコチンＥＶＤ。 the trained neural network is further configured to detect a dry puff state with the nicotine EVD based on the estimated minimum steady state resistance value of the heating element to the application of the first negative pressure;
20. The nicotine EVD of claim 17, wherein the control circuitry is further configured to disable the power to the heating element in response to the detected dry puff condition.
前記ピーク抵抗値および前記少なくとも一つの追加的な抵抗値を入力値として受信するように、
前記第一の期間にわたる前記入力値の減衰を決定するように、かつ
前記第一の期間にわたる前記発熱体の前記抵抗値の前記決定された減衰の結果に基づいて、前記第一の陰圧の印加に対する前記発熱体の前記推定最小定常状態抵抗値を出力するように構成された機能適合ネットワークである、請求項１７または請求項１８に記載のニコチンＥＶＤ。 The trained neural network comprises:
receiving the peak resistance value and the at least one additional resistance value as input values;
The nicotine EVD of claim 17 or claim 18, wherein the functionally adaptive network is configured to determine a decay of the input value over the first period of time, and to output the estimated minimum steady state resistance value of the heating element to the application of the first negative pressure based on the result of the determined decay of the resistance value of the heating element over the first period of time.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/929,689 US11744285B2 (en) | 2020-07-15 | 2020-07-15 | Steady state resistance estimation for overheating protection of a nicotine e-vaping device |
| US16/929,689 | 2020-07-15 | ||
| PCT/EP2021/069840 WO2022013386A1 (en) | 2020-07-15 | 2021-07-15 | Steady state resistance estimation for overheating protection of a nicotine e-vaping device |
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| JP2023534654A JP2023534654A (en) | 2023-08-10 |
| JPWO2022013386A5 true JPWO2022013386A5 (en) | 2024-07-09 |
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| Country | Link |
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| US (2) | US11744285B2 (en) |
| EP (1) | EP4181716B1 (en) |
| JP (1) | JP2023534654A (en) |
| KR (1) | KR20230038725A (en) |
| CN (1) | CN115776851A (en) |
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| US20220015443A1 (en) * | 2020-07-15 | 2022-01-20 | Altria Client Services Llc | Steady state resistance estimation for overheating protection of a non-nicotine e-vaping device |
| US11744285B2 (en) | 2020-07-15 | 2023-09-05 | Altria Client Services Llc | Steady state resistance estimation for overheating protection of a nicotine e-vaping device |
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2020
- 2020-07-15 US US16/929,689 patent/US11744285B2/en active Active
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2021
- 2021-07-15 CN CN202180048721.8A patent/CN115776851A/en active Pending
- 2021-07-15 KR KR1020237003852A patent/KR20230038725A/en unknown
- 2021-07-15 EP EP21743515.5A patent/EP4181716B1/en active Active
- 2021-07-15 WO PCT/EP2021/069840 patent/WO2022013386A1/en active Search and Examination
- 2021-07-15 JP JP2023501263A patent/JP2023534654A/en active Pending
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2023
- 2023-07-25 US US18/358,531 patent/US20230363445A1/en active Pending
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