Electronic cigarette taste control method and system

By collecting and modeling data in real time to adjust the atomization and airflow parameters of e-cigarettes, the problems of poor flavor consistency and inaccurate parameter adjustment in existing technologies have been solved, enabling personalized flavor control and multi-filler adaptation, thus improving the user experience.

CN122123535APending Publication Date: 2026-06-02深圳市特伯雷电子有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
深圳市特伯雷电子有限公司
Filing Date
2026-04-23
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing e-cigarettes have a single method for controlling flavor, which cannot be dynamically adjusted according to the characteristics of e-liquid, smoking habits and environmental conditions. This results in poor flavor consistency, inaccurate parameter adjustment, inability to adapt to multi-liquid tank scenarios, and a lack of real-time feedback mechanism, which affects the user experience.

Method used

By collecting electronic cigarette operating parameters in real time, a flavor control model is established, atomization and airflow parameters are dynamically adjusted, a collaborative correlation model of atomization and airflow is constructed, and personalized flavor control is achieved by combining closed-loop feedback optimization.

Benefits of technology

It improves the consistency and stability of taste, reduces taste differences and the incidence of defects, meets the needs of multi-oil tank scenarios, and enhances user experience and product adaptability.

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Abstract

This invention discloses a method and system for controlling the flavor of electronic cigarettes, specifically relating to the field of electronic cigarette flavor control technology. By real-time collection of parameters such as e-liquid, environment, and device status, it dynamically adjusts atomization and airflow control parameters to avoid flavor differences caused by fixed parameters. Simultaneously, closed-loop feedback optimization ensures flavor consistency between batches and throughout the inhalation process. By constructing a collaborative correlation model of atomization and airflow parameters, it achieves precise matching between the two. Furthermore, through multi-parameter coupling modeling, it improves parameter adjustment accuracy, enabling precise flavor control without manual user adjustment. By real-time monitoring of parameter changes, it automatically adapts to flavor requirements under different environments and e-liquid states. It supports multi-tank e-liquid mixing and precise customization by controlling the atomization parameter ratios of each tank, meeting diverse and personalized flavor needs of consumers.
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