CN-122018600-A - Self-adaptive control method and system for temperature of liquid in heating cup based on artificial intelligence

CN122018600ACN 122018600 ACN122018600 ACN 122018600ACN-122018600-A

Abstract

The application discloses an artificial intelligence-based self-adaptive control method and system for the temperature of liquid in a heating cup. The heating cup comprises an intelligent liquid container. The method comprises the steps of obtaining and analyzing digital schedule data of a user to predict a drinking window and a non-drinking window, calculating thermal inertia characteristics of liquid in the intelligent liquid container by monitoring the temperature change rate of the liquid to identify the liquid type, integrating the predicted window and the identified liquid type, generating and executing dynamic temperature control logic, controlling a heating circuit to enter a low-power consumption mode during the non-drinking window, and adjusting the liquid temperature to a target drinking temperature matched with the liquid type before the drinking window arrives. The application can realize the noninductive self-adaptive control of the temperature according to the schedule of the user and the type of the liquid, and optimize the energy efficiency of the equipment and enhance the use safety while improving the user experience.

Inventors

ZHONG HONGWEI
YANG GUANGYU
LI YANAN
HANG WENBIN
XU XIAOGANG
FENG XU
GUO XUE

Assignees

中烨能源(北京)有限公司
杭州日行迹科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (10)

1. The utility model provides a temperature rising cup liquid temperature self-adaptation control method based on artificial intelligence, the temperature rising cup includes an intelligent liquid container, its characterized in that includes: Based on the digital schedule data of the user, a predicted drinking water window and a predicted non-drinking water window are obtained; monitoring the temperature change rate of the target liquid in the intelligent liquid container when the target liquid in the intelligent liquid container is heated by applying preset power through a temperature sensor and a heating circuit which are arranged in the intelligent liquid container; Calculating to obtain the thermal inertia characteristic of the target liquid based on the temperature change rate, and identifying the liquid type of the target liquid according to the thermal inertia characteristic to obtain the identified liquid type; generating and executing dynamic temperature control logic integrating the predicted drinking window, the predicted non-drinking window, and the identified liquid type, the dynamic temperature control logic comprising: controlling the heating circuit to enter a low power consumption mode during the non-drinking window; And driving the heating circuit in a preset advance time before the drinking window arrives, and adjusting the temperature of the liquid to a target drinking temperature matched with the type of the liquid.
2. The method according to claim 1, wherein the step of calculating a thermal inertia characteristic of the target liquid based on the temperature change rate and identifying a liquid type of the target liquid based on the thermal inertia characteristic specifically comprises: Controlling the heating circuit to constant test power Heating the target liquid for a preset test period ; Acquiring an initial temperature at the beginning of heating by the temperature sensor And end temperature at the end of heating ; Calculating the temperature variation And defines the rate of temperature change as ; Comparing the calculated temperature change rate with a preset mapping database, wherein the mapping database stores a plurality of liquid types and temperature change rate threshold intervals corresponding to the liquid types, and determining the target liquid type by judging the interval in which the temperature change rate falls.
3. The method of claim 2, wherein the temperature change rate threshold interval in the map database is dynamic, a specific value of which is equal to a current ambient temperature measured by the temperature sensor prior to execution of the method And the triggering condition of the step of identifying the type of liquid is that the temperature sensor detects that the temperature of the target liquid falls within a specified time window by more than a preset temperature dip threshold Or a liquid level sensor built in the intelligent liquid container detects that the liquid level is changed beyond a preset filling threshold value, so that the occurrence of a target liquid refilling event is judged.
4. The method of claim 1, wherein the dynamic temperature control logic divides the operational state of the intelligent liquid container into at least three, A sleep state, wherein the intelligent liquid container enters the sleep state during the non-drinking window, and the average working power of the heating circuit is controlled to be a preset sleep power threshold value The following are set forth; A ready state, the intelligent liquid container entering the ready state within the preset advance time before the drinking window arrives, the heating circuit being activated to heat the liquid temperature from a current temperature to the target drinking temperature; And the intelligent liquid container enters the heat preservation state during the drinking window, and the heating circuit works in a pulse or variable power mode to maintain the liquid temperature within a preset temperature floating range near the target drinking temperature.
5. The method of claim 4, wherein the preset advance time in the ready state Is generated according to the dynamic calculation of the current equipment state, and the calculation mode is as follows: ; Wherein, the For the target drinking temperature to be described, To enter a ready state the current liquid temperature as measured by the temperature sensor, Rated heating power for the heating circuit; A current liquid mass estimated based on a liquid level sensor reading within the smart liquid container; a specific heat capacity coefficient value corresponding to the liquid type identified according to the method of claim 1; is a preset buffering time.
6. The method of claim 1, wherein the step of obtaining a predicted drinking water window and a predicted non-drinking water window based on the digital schedule data of the user, comprises: Based on digital schedule data of a user, extracting event text, a time interval and a position label in the digital schedule data; the method comprises the steps of mapping an event text into a disturbance index of an event, constructing a multidimensional feature vector by combining historical event drinking frequency of the same type of user and a position change state corresponding to a position label, inputting the multidimensional feature vector into a pre-trained time sequence prediction model, and outputting drinking probability prediction values of all time slices in the future; The method further comprises the steps of extracting event types in schedule data, marking a time period covered by the event as a non-drinking window when the event types are analyzed to be conferences, reports or driving, and marking the time period covered by the event as a drinking window when the event types are independent office, noon break or no day Cheng Liubai.
7. The method of claim 1, further comprising querying a reading of a level sensor disposed within the smart liquid container prior to executing the instructions to drive the heating circuit, and executing the drive instructions to the heating circuit only if the reading of the level sensor indicates that the current liquid level is above a preset minimum safe liquid level threshold.
8. The method of claim 7, wherein the minimum safe level threshold is variable, the method further comprising invoking a corresponding safe level threshold from a lookup table based on the liquid type after identifying the liquid type, invoking a higher safe level threshold for the liquid type identified as high volatility or low boiling point to reserve a larger safe space at the top of the container.
9. The method of claim 1, further comprising monitoring the attitude and micro-vibration of the container by an inertial measurement unit disposed within the intelligent liquid container to identify a drinking action by the user, and determining a valid drinking action when the container tilt is detected to exceed a preset tilt threshold for more than a preset time.
10. Temperature rising cup liquid temperature self-adaptive control system based on artificial intelligence, including an intelligent liquid container, its characterized in that includes: the cloud server is internally provided with a schedule analysis module which is used for acquiring and analyzing digital schedule data of a user so as to predict future drinking windows and non-drinking windows; An intelligent liquid container, the intelligent liquid container comprising: The communication module is used for communicating with the cloud server; A temperature sensor for monitoring the temperature of the liquid in the container; a heating circuit for heating the liquid; A processor electrically connected to the communication module, the temperature sensor, and the heating circuit, the processor configured to, Receiving the drinking window and non-drinking window information sent by the cloud server; controlling the heating circuit to apply power, and calculating the thermal inertia characteristic of the liquid based on temperature data fed back by the temperature sensor so as to identify the type of the liquid; And integrating the drinking window, the non-drinking window and the identified liquid type, controlling the heating circuit to enter a low-power consumption mode during the non-drinking window, and driving the heating circuit to adjust the liquid temperature to a target drinking temperature matched with the liquid type before the drinking window arrives.

Description

Self-adaptive control method and system for temperature of liquid in heating cup based on artificial intelligence Technical Field The application relates to the field of data processing and automatic control, in particular to an artificial intelligence-based self-adaptive control method and system for the temperature of liquid in a heating cup, which are applied to office and health management scenes. Background In modern fast paced office environments, the drinking behavior of users often presents a high degree of fragmentation and uncertainty. Existing smart liquid containers, such as smart water cups, typically employ a "fixed set point constant temperature" mode of operation, e.g., a preset and constant maintenance of temperature at 55 ℃. However, such modes have significant drawbacks. First, this mode ignores the user's specific schedule. When the user is in a state of meeting or going out and the like and can not drink water, the water cup can still continuously heat and preserve heat of the internal liquid, so that unnecessary electric energy consumption is caused, and the endurance time of the portable device which depends on battery power supply is shortened. Second, this mode lacks the ability to perceive the properties of the liquid within the container. The user may add different kinds of beverages to the container, such as instant coffee that needs to be brewed with hot water at 85 ℃, or tea that needs to be tasted at a specific temperature. The traditional constant temperature mode cannot identify the liquid type and match the optimal temperature, and if the system still maintains the temperature at the preset 55 ℃, insufficient brewing of the beverage may result, severely affecting the mouthfeel and drinking experience. The prior art typically relies on manual temperature adjustment by a user through a smart phone application or physical keys on the container body. The interaction mode of the human adaptation equipment increases the operation burden and the cognitive load of a user, and is contrary to the development trend of automation and non-sensitivity of intelligent equipment. Furthermore, conventional temperature control algorithms, such as proportional-integral-derivative control, adjust based on just the difference between the current liquid temperature and the target temperature, lack the ability to predict future behavior of the user. This results in a significant time lag between the user's immediate needs and the system's response, failing to implement a "predictive" intelligent service. Therefore, how to solve the problem that the existing intelligent liquid container cannot dynamically adjust the temperature control method according to the schedule state and the liquid characteristics of the user, so that the energy efficiency is low and the drinking experience is poor is a technical problem to be solved by the person skilled in the art. Disclosure of Invention The invention mainly aims to provide an artificial intelligence-based self-adaptive control method and system for the liquid temperature of a heating cup, which are used for solving the problems that the traditional intelligent water cup cannot dynamically adjust the temperature control method according to the schedule state and the liquid characteristics of a user, so that the energy efficiency is low and the drinking experience is poor. The invention provides an artificial intelligence-based self-adaptive control method for the temperature of a heating cup liquid, which comprises the steps of obtaining a predicted drinking window and a predicted non-drinking window based on digital schedule data of a user, monitoring the temperature change rate of the liquid when preset power is applied to the liquid in an intelligent liquid container through a temperature sensor and a heating circuit which are arranged in the intelligent liquid container, calculating the thermal inertia characteristic of the liquid based on the temperature change rate, identifying the liquid type of the liquid according to the thermal inertia characteristic, and generating and executing dynamic temperature control logic by integrating the predicted drinking window, the non-drinking window and the identified liquid type, wherein the dynamic temperature control logic comprises the steps of controlling the heating circuit to enter a low power consumption mode during the non-drinking window, driving the heating circuit to adjust the temperature of the liquid to a target drinking temperature matched with the liquid type within a preset advance time before the drinking window arrives. The invention further provides an artificial intelligence-based self-adaptive control system for the temperature of the liquid of the heating cup, which comprises a cloud server, an intelligent liquid container, a temperature sensor, a heating circuit and a processor, wherein the cloud server is internally provided with a schedule analysis module, the schedule analysis module i