Electric ceramic cooker energy efficiency optimization method and device based on cooking behaviors, equipment and medium

Abstract

The invention relates to an electric ceramic cooker energy efficiency optimization method and device based on cooking behaviors, equipment and a medium, and the method comprises the steps: obtaining heating temperature data, calculating a temperature change rate and a temperature fluctuation amplitude according to the heating temperature data, and recognizing the attribute information of cookware; based on the temperature change rate, the temperature fluctuation amplitude and the pot attribute information, the current cooking stage of the electric ceramic cooker is recognized, and then the heating power of the electric ceramic cooker is dynamically adjusted according to the cooking stage; running state data in the heating process are obtained in real time, the current instantaneous power of the radiant cooker is calculated based on the running state data, and accumulated energy consumption is calculated according to the instantaneous power accumulation; and after cooking is completed, comparing the accumulated energy consumption with preset standard energy consumption, and generating an energy efficiency evaluation result. The electric ceramic furnace has the effect of improving the heating efficiency of the electric ceramic furnace.

Description

Technical Field

[0001] The present application relates to the technical field of electro-ceramic cooking appliances, and particularly to an energy efficiency optimization method, device, equipment and medium for an electro-ceramic stove based on cooking behavior. Background Art

[0002] At present, as an electro-thermal cooking appliance that realizes heat transfer through a resistance heating panel, an electro-ceramic stove is widely used in household kitchens and commercial cooking scenarios. The electro-ceramic stove can be compatible with cookware of various materials, and while realizing the replacement of open flames and precise temperature control, it has good safety and operation convenience, so it has gradually become an important part of electro-thermal cooking appliances.

[0003] Currently, existing electro-ceramic stove products usually adopt a control method of fixed power output or multi-gear preset power switching. After the user sets the heating gear, the device continuously heats at the corresponding power until the user manually turns it off or adjusts it. Since the device continuously heats at the set power throughout the cooking process, it causes a mismatch between the power output and the heat load demand in different cooking stages, which not only affects the heating efficiency but also easily causes energy waste.

[0004] The above-mentioned prior art solutions have the following defects: The existing electro-ceramic stoves adopt a control method of fixed power output or multi-gear preset power switching, resulting in low heating energy efficiency and inaccurate power output, so there is room for improvement. Summary of the Invention

[0005] In order to improve the heating efficiency of an electro-ceramic stove, the present application provides an energy efficiency optimization method, device, equipment and medium for an electro-ceramic stove based on cooking behavior.

[0006] The first invention object of the present application is achieved through the following technical solutions: An energy efficiency optimization method for an electro-ceramic stove based on cooking behavior recognition, the method includes: Obtain heating temperature data, calculate the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and then identify the cookware attribute information; Based on the temperature change rate, temperature fluctuation amplitude and the cookware attribute information, identify the current cooking stage of the electro-ceramic stove, and then dynamically adjust the heating power of the electro-ceramic stove according to the cooking stage; Real-time obtain the operation state data during the heating process, calculate the instantaneous power of the electro-ceramic stove based on the operation state data, and accumulate and calculate the cumulative energy consumption according to the instantaneous power; After cooking is completed, compare the cumulative energy consumption with the preset standard energy consumption to generate an energy efficiency evaluation result.

[0007] By adopting the above technical solutions, by obtaining the heating temperature data and calculating the temperature change rate and the temperature fluctuation amplitude to further identify the cookware attribute information, it is possible to achieve the dynamic perception and classification of the heating object by the induction cooker, thereby providing a data basis for the subsequent precise control of the heating power, improving the heating adaptability and energy utilization rate; by identifying the current cooking stage based on the temperature change rate, the temperature fluctuation amplitude and the cookware attribute information and dynamically adjusting the heating power, it is possible to adjust the heat supply in a timely manner according to the actual cooking requirements, thereby avoiding overheating or underheating, improving the cooking quality and reducing energy waste; by obtaining the operating state data during the heating process in real time and calculating the instantaneous power and the cumulative energy consumption, it is possible to accurately record the energy consumption change during the entire cooking process, thereby providing reliable support for energy efficiency evaluation and subsequent optimization control strategies; by generating an energy efficiency evaluation result by comparing the cumulative energy consumption with the preset standard energy consumption after cooking is completed, it is possible to effectively evaluate the actual energy consumption level and provide energy-saving tips for users, thereby promoting reasonable use and energy consumption optimization.

[0008] In one example, the present application can be further configured as follows: The obtaining of the heating temperature data, calculating the temperature change rate and the temperature fluctuation amplitude according to the heating temperature data, and further identifying the cookware attribute information specifically include: Calculating the corresponding change rate according to the heating temperature data of adjacent sampling points, and taking the sliding average of the continuous change rates to obtain the temperature change rate, and extracting the maximum value and the minimum value of the heating temperature data within a preset time window to calculate the temperature fluctuation amplitude; Based on a plurality of temperature detection zones preset on the surface of the heating panel, detecting the response time difference of the temperature change rate, and further determining the placement center position and the occupied area of the cookware, and identifying the material type of the cookware according to the heating response characteristic parameters of each detection zone to obtain the cookware attribute information.

[0009] By adopting the above technical solutions, by calculating the change rate according to the heating temperature data of adjacent sampling points and taking the sliding average to obtain the temperature change rate, and at the same time extracting the maximum and minimum temperature values to calculate the temperature fluctuation amplitude, it is possible to effectively filter out single-point abnormal fluctuations and extract the true change trend of the heating process, thereby improving the accuracy of cooking stage identification and cookware attribute inference; by detecting the response time difference of the temperature change rate based on a plurality of temperature detection zones on the surface of the heating panel and analyzing the heating response characteristic parameters to identify the cookware attribute information, it is possible to realize the automatic identification of the cookware placement situation and the material type, thereby further improving the pertinence of heating control and the energy efficiency management level.

[0010] In one example, the present application can be further configured as follows: The identifying of the induction cooker cooking stage based on the temperature change rate, the temperature fluctuation amplitude and the cookware attribute information and dynamically adjusting the heating power specifically includes: When the rate of temperature change is greater than a set preheating rate threshold, it is determined that the current is in the preheating stage, and then the heating power is controlled to gradually increase to the target power in a linearly increasing manner; When the amplitude of temperature fluctuation exceeds a set boiling fluctuation threshold and the material of the cookware is a high - thermal - conductivity material, it is determined that the current is in the boiling stage, maintaining a preset constant medium - high power heating and restricting the change range of the heating power within a set range; When the rate of temperature change fluctuates periodically and the bottom area of the cookware is greater than a preset standard value, it is determined that the current is in the quick - frying stage, and the heating power is controlled to switch between high and low periodically; When the amplitude of temperature fluctuation is less than a set slow - stewing stability threshold and the material of the cookware is a low - thermal - conductivity material, it is determined that the current is in the slow - stewing stage, and intermittent heating control within a preset temperature range is adopted.

[0011] By adopting the above - mentioned technical solution, when the rate of temperature change is greater than the preheating rate threshold, it is determined as the preheating stage and the heating power is controlled to increase linearly, which can realize the control of rapid and uniform heating of the cookware, thus shortening the cooking preparation time and avoiding thermal shock damage; when the amplitude of temperature fluctuation exceeds the boiling fluctuation threshold and the cookware is made of high - thermal - conductivity material, it is determined as the boiling stage and a constant medium - high power heating is maintained, which can stably maintain the boiling state of the liquid, thus improving the cooking efficiency and the consistency of the finished product; when the rate of temperature change fluctuates periodically and the bottom area of the cookware is large, it is determined as the quick - frying stage and the heating power is switched between high and low periodically, which can meet the rapid heat - adjustment requirements during the quick - frying process, thus avoiding ingredient damage caused by local overheating; when the amplitude of temperature fluctuation is small and the cookware material is a low - thermal - conductivity material, it is determined as the slow - stewing stage and intermittent heating within an interval is adopted, which can maintain a stable low - temperature environment in the pot, thus ensuring the slow - cooking effect of the ingredients and saving energy consumption.

[0012] In one example of the present application, it can be further configured that: the real - time acquisition of the operation state data during the heating process and the calculation of the instantaneous power and the cumulative energy consumption specifically include: Obtaining a pair of data of the working current and the output voltage synchronously within a fixed sampling period Δt, and performing an abnormality comparison on the data pair with a preset normal current threshold and a normal voltage threshold to eliminate abnormal data; Based on the data pair after eliminating abnormalities, calculating the instantaneous power P corresponding to each sampling period according to the instantaneous power calculation formula P = U×I, where U is the output voltage and I is the working current; According to the instantaneous power and the sampling period, the cumulative energy consumption E is calculated by the formula E = Σ(P×Δt), and the energy consumption change rate within a continuous number of the sampling periods is calculated. In the case where the energy consumption change rate exceeds a preset change threshold, an abnormal energy consumption event is marked for the outlier.

[0013] By adopting the above technical solution, by synchronously acquiring the working current and output voltage data within a fixed sampling period and eliminating abnormal data, it can ensure the accuracy and reliability of the data source for subsequent power and energy consumption calculations, thereby improving the quality of the basic data for energy efficiency evaluation; by calculating the instantaneous power based on the data after eliminating abnormalities, it can reflect the actual heat output power change of the electro-ceramic stove in real time, thereby providing a real-time basis for dynamic power adjustment and energy consumption monitoring; by calculating the cumulative energy consumption by accumulating the instantaneous power and the sampling period and monitoring the energy consumption change rate in real time, it can timely detect the abnormal trend of energy consumption during the heating process and mark the abnormal energy consumption event, thereby providing data support for subsequent energy efficiency correction and optimal control.

[0014] In one example, the present application can be further configured as: comparing the cumulative energy consumption with a preset standard energy consumption and generating an energy efficiency evaluation result, which specifically includes: According to the cumulative energy consumption value and the standard energy consumption value of the corresponding cooking mode, the energy efficiency deviation ΔE is calculated by the formula ΔE = (E - Es) / Es; Based on the abnormal energy consumption event mark, the cumulative energy consumption is corrected, and then the corrected energy efficiency deviation is recalculated according to the correction result; Based on a preset energy efficiency evaluation standard, the corrected energy efficiency deviation is evaluated, the corresponding energy efficiency status is output, and the energy efficiency evaluation result is obtained.

[0015] By adopting the above technical solution, by calculating the energy efficiency deviation according to the cumulative energy consumption value and the standard energy consumption value of the corresponding cooking mode, it can objectively quantify the energy efficiency performance of the current cooking process, thereby providing an intuitive and perceivable energy efficiency feedback for the user; by correcting the cumulative energy consumption based on the abnormal energy consumption event mark and recalculating the corrected energy efficiency deviation, it can effectively eliminate the abnormal influence and improve the accuracy of the energy efficiency evaluation, thereby avoiding the misjudgment of energy efficiency caused by short-term abnormalities; by grading and evaluating the corrected energy efficiency deviation based on a preset energy efficiency evaluation standard and outputting the energy efficiency status, it can help the user intuitively understand the energy efficiency level of the equipment operation, thereby guiding the optimization of cooking operation behaviors and improving the overall energy use efficiency.

[0016] In one example, the present application can be further configured as: correcting the cumulative energy consumption, and then recalculating the corrected energy efficiency deviation according to the correction result, which specifically includes: Based on the abnormal energy consumption event marker, extract the abnormal time period and the corresponding energy consumption change amplitude. When the time length of the abnormal time period exceeds the set abnormal time threshold and the energy consumption change amplitude exceeds the set energy consumption amplitude threshold, determine that the current abnormal energy consumption event marker is a valid abnormality, and then eliminate the valid abnormality; Based on the instantaneous power mean values within the normal sampling periods adjacent to the start and end points of the abnormal segment, use linear interpolation to estimate the normal energy consumption compensation amount for the abnormal segment, and then recalculate the corresponding energy efficiency deviation as the corrected energy efficiency deviation.

[0017] By adopting the above technical solutions, by extracting the abnormal time period and the corresponding energy consumption change amplitude based on the abnormal energy consumption event marker, and determining it as a valid abnormality and eliminating it when the abnormal time length and amplitude exceed the set thresholds, it can effectively exclude the interference of abnormal energy consumption fluctuations during the heating process on the overall evaluation result, thereby ensuring the authenticity and stability of the energy efficiency statistical data; by using linear interpolation to estimate the normal energy consumption compensation amount for the abnormal segment based on the instantaneous power mean values of the normal sampling periods adjacent to the start and end points of the abnormal segment and recalculating the energy efficiency deviation, it can restore a reasonable energy consumption change curve, thereby further improving the accuracy and reliability of the energy efficiency evaluation during the cooking process.

[0018] The second above-mentioned inventive object of the present application is achieved through the following technical solutions: An electromagnetic cooker energy efficiency optimization device based on cooking behavior recognition, the device includes: A temperature data acquisition module, configured to acquire heating temperature data, calculate the temperature change rate and the temperature fluctuation amplitude according to the heating temperature data, and then identify the cookware attribute information; A cooking stage recognition module, configured to identify the current cooking stage of the electromagnetic cooker based on the temperature change rate, the temperature fluctuation amplitude, and the cookware attribute information, and then dynamically adjust the heating power of the electromagnetic cooker according to the cooking stage; An operating state monitoring module, configured to acquire the operating state data during the heating process in real time, calculate the current instantaneous power of the electromagnetic cooker based on the operating state data, and accumulate and calculate the cumulative energy consumption according to the instantaneous power; An energy efficiency evaluation module, configured to compare the cumulative energy consumption with a preset standard energy consumption after cooking is completed, and generate an energy efficiency evaluation result.

[0019] By adopting the above technical solution, by obtaining the heating temperature data and calculating the temperature change rate and the temperature fluctuation amplitude to further identify the cookware attribute information, it is possible to achieve the dynamic perception and classification of the heating object by the induction cooker, thereby providing a data basis for the subsequent precise control of the heating power, improving the heating adaptability and energy utilization rate; by identifying the current cooking stage based on the temperature change rate, the temperature fluctuation amplitude and the cookware attribute information and dynamically adjusting the heating power, it is possible to timely adjust the heat supply according to the actual cooking requirements, thereby avoiding overheating or underheating, improving the cooking quality and reducing energy waste; by obtaining the operation state data during the heating process in real time and calculating the instantaneous power and the cumulative energy consumption, it is possible to accurately record the energy consumption change during the entire cooking process, thereby providing a reliable support for the energy efficiency evaluation and the subsequent optimization control strategy; by comparing the cumulative energy consumption with the preset standard energy consumption after cooking to generate an energy efficiency evaluation result, it is possible to effectively evaluate the actual energy consumption level and provide an energy-saving reminder for the user, thereby promoting reasonable use and energy consumption optimization.

[0020] The above object three of the present application is achieved by the following technical solution: A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above method for optimizing the energy efficiency of the induction cooker based on cooking behavior are implemented.

[0021] The above object four of the present application is achieved by the following technical solution: A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the above method for optimizing the energy efficiency of the induction cooker based on cooking behavior are implemented.

[0022] In summary, the present application includes the following beneficial technical effects: 1. By obtaining heating temperature data, calculating the temperature change rate and temperature fluctuation amplitude, and then identifying the cookware attribute information, it is possible to achieve the dynamic perception and classification of the heating object by the induction cooker, thereby providing a data basis for subsequent precise control of the heating power, improving the adaptability of heating and energy utilization efficiency; by identifying the current cooking stage based on the temperature change rate, temperature fluctuation amplitude and cookware attribute information and dynamically adjusting the heating power, it is possible to adjust the heat supply in a timely manner according to the actual cooking needs, thereby avoiding overheating or insufficient heating, improving the cooking quality and reducing energy waste; by obtaining the operating state data during the heating process in real time and calculating the instantaneous power and cumulative energy consumption, it is possible to accurately record the energy consumption change during the entire cooking process, thereby providing reliable support for energy efficiency evaluation and subsequent optimization control strategies; by generating an energy efficiency evaluation result by comparing the cumulative energy consumption with the preset standard energy consumption after cooking is completed, it is possible to effectively evaluate the actual energy consumption level and provide energy-saving tips for users, thereby promoting reasonable use and energy consumption optimization; 2. By calculating the change rate based on the heating temperature data of adjacent sampling points and taking the sliding average to obtain the temperature change rate, and at the same time extracting the maximum and minimum temperatures to calculate the temperature fluctuation amplitude, it is possible to effectively filter out single-point abnormal fluctuations and refine the true change trend during the heating process, thereby improving the accuracy of cooking stage identification and cookware attribute inference; by detecting the difference in the temperature change rate response time based on multiple temperature detection zones on the surface of the heating panel and analyzing the heating response characteristic parameters to identify the cookware attribute information, it is possible to automatically identify the placement and material type of the cookware, thereby further improving the pertinence of heating control and the energy efficiency management level; 3. By determining that it is the preheating stage when the temperature change rate is greater than the preheating rate threshold and controlling the heating power to increase linearly, it is possible to achieve the control of rapid and uniform heating of the cookware, thereby shortening the cooking preparation time and avoiding thermal shock damage; by determining that it is the boiling stage and maintaining a constant medium-high power heating when the temperature fluctuation amplitude exceeds the boiling fluctuation threshold and the cookware is made of high thermal conductivity material, it is possible to stably maintain the boiling state of the liquid, thereby improving the cooking efficiency and the consistency of the finished product; by determining that it is the stir-frying stage and performing periodic high-low power switching when the temperature change rate fluctuates periodically and the bottom area of the cookware is large, it is possible to meet the rapid heat adjustment requirements during the stir-frying process, thereby avoiding ingredient damage caused by local overheating; by determining that it is the slow cooking stage and adopting interval intermittent heating when the temperature fluctuation amplitude is small and the cookware material is of low thermal conductivity, it is possible to maintain a stable low-temperature environment in the pot, thereby ensuring the slow-cooking effect of the ingredients and saving energy. Description of the Drawings

[0023] Figure 1 is a flowchart of an energy efficiency optimization method for an induction cooker based on cooking behavior in an embodiment of the present application; Figure 2is a flowchart for implementing step S10 in a method for optimizing energy efficiency of an electric ceramic stove based on cooking behavior in one embodiment of the present application; Figure 3 is a flowchart for implementing step S20 in the method for optimizing energy efficiency of an electric ceramic stove based on cooking behavior in one embodiment of the present application; Figure 4 is a flowchart for implementing step S30 in the method for optimizing energy efficiency of an electric ceramic stove based on cooking behavior in one embodiment of the present application; Figure 5 is a flowchart for implementing step S40 in the method for optimizing energy efficiency of an electric ceramic stove based on cooking behavior in one embodiment of the present application; Figure 6 is a flowchart for implementing step S42 in the method for optimizing energy efficiency of an electric ceramic stove based on cooking behavior in one embodiment of the present application; Figure 7 It is a principle block diagram of an electric ceramic stove energy efficiency optimization device based on cooking behavior in one embodiment of the present application; Figure 8 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses a method for optimizing energy efficiency of an electric ceramic stove based on cooking behavior, which specifically includes the following steps: S10: Obtain heating temperature data, calculate the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and then identify the pot attribute information.

[0026] Specifically, the temperature detection module is called to collect the temperature data of the surface of the heating panel with a fixed sampling period Δt. The panel surface temperature value corresponding to the current sampling moment is recorded at each sampling to form a continuous temperature data sequence. To ensure the traceability of the temperature change process and the consistency of data processing, the consistency of the sampling time interval is continuously monitored during the sampling process to ensure that there is no loss or jump in the temperature data. At the same time, the sampled temperature data is initially screened for validity during the collection process to eliminate abnormal points to improve the accuracy of subsequent calculations. The collected temperature data will be used as the basic data input for subsequent calculations of the temperature change rate, temperature fluctuation amplitude, and identification of cookware attribute information to support subsequent cooking stage identification and power adjustment actions.

[0027] S20: Based on the temperature change rate, the temperature fluctuation amplitude and the cookware property information, the current cooking stage of the electric ceramic stove is identified, and then the heating power of the electric ceramic stove is dynamically adjusted according to the cooking stage.

[0028] Specifically, after completing the acquisition of heating temperature data and obtaining the information on the properties of the cookware, first, it is determined whether the heating process is in the preheating stage with a rapid temperature rise or the boiling stage with violent temperature fluctuations based on the magnitude and trend of the temperature change rate. Secondly, the cooking state is further subdivided according to the temperature fluctuation amplitude in combination with the heat conduction performance characteristics of the cookware material. For example, when it is determined that the temperature change rate shows periodic fluctuations, it is combined with the bottom area of the cookware to identify whether it enters the fast stir-fry stage, or when the temperature change amplitude is small and the cookware material is of a low heat conduction type, the slow simmering stage is identified. During the identification process, a joint determination is made based on the set temperature rate threshold, fluctuation amplitude threshold, and cookware characteristic parameters to improve the accuracy of cooking stage identification. By dynamically and real-time identifying the cooking stage, it provides a basis for subsequent heating power adjustment, making the heating process more in line with the cooking requirements of the ingredients.

[0029] S30: Obtain the operation state data during the heating process in real time, calculate the current instantaneous power of the induction cooker based on the operation state data, and calculate the cumulative energy consumption by cumulative calculation according to the instantaneous power.

[0030] Specifically, select the corresponding heating power adjustment strategy according to the identified current cooking stage. In the preheating stage, control the heating power to continuously increase in a linear manner to accelerate the heating speed of the cookware. In the boiling stage, maintain a medium-high constant power to ensure the continuous boiling of the liquid and avoid overheating. In the fast stir-fry stage, control the heating power to alternately switch between high and low according to a set period to match the rapid changes in the large heat absorption and heat release of the ingredients during the frying process. In the slow simmering stage, trigger intermittent heating control alternately between the upper and lower limits by setting the temperature control bandwidth to keep the temperature in the pot stable. During the power adjustment process, monitor the temperature change rate and fluctuation of the heating panel in real time and dynamically correct the output strategy to cope with the cooking load fluctuations caused by environmental changes or ingredient characteristic changes.

[0031] S40: After cooking is completed, compare the cumulative energy consumption with the preset standard energy consumption to generate an energy efficiency evaluation result.

[0032] Specifically, during the heating process, real-time data of the working current I and the output voltage U are synchronously collected at a fixed sampling period Δt. The current detection module and the voltage detection module are used for sampling respectively and the data pairs are synchronously matched in combination with the time stamps. At the same time, during the collection process, the current value and the voltage value are respectively compared with the preset normal working range threshold in real time to eliminate invalid sampling points caused by sensor abnormalities, line jitters, or external interferences. On the premise of ensuring data validity, a synchronous current-voltage data pair sequence is generated. This data sequence will serve as the basic data support for subsequent instantaneous power calculation and cumulative energy consumption statistics. At the same time, the original sampling information is retained during the collection of operation state data for abnormal energy consumption analysis and traceability processing during the energy efficiency evaluation process.

[0033] In one embodiment, such asFigure 2 As shown, in step S10, that is, obtaining heating temperature data, calculating the temperature change rate and temperature fluctuation amplitude based on the heating temperature data, and further identifying the cookware attribute information, specifically including: S11: Calculate the corresponding change rate based on the heating temperature data of adjacent sampling points, and take the moving average of the continuous change rates to obtain the temperature change rate. Extract the maximum value and minimum value of the heating temperature data within a preset time window to calculate the temperature fluctuation amplitude.

[0034] Specifically, calculate the temperature change amount per unit time based on the heating temperature data corresponding to two adjacent sampling moments before and after, and divide it by the sampling time interval Δt to obtain the instantaneous temperature change rate. Then, calculate the moving average of the instantaneous temperature change rate in a sliding window manner within a continuous number of sampling periods to eliminate local mutations caused by single-point sampling errors, thereby obtaining a stable temperature change rate curve during the heating process. At the same time, extract the maximum value Tmax and minimum value Tmin of the heating temperature data within the preset time window, and calculate the temperature fluctuation amplitude ΔT = Tmax - Tmin to reflect the severity of the temperature change on the surface of the heating panel during this period. The temperature change rate is used to determine the change trend of the heating and warming speed, and the temperature fluctuation amplitude is used to identify the boiling severity or the stability characteristics during the heat preservation stage in the heating process.

[0035] S12: Based on multiple temperature detection zones preset on the surface of the heating panel, detect the response time difference of the temperature change rate, and then determine the placement center position and occupied area of the cookware. According to the heating response characteristic parameters of each detection zone, identify the material type of the cookware to obtain the cookware attribute information.

[0036] Specifically, collect the temperature change rate of each zone in the initial heating stage based on multiple temperature detection zones divided on the surface of the heating panel, and synchronously record its temperature rise response time. During the detection process, judge the placement center position and bottom coverage area of the cookware by comparing the response speed and temperature rise amplitude differences of the temperature rise curves of each detection zone. Further analyze the thermal conductivity index of the bottom of the cookware according to the uniformity and heat diffusion characteristics of the temperature rise rate between different zones. Determine the cookware material type by comparing the heating response characteristics of the cookware with the characteristic models in the preset standard thermal conductivity material database. Finally, form the cookware attribute information including the cookware placement position, bottom size range, and material type. The cookware attribute information is used as the input basis for subsequent identification of the cooking stage and dynamic power adjustment to improve the control accuracy and heating efficiency.

[0037] In one embodiment, as Figure 3 shown, in step S20, that is, identifying the cooking stage of the induction cooker and dynamically adjusting the heating power based on the temperature change rate, temperature fluctuation amplitude, and cookware attribute information, specifically including: S21: When the temperature change rate is greater than the set preheating rate threshold, it is determined that the current is in the preheating stage, and then the heating power is controlled to gradually increase to the target power in a linearly increasing manner.

[0038] Specifically, within a continuous sampling period, the temperature change rate on the surface of the heating panel is detected. When the temperature change rate continuously exceeds the set preheating rate threshold and the temperature fluctuation amplitude is in a stable upward trend, combined with the bottom area and material characteristics in the cookware attribute information, it is judged that the heat absorption of the cookware is in a state of uniform and rapid increase. Further confirm that at the initial stage of heating, the ingredients have not released a large amount of moisture or oil, resulting in a drastic temperature change. It is determined that the current cooking process is in the preheating stage. During the determination process, the minimum period for continuously meeting the threshold conditions is set to avoid misjudgment caused by instantaneous interference. By identifying the preheating stage, a linearly increasing heating power strategy can be adopted in the heating control to accelerate the overall heating efficiency of the cookware.

[0039] S22: When the temperature fluctuation amplitude exceeds the set boiling fluctuation threshold and the material of the cookware is a high thermal conductivity material, it is determined that the current is in the boiling stage, and the preset constant medium-high power heating is maintained, and the change amplitude of the heating power is limited within the set range.

[0040] Specifically, within the set time window, the temperature fluctuation amplitude on the surface of the heating panel is continuously monitored. When it is detected that the temperature fluctuation amplitude ΔT continuously exceeds the set boiling determination fluctuation threshold and the material type in the cookware attribute information is identified as a high thermal conductivity material, based on the physical principle of the characteristics of the liquid phase change in the high thermal conductivity material cookware during heating, resulting in a violent heat release and absorption cycle, combined with the local high-frequency fluctuation mode of the temperature change rate to further prove the occurrence of the boiling phenomenon, it is determined that the current heating state is in the boiling stage. The determination of the boiling stage allows the heating control strategy to enter the constant medium-high power output mode to stably maintain the continuous boiling of the liquid in the pot and suppress the risk of local overheating.

[0041] S23: When the temperature change rate fluctuates periodically and the bottom area of the cookware is greater than the preset standard value, it is determined that the current is in the quick stir-fry stage, and the heating power is controlled to switch periodically between high and low.

[0042] Specifically, within a continuous sampling period, the change trend of the temperature change rate of the heating panel is analyzed. When it is detected that the temperature change rate shows periodic high and low alternating changes and the period characteristics conform to the set period fluctuation mode parameters, and at the same time, combined with the bottom area in the cookware attribute information being greater than the preset standard area threshold, it is inferred that the current cooking process is in the quick stir-fry stage. Based on the characteristics of frequent stirring and rapid heat absorption and release alternation of the cookware during the quick stir-fry process, it is determined that the quick stir-fry stage requires a power adjustment strategy with rapid response to provide sufficient heat impact and prevent the ingredients from being burnt due to local overheating. By identifying this stage, the heating power can be dynamically adjusted to match the rhythm of ingredient processing.

[0043] S24: When the temperature fluctuation amplitude is less than the set slow-cooking stability threshold and the material of the cookware is a low thermal conductivity material, it is determined that the current is in the slow-cooking stage, and intermittent heating control within a preset temperature range is adopted.

[0044] Specifically, within the set sampling time window, continuously analyze the temperature fluctuation amplitude on the surface of the heating panel. When the temperature fluctuation amplitude ΔT is lower than the slow-cooking stage stability determination threshold and the material type in the cookware attribute information is identified as a low thermal conductivity material, further verify in combination with the characteristics of slow heat transfer at the center and gentle surface temperature change of the low thermal conductivity cookware during the slow heating process, and determine that the current cooking state is in the slow-cooking stage. The identification of the slow-cooking stage enables the heating control to adopt an intermittent heating strategy within the set temperature range, ensuring that the temperature in the pot remains stable and fluctuates, meeting the requirement of slow cooking of ingredients at a low temperature for a long time.

[0045] In one embodiment, as Figure 4 shown, in step S30, that is, obtain the operating state data during the heating process in real time and calculate the instantaneous power and cumulative energy consumption, specifically including: S31: Obtain a pair of synchronous working current and output voltage data within a fixed sampling period Δt, and compare the data pair with the preset normal current threshold and normal voltage threshold for anomaly comparison to eliminate abnormal data.

[0046] Specifically, after identifying that the current cooking stage is the preheating stage, set the preheating target power Ptarget and the initial power Pstart, and control the heating power to gradually increase according to the linear increasing function P(t) = Pstart + k × t at a fixed time step Δt, where k is the increasing rate coefficient, determined by Ptarget and the set preheating duration Tpreheat. During the increasing process, monitor the change rate of the surface temperature of the heating panel in real time to ensure a stable temperature rise process. When the actual heating temperature reaches the preset temperature rise rate threshold or the heating power reaches Ptarget, stop increasing and enter the next stage control logic. The linear increasing method can avoid thermal shock damage to the cookware caused by sudden temperature changes, while improving the preheating speed and shortening the cooking preparation time.

[0047] S32: Based on the data pair after eliminating anomalies, calculate the instantaneous power P corresponding to each sampling period according to the instantaneous power calculation formula P = U×I, where U is the output voltage and I is the working current.

[0048] Specifically, after it is recognized that the cooking process enters the boiling stage, the heating power is controlled to be constantly output within the set medium-high power level range. The medium-high power level range is estimated based on the thermal conductivity of the cookware material, the bottom area, and the liquid volume to ensure the continuous heating requirement during the boiling process. During the constant power output period, the temperature fluctuation amplitude and the temperature change rate are continuously monitored to judge the stability of the boiling state. If it is detected that the temperature fluctuation amplitude significantly decreases or the liquid surface cooling trend is obvious, the medium-high power level range is adjusted in a timely manner to maintain the continuous boiling of the liquid. At the same time, to avoid the phenomenon of liquid boiling due to local overheating, the maximum power threshold is limited during the constant output process to achieve heating safety protection. The continuous power output during the boiling stage can ensure the continuity of the heating process and the stability of the liquid phase change.

[0049] S33: According to the instantaneous power and the sampling period, the cumulative energy consumption E is calculated through the formula E = Σ(P×Δt), and the energy consumption change rate within several consecutive sampling periods is calculated. In the case where the energy consumption change rate exceeds the preset change threshold, an abnormal energy consumption event is marked for the outlier.

[0050] Specifically, after it is recognized that the cooking process is in the quick stir-fry stage, two switching power points, the high power Phigh and the low power Plow, and the switching period Tcycle are set. The heating power is controlled to alternately switch between Phigh and Plow according to the high and low power duty cycles Dhigh and Dlow within the set period Tcycle. Among them, Dhigh and Dlow are optimally set according to the heat absorption and release laws during the food stir-frying process and the heat conduction characteristics of the cookware. In each switching cycle, first, the bottom of the pot is heated at the Phigh power for a time proportional to Dhigh to promote the rapid rise of the bottom temperature, and then it is heated at the Plow power for a time proportional to Dlow to prevent overheating accumulation at the bottom of the pot. During the entire periodic switching process, the temperature change trend is monitored in real time to dynamically adjust the switching rhythm parameters. The periodic power switching method can improve the temperature control response speed in the quick stir-fry stage and meet the requirement of rapid heat adjustment for frequent stir-frying actions.

[0051] In one embodiment, as Figure 5 shown, in step S40, that is, comparing the cumulative energy consumption with the preset standard energy consumption and generating an energy efficiency evaluation result, specifically including: S41: According to the cumulative energy consumption value and the standard energy consumption value of the corresponding cooking mode, the energy efficiency deviation ΔE is calculated through the formula ΔE = (E - Es) / Es.

[0052] Specifically, within each fixed sampling period Δt, based on the pair of output voltage U and working current I data collected synchronously, the instantaneous power value P for the corresponding sampling period is calculated through the instantaneous power calculation formula P = U × I. The instantaneous power value reflects the actual energy consumption rate of the heating load at this sampling moment. After the instantaneous power calculation is completed, P is multiplied by the sampling period Δt to obtain the energy consumption amount ΔE within this period. Then, ΔE is successively accumulated to obtain the continuously updated cumulative energy consumption E. At the same time, each time the cumulative energy consumption is updated, the corresponding timestamp and cumulative energy consumption value are saved for subsequent energy efficiency analysis. To ensure the accuracy of data calculation, before power calculation, the original voltage and current data are applied with a preset outlier rejection rule to filter out measurement outliers and ensure the authenticity and continuity of power and energy consumption data.

[0053] S42: Based on the abnormal energy consumption event marker, the cumulative energy consumption is corrected, and then the corrected energy efficiency deviation is recalculated according to the correction result.

[0054] Specifically, within a continuous number of sampling periods, the change trend of the cumulative energy consumption E is analyzed, the energy consumption change rate between two consecutive cumulative energy consumption update points is calculated, and it is determined whether an abnormal heating event has occurred, such as abnormal heating of the cookware, external environmental interference, etc. Further, the corresponding abnormal time period is marked with an energy consumption event, and the marked content includes the abnormal occurrence time, abnormal duration, abnormal energy consumption amplitude change amount, etc., which are used for abnormal rejection or compensation processing during subsequent cumulative energy consumption data correction and energy efficiency evaluation. Through the real-time marking of abnormal energy consumption events, the credibility of energy efficiency data during the cooking process can be effectively improved.

[0055] S43: Based on the preset energy efficiency evaluation criteria, the corrected energy efficiency deviation is evaluated, the corresponding energy efficiency status is output, and the energy efficiency evaluation result is obtained.

[0056] Specifically, after the abnormal energy consumption event marker is completed, the cumulative energy consumption data sequence is traversed and the data points overlapping with the abnormal energy consumption event time period are screened out. When it is detected that the timestamp of the data point falls within the abnormal event marker range, the energy consumption value ΔE of the corresponding data point is abnormally excluded from the cumulative energy consumption calculation linked list, and during the exclusion process, the time continuity of the energy consumption data is ensured. The time line is filled by interpolating the normal data before and after the abnormal segment to avoid jumps in the cumulative energy consumption curve. After the exclusion is completed, the remaining valid energy consumption data is re-accumulated to obtain the preliminarily corrected cumulative energy consumption. While excluding the abnormal segment, the abnormal event record is retained for subsequent compensation stage to restore the reasonably estimated energy consumption value according to the interpolation logic, ensuring the coherence and accuracy of the overall energy efficiency evaluation.

[0057] In one embodiment, as Figure 6 shown, in step S42, that is, the cumulative energy consumption is corrected, and then the corrected energy efficiency deviation is recalculated according to the correction result, specifically including: S421: Based on the abnormal energy consumption event marker, extract the abnormal time period and the corresponding energy consumption change amplitude. When the time length of the abnormal time period exceeds the set abnormal time threshold and the energy consumption change amplitude exceeds the set energy consumption amplitude threshold, determine that the current abnormal energy consumption event marker is a valid abnormality, and then eliminate the valid abnormality.

[0058] Specifically, on the basis of completing the elimination of abnormal energy consumption events, extract the instantaneous power mean values of the normal sampling periods before and after the start and end points of each abnormal segment as the correction reference values. Use the linear interpolation method to generate a fitted normal energy consumption compensation curve within the abnormal time period. During the compensation process, according to the starting power value Pstart and the ending power value Pend, generate the fitted instantaneous power value P'(t) for each sampling period step by step according to the linear change rule within the duration ΔTex of the abnormal segment. Then multiply P'(t) by the sampling period Δt to obtain the compensated energy consumption increment ΔE', and accumulate ΔE' into the corrected cumulative energy consumption E'. During the compensation calculation process, continuously check the smoothness of the compensation curve to avoid sudden changes in the energy consumption curve after correction in the abnormal segment, and at the same time ensure that the compensated cumulative energy consumption E' is consistent with the energy consumption change trends of the front and back normal segments in terms of trend. Correcting the cumulative energy consumption through the interpolation compensation method can effectively restore the energy consumption continuity during the heating process and improve the accuracy and credibility of subsequent energy efficiency evaluation.

[0059] S422: Based on the instantaneous power mean values within the normal sampling periods adjacent to the start and end points of the abnormal segment, use the linear interpolation method to estimate the normal energy consumption compensation amount of the abnormal segment, and then recalculate the corresponding energy efficiency deviation as the corrected energy efficiency deviation.

[0060] Specifically, after completing the correction of the cumulative energy consumption, extract the corrected cumulative energy consumption E'. Combine it with the standard energy consumption Es corresponding to the preset cooking mode, and calculate the corrected energy efficiency deviation ΔE through the energy efficiency deviation calculation formula ΔE = (E' - Es) / Es. The energy efficiency deviation ΔE is used to reflect the relative difference between the actual energy consumption and the standard energy consumption during the current cooking process. According to the size of the ΔE value and the preset energy efficiency evaluation standard, conduct a grading determination. If ΔE falls within the excellent interval, output the high energy efficiency level result; if ΔE falls within the normal interval, output the medium energy efficiency level result; if ΔE exceeds the set threshold, output the low energy efficiency level result and prompt optimization suggestions. While generating the energy efficiency evaluation result, save the data of this evaluation and the abnormal energy consumption event record to support subsequent energy efficiency trend analysis and user behavior optimization. Evaluating the energy efficiency deviation based on the corrected cumulative energy consumption can comprehensively reflect the actual energy utilization efficiency of the induction cooker and provide users with reliable energy-saving usage guidance.

[0061] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0062] In one embodiment, an energy efficiency optimization device for an induction cooker based on cooking behavior is provided. The energy efficiency optimization device for the induction cooker based on cooking behavior corresponds one-to-one with the energy efficiency optimization method for the induction cooker based on cooking behavior in the above embodiment. As Figure 7 shown, the energy efficiency optimization device for the induction cooker based on cooking behavior includes a temperature data acquisition module, a cooking stage identification module, an operating state monitoring module, and an energy efficiency evaluation module. The detailed description of each functional module is as follows: The temperature data acquisition module is used to obtain heating temperature data, calculate the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and further identify the cookware attribute information; The cooking stage identification module is used to identify the current cooking stage of the induction cooker based on the temperature change rate, temperature fluctuation amplitude and cookware attribute information, and then dynamically adjust the heating power of the induction cooker according to the cooking stage; The operating state monitoring module is used to obtain the operating state data during the heating process in real time, calculate the current instantaneous power of the induction cooker based on the operating state data, and accumulate and calculate the cumulative energy consumption according to the instantaneous power; The energy efficiency evaluation module is used to compare the cumulative energy consumption with the preset standard energy consumption after cooking is completed, and generate an energy efficiency evaluation result.

[0063] Optionally, the temperature data acquisition module specifically includes: The rate calculation sub-module is used to calculate the corresponding change rate according to the heating temperature data of adjacent sampling points, take the sliding average of the continuous change rates to obtain the temperature change rate, and extract the maximum value and minimum value of the heating temperature data within a preset time window to calculate the temperature fluctuation amplitude; The cookware identification sub-module is used to detect the response time difference of the temperature change rate based on a plurality of preset temperature detection zones on the surface of the heating panel, and then determine the placement center position and occupied area of the cookware, and identify the material type of the cookware according to the heating response characteristic parameters of each detection zone to obtain the cookware attribute information.

[0064] Optionally, the cooking stage identification module specifically includes: The preheating identification sub-module is used to determine that the current is in the preheating stage when the temperature change rate is greater than the set preheating rate threshold, and then control the heating power to gradually increase to the target power in a linearly increasing manner; The boiling identification sub-module is used to determine that the current is in the boiling stage when the temperature fluctuation amplitude exceeds the set boiling fluctuation threshold and the material of the cookware is a high thermal conductivity material, maintain the preset constant medium-high power heating, and limit the change range of the heating power within the set range; A quick stir - fry recognition sub - module, which is used to determine that the current is in the quick stir - fry stage when the rate of temperature change fluctuates periodically and the bottom area of the cooking pot is greater than a preset standard value, and controls the heating power to switch between high and low periodically; A slow stew recognition sub - module, which is used to determine that the current is in the slow stew stage when the amplitude of temperature fluctuation is less than the set slow - stew stability threshold and the material of the cooking pot is a low - thermal - conductivity material, and adopts intermittent heating control within a preset temperature range.

[0065] Optionally, the operation status monitoring module specifically includes: An electrical parameter acquisition sub - module, which is used to obtain a pair of data of synchronous working current and output voltage within a fixed sampling period Δt, and compare the data pair with preset normal current threshold and normal voltage threshold for anomaly comparison to eliminate abnormal data; An instantaneous power calculation sub - module, which is used to calculate the instantaneous power P corresponding to each sampling period based on the data pair after eliminating anomalies according to the instantaneous power calculation formula P = U×I, where U is the output voltage and I is the working current; An energy consumption monitoring sub - module, which is used to calculate the cumulative energy consumption E according to the instantaneous power and the sampling period through the formula E = Σ(P×Δt), and calculate the rate of change of energy consumption within a continuous number of sampling periods. In the case where the rate of change of energy consumption exceeds the preset change threshold, mark the abnormal value as an abnormal energy consumption event.

[0066] Optionally, the energy efficiency evaluation module specifically includes: A deviation calculation sub - module, which is used to calculate the energy efficiency deviation ΔE according to the cumulative energy consumption value and the standard energy consumption value of the corresponding cooking mode through the formula ΔE=(E - Es) / Es; An energy consumption correction sub - module, which is used to perform correction processing on the cumulative energy consumption based on the abnormal energy consumption event mark, and then recalculate the corrected energy efficiency deviation according to the correction result; A level evaluation sub - module, which is used to evaluate the corrected energy efficiency deviation based on a preset energy efficiency evaluation standard, output the corresponding energy efficiency status, and obtain the energy efficiency evaluation result.

[0067] Optionally, the energy consumption correction sub - module specifically includes: An abnormal data elimination unit, which is used to extract the abnormal time period and the corresponding energy consumption change amplitude based on the abnormal energy consumption event mark. When the time length of the abnormal time period exceeds the set abnormal time threshold and the energy consumption change amplitude exceeds the set energy consumption amplitude threshold, determine that the current abnormal energy consumption event mark is a valid anomaly, and then eliminate the valid anomaly; A compensation calculation unit, which is used to estimate the normal energy consumption compensation amount of the abnormal segment by using linear interpolation based on the average instantaneous power within the normal sampling periods adjacent to the start and end points of the abnormal segment, and then recalculate the corresponding energy efficiency deviation as the corrected energy efficiency deviation.

[0068] For the specific limitations of the electric ceramic stove energy efficiency optimization device based on cooking behavior, reference can be made to the limitations of the electric ceramic stove energy efficiency optimization method based on cooking behavior in the above text, which will not be elaborated here. Each module in the above-mentioned electric ceramic stove energy efficiency optimization device based on cooking behavior can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0069] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 8 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements an electric ceramic stove energy efficiency optimization method based on cooking behavior.

[0070] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented: Obtain heating temperature data, calculate the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and then identify the cookware attribute information; Based on the temperature change rate, temperature fluctuation amplitude, and cookware attribute information, identify the current cooking stage of the electric ceramic stove, and then dynamically adjust the heating power of the electric ceramic stove according to the cooking stage; Obtain the operation status data during the heating process in real time, calculate the current instantaneous power of the electric ceramic stove based on the operation status data, and calculate the cumulative energy consumption by accumulating according to the instantaneous power; After cooking is completed, compare the cumulative energy consumption with the preset standard energy consumption to generate an energy efficiency evaluation result.

[0071] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the following steps are implemented: Obtain heating temperature data, calculate the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and then identify the cookware attribute information; Based on the rate of temperature change, the amplitude of temperature fluctuation, and the information of the cookware attributes, identify the current cooking stage of the induction cooker, and then dynamically adjust the heating power of the induction cooker according to the cooking stage; Obtain the operation status data during the heating process in real time, calculate the current instantaneous power of the induction cooker based on the operation status data, and calculate the cumulative energy consumption by cumulative calculation according to the instantaneous power; After cooking is completed, compare the cumulative energy consumption with the preset standard energy consumption to generate an energy efficiency evaluation result.

[0072] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0073] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0074] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An energy efficiency optimization method for an induction cooker based on cooking behavior recognition, characterized in that, The method includes: Obtaining heating temperature data, calculating the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and then identifying the cookware attribute information; Based on the temperature change rate, temperature fluctuation amplitude and the cookware attribute information, identifying the current cooking stage of the induction cooker, and then dynamically adjusting the heating power of the induction cooker according to the cooking stage; Real-time obtaining the operation state data during the heating process, calculating the current instantaneous power of the induction cooker based on the operation state data, and calculating the cumulative energy consumption by cumulative calculation according to the instantaneous power; After cooking is completed, comparing the cumulative energy consumption with the preset standard energy consumption to generate an energy efficiency evaluation result.

2. The energy efficiency optimization method of the electro-ceramic stove based on cooking behavior recognition according to claim 1, characterized in that, The obtaining of the heating temperature data, calculating the temperature change rate and temperature fluctuation amplitude according to the heating temperature data, and then identifying the cookware attribute information specifically includes: Calculating the corresponding change rate according to the heating temperature data of adjacent sampling points, taking the sliding average of the continuous change rates to obtain the temperature change rate, and extracting the maximum value and minimum value of the heating temperature data within a preset time window to calculate the temperature fluctuation amplitude; Based on a plurality of preset temperature detection zones on the surface of the heating panel, detecting the response time difference of the temperature change rate, and then determining the placement center position and occupied area of the cookware, and identifying the material type of the cookware according to the heating response characteristic parameters of each detection zone to obtain the cookware attribute information.

3. The energy efficiency optimization method of the electro-ceramic stove based on cooking behavior recognition according to claim 1, characterized in that, The identifying the cooking stage of the induction cooker and dynamically adjusting the heating power based on the temperature change rate, temperature fluctuation amplitude and the cookware attribute information specifically includes: When the temperature change rate is greater than the set preheating rate threshold, it is determined that the current is in the preheating stage, and then the heating power is controlled to gradually increase to the target power in a linearly increasing manner; When the temperature fluctuation amplitude exceeds the set boiling fluctuation threshold and the material of the cookware is a high thermal conductivity material, it is determined that the current is in the boiling stage, maintaining a preset constant medium-high power heating, and limiting the change range of the heating power within the set range; When the temperature change rate fluctuates periodically and the bottom area of the cookware is greater than the preset standard value, it is determined that the current is in the stir-frying stage, and the heating power is controlled to switch periodically between high and low; When the temperature fluctuation amplitude is less than the set slow cooking stability threshold and the material of the cookware is a low thermal conductivity material, it is determined that the current is in the slow cooking stage, and intermittent heating control within a preset temperature range is adopted.

4. The method for optimizing the energy efficiency of an induction cooker based on cooking behavior recognition according to claim 1, wherein The real-time obtaining of the operation state data during the heating process and calculating the instantaneous power and cumulative energy consumption specifically includes: Obtaining a pair of data of synchronous working current and output voltage within a fixed sampling period Δt, and performing an anomaly comparison on the pair of data with the preset normal current threshold and normal voltage threshold to eliminate abnormal data; Based on the pair of data after eliminating anomalies, calculating the corresponding instantaneous power P for each sampling period according to the instantaneous power calculation formula P = U×I, where U is the output voltage and I is the working current; According to the instantaneous power and the sampling period, the cumulative energy consumption E is calculated by the formula E = Σ(P×Δt), and the energy consumption change rate within a continuous number of the sampling periods is calculated. In the case where the energy consumption change rate exceeds a preset change threshold, an outlier is marked with an abnormal energy consumption event.

5. The method for optimizing the energy efficiency of an electro-ceramic stove based on cooking behavior recognition according to claim 4, wherein The comparison between the cumulative energy consumption and a preset standard energy consumption and the generation of an energy efficiency evaluation result specifically include: According to the cumulative energy consumption value and the standard energy consumption value of the corresponding cooking mode, the energy efficiency deviation ΔE is calculated by the formula ΔE = (E - Es) / Es; Based on the abnormal energy consumption event mark, the cumulative energy consumption is corrected, and then the corrected energy efficiency deviation is recalculated according to the correction result; Based on a preset energy efficiency evaluation standard, the corrected energy efficiency deviation is evaluated, the corresponding energy efficiency status is output, and the energy efficiency evaluation result is obtained.

6. The method for optimizing the energy efficiency of an electro-ceramic stove based on cooking behavior recognition according to claim 5, characterized in that, The correction process of the cumulative energy consumption and then the recalculation of the corrected energy efficiency deviation according to the correction result specifically include: Based on the abnormal energy consumption event mark, the abnormal time period and the corresponding energy consumption change range are extracted. When the time length of the abnormal time period exceeds a set abnormal time threshold and the energy consumption change range exceeds a set energy consumption range threshold, the current abnormal energy consumption event mark is determined to be a valid abnormality, and then the valid abnormality is excluded; Based on the average value of the instantaneous power in the normal sampling periods adjacent to the start and end points of the abnormal segment, the linear interpolation method is used to estimate the normal energy consumption compensation amount of the abnormal segment, and then the corresponding energy efficiency deviation is recalculated as the corrected energy efficiency deviation.

7. An energy efficiency optimization device for an induction cooker based on cooking behavior, characterized in that, The device includes: A temperature data acquisition module, configured to acquire heating temperature data, calculate the temperature change rate and the temperature fluctuation amplitude according to the heating temperature data, and then identify the cookware attribute information; A cooking stage identification module, configured to identify the current cooking stage of the induction cooker based on the temperature change rate, the temperature fluctuation amplitude and the cookware attribute information, and then dynamically adjust the heating power of the induction cooker according to the cooking stage; An operating state monitoring module, configured to acquire the operating state data during the heating process in real time, calculate the current instantaneous power of the induction cooker based on the operating state data, and accumulate and calculate the cumulative energy consumption according to the instantaneous power; An energy efficiency evaluation module, configured to compare the cumulative energy consumption with a preset standard energy consumption after cooking is completed, and generate an energy efficiency evaluation result.

8. The electro-ceramic stove energy efficiency optimization device based on cooking behavior according to claim 7, characterized in that, The temperature data acquisition module specifically includes: A rate calculation sub-module, configured to calculate the corresponding change rate according to the heating temperature data of adjacent sampling points, take the sliding average of the continuous change rates to obtain the temperature change rate, and extract the maximum value and the minimum value of the heating temperature data within a preset time window to calculate the temperature fluctuation amplitude; A cookware identification sub-module, configured to detect the response time difference of the temperature change rate based on a plurality of preset temperature detection zones on the surface of the heating panel, and then determine the placement center position and the occupied area of the cookware, and identify the material type of the cookware according to the heating response characteristic parameters of each detection zone to obtain the cookware attribute information.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method for optimizing the energy efficiency of the electro-ceramic stove based on cooking behavior according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method for optimizing the energy efficiency of the electro-ceramic stove based on cooking behavior according to any one of claims 1 to 6 are implemented.

Images