Cooking control method and apparatus, storage medium, and cooking device

Abstract

The present disclosure relates to a cooking control method, device, storage medium and cooking equipment, in the case that the real-time cooking state does not satisfy a preset ending condition, obtaining predicted cooking progress data according to cooking sensing data, in the case that the predicted cooking progress data satisfies a preset correction condition, obtaining target cooking control data according to the predicted cooking progress data, expected cooking progress data and reference cooking control data, the expected cooking progress data representing an expected cooking progress corresponding to the cooking object at the target time, thereby being able to timely adjust the cooking behavior of the cooking equipment and avoiding the cooking adjustment not being timely due to the heat preservation and thermal inertia of the cooking equipment.

Description

Technical Field

[0001] This disclosure relates to the field of cooking control, and more particularly to cooking control methods, apparatus, storage media and cooking equipment. Background Technology

[0002] In existing automatic or intelligent cooking processes, a preset cooking curve is invoked for cooking, while temperature and / or humidity sensors monitor the process in real time and adjust the cooking process based on the sensor signals until cooking is complete. However, cooking involves many influencing factors, and the state of the ingredients is complex. Users need to ensure that the pre-treatment of ingredients and the types of cooking accessories are as close as possible to the preset ideal conditions to achieve the expected cooking results. This leads to a significant gap between the user's actual cooking experience and the theoretical upper limit of the product.

[0003] Furthermore, because cooking appliances such as steam ovens have good heat retention performance, the time constant required for cooling is large, and adjustments based on real-time sensor information cannot achieve the ideal cooking effect. Summary of the Invention

[0004] To address at least one of the aforementioned technical problems, this disclosure provides a cooking control method, apparatus, storage medium, and cooking device.

[0005] According to one aspect of this disclosure, a cooking control method is provided, comprising:

[0006] Acquire baseline cooking control data and cooking sensor data;

[0007] Determine the real-time cooking status of the object being cooked based on cooking sensor data;

[0008] If the real-time cooking state does not meet the preset end condition, predicted cooking progress data is obtained based on cooking sensor data. The predicted cooking progress data represents the predicted cooking progress of the cooking object at a target time, where the target time is a time after the current time.

[0009] When the predicted cooking progress data meets the preset correction conditions, target cooking control data is obtained based on the predicted cooking progress data, the expected cooking progress data, and the baseline cooking control data. The expected cooking progress data represents the expected cooking progress of the cooking object at the target time, and the target cooking control data is used for cooking control.

[0010] Optionally, obtaining the target cooking control data based on the predicted cooking progress data, the desired cooking progress data, and the baseline cooking control data includes:

[0011] Get the correction parameters;

[0012] A deviation parameter is obtained based on the predicted cooking progress data and the expected cooking progress data, wherein the deviation parameter characterizes the degree of deviation of the predicted cooking progress data from the expected cooking progress data;

[0013] The baseline cooking control data is corrected based on the correction parameters and the deviation degree parameters to obtain the target cooking control data.

[0014] Optionally, the baseline cooking control data includes a set of baseline cooking control parameters, and the step of obtaining the target cooking control data based on the predicted cooking progress data, the desired cooking progress data, and the baseline cooking control data includes:

[0015] Obtain the level information of the benchmark cooking control parameter set, wherein the level information represents the level of the benchmark cooking control parameter set in a plurality of preset cooking control parameter sets, and the preset cooking control parameter sets include at least one cooking control parameter;

[0016] A deviation parameter is obtained based on the predicted cooking progress data and the expected cooking progress data, wherein the deviation parameter characterizes the degree of deviation of the predicted cooking progress data from the expected cooking progress data;

[0017] The level correction information is obtained based on the deviation degree parameter;

[0018] Based on the level information of the baseline cooking control data and the level correction information, target cooking control data is obtained, wherein the target cooking control data includes a set of target cooking control parameters, and the level corresponding to the set of target cooking control parameters is determined by the level information and the level correction information.

[0019] Optionally, obtaining the level correction information based on the deviation degree parameter includes:

[0020] Obtain grade correction mapping information, which is used to indicate the cooking control grade difference corresponding to the degree of deviation of the predicted cooking progress data from the expected cooking progress data;

[0021] Based on the deviation degree parameter and the level correction mapping information, the level correction information is obtained.

[0022] Optionally, before acquiring the baseline cooking control data and cooking sensor data, the following steps are included:

[0023] Obtain cooking condition data;

[0024] A baseline cooking control parameter set is obtained by matching the cooking condition data and the multiple preset cooking control parameter sets.

[0025] Optionally, the cooking control method further includes:

[0026] If the predicted cooking progress data meets the preset cooking progress conditions, cooking control is performed based on the current cooking control data.

[0027] Optionally, when the predicted cooking progress data meets preset correction conditions, obtaining target cooking control data based on the predicted cooking progress data, expected cooking progress data, and baseline cooking control data includes:

[0028] When the deviation between the predicted cooking progress data and the expected cooking progress data meets the preset deviation state condition, the target cooking control data is obtained based on the predicted cooking progress data, the expected cooking progress data, and the baseline cooking control data.

[0029] Optionally, the target time is a time after the current time, at a preset time interval T from the current time; 20s ≤ T ≤ 30min, or 0.05T. L ≤T≤0.7T L T L This is the total duration of the current cooking stage.

[0030] Optionally, after the current cooking stage ends, the following steps are included:

[0031] The cooking control data at the end of the current cooking stage, the baseline cooking control data corresponding to the current cooking stage, and the baseline cooking control data corresponding to the next cooking stage are obtained. The next cooking stage is the cooking stage that follows the current cooking stage and is adjacent to the current cooking stage.

[0032] Determine the cooking control difference data at the end of the current cooking stage relative to the baseline cooking control data corresponding to the current cooking stage;

[0033] The baseline cooking control data corresponding to the next cooking stage is corrected based on the cooking control difference data to obtain corrected baseline cooking control data, and the corrected baseline cooking control data is used as the baseline cooking control data corresponding to the next cooking stage.

[0034] According to a second aspect of this disclosure, a cooking control device is provided, comprising:

[0035] The data acquisition module is used to acquire baseline cooking control data and cooking sensor data;

[0036] The real-time cooking status determination module is used to determine the real-time cooking status of the cooking object based on cooking sensor data;

[0037] The prediction module is used to obtain predicted cooking progress data based on cooking sensor data when the real-time cooking state does not meet the preset end condition. The predicted cooking progress data represents the predicted cooking progress of the cooking object at a target time, where the target time is a time after the current time.

[0038] The control parameter correction module is used to obtain target cooking control data based on the predicted cooking progress data, expected cooking progress data, and baseline cooking control data, when the predicted cooking progress data meets the preset correction conditions. The expected cooking progress data represents the expected cooking progress of the cooking object at the target time, and the target cooking control data is used for cooking control.

[0039] According to a third aspect of this disclosure, a readable storage medium is provided, wherein at least one instruction or at least one program is stored therein, the at least one instruction or at least one program being loaded and executed by a processor to implement the cooking control method as described above.

[0040] According to a fourth aspect of this disclosure, a cooking device is provided, including a cooking component and at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the at least one processor being used to control the cooking component to perform cooking, and the at least one processor implementing the cooking control method as described above by executing the instructions stored in the memory.

[0041] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.

[0042] Implementing this disclosure will have the following beneficial effects:

[0043] A cooking control method, apparatus, storage medium, and cooking device are provided. When the real-time cooking state does not meet a preset termination condition, predicted cooking progress data is obtained based on cooking sensor data. When the predicted cooking progress data meets a preset correction condition, target cooking control data is obtained based on the predicted cooking progress data, desired cooking progress data, and baseline cooking control data. The desired cooking progress data represents the desired cooking progress of the cooking object at the target time. The target cooking control data is used for cooking control. This enables cooking control correction based on the predicted cooking progress, desired cooking progress data, and baseline cooking control data of the cooking object at the target time. It allows for timely adjustment of the cooking behavior of the cooking device, avoiding untimely cooking adjustments due to the heat preservation and thermal inertia of the cooking device. Furthermore, cooking correction based on the predicted and desired cooking progress data of the cooking object at the target time also enables cooking correction based on actual cooking conditions, preventing deviations from the ideal cooking result due to differences in the user's pre-treatment of ingredients, ingredient combinations, and types of cooking accessories compared to the preset ideal conditions.

[0044] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0045] To more clearly illustrate the technical solutions and advantages in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 A schematic flowchart of a cooking control method according to an embodiment of the present disclosure is shown;

[0047] Figure 2 A schematic flowchart illustrating a process for obtaining target cooking control parameters according to an embodiment of the present disclosure is shown;

[0048] Figure 3 A schematic diagram of another process for obtaining target cooking control parameters according to an embodiment of the present disclosure is shown;

[0049] Figure 4 A schematic diagram of the structure of a cooking control device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0050] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0051] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0052] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0053] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0054] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0055] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0056] Figure 1This diagram illustrates a flowchart of a cooking control method according to an embodiment of the present disclosure. The cooking control method of this invention can be applied to cooking equipment or smart terminals, such as the control unit of the cooking equipment, or a smart terminal communicatively connected to the cooking equipment. The cooking equipment is a device for cooking food or an object to be cooked; for example, the cooking equipment is an oven, steam oven, microwave oven, electric stove, or air fryer. The smart terminal is communicatively connected to at least one cooking equipment, for example, the communication connection can be switched on and off, and it can control the cooking equipment to perform cooking. The smart terminal can be a PC, mobile phone, tablet computer, smart bracelet, or other smart electronic device. This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many steps and does not represent a unique execution order. In actual system or server product execution, the method can be executed sequentially according to the embodiments or drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Figure 1 As shown, the above cooking control method includes:

[0057] Step S101: Acquire baseline cooking control data and cooking sensor data.

[0058] Specifically, the cooking equipment includes cooking components for cooking ingredients or objects, and cooking control parameters are control parameters that control the cooking components to perform cooking. For example, cooking control parameters include heating control parameters or fan operating parameters. Heating control parameters are used to control the heating mechanism in the cooking components to perform heating, such as controlling the heating power of the heating mechanism and whether heating is performed. Fan operating parameters are used to control the fan blade speed and the provided airflow speed of the fan in the cooking components.

[0059] The baseline cooking control data are the cooking control parameters that have not been adjusted or corrected during the cooking process. The baseline cooking control data are determined based on the cooking condition parameters, which include at least one of the following: environmental condition parameters, power supply condition parameters, cooking hardware condition parameters, and cooking object condition parameters. The environmental condition parameters include at least one of the following: ambient temperature, altitude, and air pressure. The power supply condition parameters include at least one of the following: operating voltage and voltage stability. The cooking hardware condition parameters include at least one of the following: cooking equipment type and cooking equipment model. The cooking object condition parameters include at least one of the following: cooking function and cooking object weight.

[0060] In an alternative implementation, the baseline cooking control data is determined based on cooking operation data, and the cooking operation parameters are generated according to the user's cooking operations. For example, an input device receives the user's cooking operations, generates cooking operation data based on the user's cooking operations, and sends the cooking operation data to a cooking control device. The cooking control device generates baseline cooking control data based on the received cooking operation data. The input device is an input operation component or a voice input component, which includes a touch screen and / or at least one button. For example, the input operation component is an operation panel including at least one button. The input device may be located in the cooking device or a smart terminal. In one example, the user places the food to be cooked in the cooking device and selects the desired cooking function (e.g., fermentation, proofing, steaming, baking, or boiling), food weight, or heating method through the input device. The input device receives the user's input operations and generates cooking operation data based on the user's input operations, and sends the cooking operation data to the cooking control device. The cooking control device generates baseline cooking control data based on the received cooking operation data and controls the cooking device to perform cooking according to the baseline cooking control data.

[0061] Cooking sensor data is obtained by monitoring cooking equipment and / or the object being cooked using sensors. These sensors can be at least one of temperature sensors, humidity sensors, weight sensors, image sensors, and distance sensors. The sensors monitor the operating status of the cooking equipment and / or the object being cooked. For example, sensors can monitor temperature, humidity, or wind speed at preset locations or areas within the cooking equipment. Sensors can also monitor the temperature, weight, volume, or appearance of the object being cooked.

[0062] Step S102: Determine the real-time cooking status of the object being cooked based on the cooking sensor data.

[0063] Specifically, the cooking state is the state of the object being cooked itself. For example, the cooking state includes at least one of the following: temperature, weight, volume, shape, moisture content, hardness, and surface color of the object being cooked.

[0064] The real-time cooking status of the cooking object can be determined based on cooking sensor data. Specifically, the cooking object is monitored by sensors to obtain cooking sensor data. The cooking sensor data can determine at least one of the following: temperature, weight, degree of weight change, volume, degree of volume change, shape, height, degree of height change, temperature, moisture content, and surface color of the cooking object, or other cooking statuses of the cooking object.

[0065] Step S103: If the real-time cooking state does not meet the preset termination condition, predicted cooking progress data is obtained based on cooking sensor data. This predicted cooking progress data represents the predicted cooking progress of the cooking object at a target time, which is a time after the current time. Specifically, the cooking process for cooking the object includes at least one cooking stage, preferably 1-6 cooking stages, such as 2, 3, or 4 cooking stages. This facilitates control of the cooking components to perform corresponding cooking treatments on the cooking object at different cooking stages, enabling the cooking object to reach the desired cooking state. Staged cooking allows for accurate control of the cooking treatment and cooking state of the cooking object, facilitating adjustments to the cooking treatment. The cooking components sequentially perform each cooking stage on the cooking object until the entire cooking process is completed.

[0066] Each cooking stage processes the food object to achieve a desired cooking state, which is the state reached by the food object after processing in that stage. Optionally, the current cooking stage ends when the real-time cooking state of the food object meets a preset end condition. For example, if the real-time cooking state of the food object reaches the desired cooking state, or if the real-time cooking state of the food object is the desired cooking state, then the real-time cooking state of the food object meets the preset end condition, and the current cooking stage ends.

[0067] Optionally, before ending the current cooking stage when the real-time cooking state of the object being cooked meets the preset end condition, or before obtaining the predicted cooking progress data based on the cooking sensor data when the real-time cooking state does not meet the preset end condition, the following steps are included:

[0068] Obtain expected state information corresponding to at least one target cooking stage. The expected state information represents the expected cooking state of the cooking object corresponding to the target cooking stage. The expected state information may be preset expected cooking state data or preset state mapping relationship. The state mapping relationship may be the correspondence between the cooking state of the cooking object at the start time of the target cooking stage and the expected cooking state, or the correspondence between the cooking state of the cooking object at the start time of the entire cooking process and the expected cooking state corresponding to the target cooking stage. The target cooking stage is one of at least one cooking stage included in the cooking process. For example, the target cooking stage is the current cooking stage.

[0069] When the desired state information is a preset state mapping relationship, the desired cooking state corresponding to the target cooking stage is obtained based on the desired state information and the cooking state of the cooking object at the start of the target cooking stage, or based on the desired state information and the cooking state of the cooking object at the start of the entire cooking process.

[0070] In an optional implementation, the cooking sensor data includes at least one of the height information, upper surface area information, and volume information of the object being cooked, and the real-time cooking state includes the real-time expansion rate. Determining the real-time cooking state of the object based on the cooking sensor data includes:

[0071] The real-time expansion rate α of the cooking object is obtained based on at least one of the height information, upper surface area data information, and volume information of the cooking object.

[0072] Wherein, the real-time expansion rate α of the cooking object is the ratio of the change in the real-time volume of the cooking object relative to its initial volume at the beginning of the current cooking stage to that initial volume, where the initial volume is the volume of the cooking object at the start of the current cooking stage. The real-time expansion rate α is obtained according to the following formula:

[0073]

[0074] Among them, S C S0 is the real-time volume of the cooking object, obtained from cooking sensor data, for example, from at least one of height information, upper surface area data information, and volume information. S0 is the initial volume of the cooking object in the current cooking stage, obtained from cooking sensor data corresponding to the start time of the current cooking stage.

[0075] Accordingly, ending the current cooking stage when the real-time cooking state of the object being cooked meets the preset end conditions includes:

[0076] When the real-time expansion rate α reaches the preset expansion rate Z, the current cooking stage ends. The preset expansion rate Z is the expected expansion rate of the object being cooked in the current cooking stage.

[0077] Optionally, the preset expansion rate Z can be in the range of 0.2 ≤ Z ≤ 5, preferably 0.5 ≤ Z ≤ 3, for example, Z can be 0.7, 0.8, 0.9, 1.3, 1.5, 2 or 2.5. Thus, when the real-time volume of the cooking object expands relative to its initial volume in the current cooking stage to the preset expansion level or falls back to the preset volume level, the current cooking stage ends.

[0078] Optionally, the cooking sensor data includes color information, which characterizes the detected surface color of the cooking object. The real-time cooking state includes the real-time color state of the cooking object's surface. Determining the real-time cooking state of the cooking object based on the cooking sensor data includes:

[0079] Based on the color information, the real-time color status of the cooking object is obtained.

[0080] During the cooking process of bread, cakes, cookies, roast chicken, or flatbread, the color of the surface of the food gradually changes. The cooking state of the food is determined based on the color state of its surface. The current cooking stage ends when the real-time cooking state of the food meets a preset end condition, including:

[0081] The current cooking phase ends when the real-time color state of the object being cooked reaches the desired color state.

[0082] Specifically, the desired color state is a preset color state. Alternatively, the desired color state is derived from the color state of the cooking object at the start of the current cooking stage. For example, a mapping relationship between the color state of the cooking object at the start of the current cooking stage and the desired color state can be pre-stored. Different mapping relationships can be set for different cooking functions and different cooking objects, allowing users to choose from them or providing appropriate mapping relationships based on their cooking needs. The desired color state is obtained based on the color state of the cooking object at the start of the current cooking stage and this mapping relationship. This improves the flexibility and accuracy of cooking control, enhances adaptability to different ingredients, and improves cooking results.

[0083] Optionally, the cooking sensor data includes the weight information of the object being cooked, and the real-time cooking state includes the real-time weight state. Determining the real-time cooking state of the object based on the cooking sensor data includes:

[0084] Based on the weight information of the object being cooked, the real-time weight status of the object being cooked is obtained.

[0085] The step of ending the current cooking stage when the real-time cooking status of the object being cooked meets the preset end conditions includes:

[0086] The current cooking phase ends when the real-time weight of the object being cooked reaches the desired weight.

[0087] Specifically, the desired weight state is a preset weight state. Alternatively, the desired weight state is obtained based on the weight state of the cooking object at the start of the current cooking stage. For example, a mapping relationship between the weight state of the cooking object at the start of the current cooking stage and the desired weight state is pre-stored. Different mapping relationships are set for different cooking functions and different cooking objects, allowing users to select from them or providing appropriate mapping relationships according to the user's cooking needs. For example, the desired weight is 0.5-0.95 times the weight of the cooking object at the start of the current cooking stage, preferably 0.6-0.9 times, for example, 0.7 times or 0.8 times. The desired weight state is obtained based on the weight state of the cooking object at the start of the current cooking stage and this mapping relationship. This improves the flexibility and accuracy of cooking control, enhances adaptability to different ingredients, and improves cooking results.

[0088] Optionally, the cooking sensor data includes temperature information of the object being cooked, and the real-time cooking state includes real-time temperature status. Determining the real-time cooking state of the object based on the cooking sensor data includes:

[0089] Based on the temperature information of the object being cooked, the real-time temperature status of the object being cooked is obtained.

[0090] The step of ending the current cooking stage when the real-time cooking status of the object being cooked meets the preset end conditions includes:

[0091] The current cooking phase ends when the real-time temperature of the object being cooked reaches the desired temperature.

[0092] Specifically, the desired temperature state is a preset temperature state. Alternatively, the desired temperature state is obtained based on the temperature state of the object being cooked at the start of the current cooking stage. For example, a mapping relationship between the temperature state of the object being cooked at the start of the current cooking stage and the desired temperature state can be pre-stored. Different mapping relationships can be set for different cooking functions and different objects being cooked, allowing users to choose from them or providing suitable mapping relationships according to the user's cooking needs. The desired temperature state is obtained based on the temperature state of the object being cooked at the start of the current cooking stage and this mapping relationship. This improves the flexibility and accuracy of cooking control, enhances adaptability to different ingredients and cooking effects, and is particularly suitable for the heating or temperature rise control stages of ingredients.

[0093] If the real-time cooking state does not meet the preset termination condition, predicted cooking progress data is obtained based on cooking sensor data. For example, if the real-time cooking state of the cooking object does not reach the desired cooking state, such as the real-time weight change, real-time volume change, or real-time surface color of the cooking object does not reach the desired cooking state, then the real-time cooking state of the cooking object does not meet the preset termination condition, and predicted cooking progress data is obtained based on cooking sensor data.

[0094] Specifically, the cooking progress of a cooking object represents the speed or degree of change in the cooking state of the cooking object. For example, a predictive model is used to determine the predicted cooking progress data of the cooking object based on cooking sensor data.

[0095] Optionally, before obtaining the predicted cooking progress data of the cooking object based on the cooking sensor data when the real-time cooking status of the cooking object does not meet the preset termination condition, the following steps are included:

[0096] Step S11: Obtain cooking condition parameters, or cooking condition parameters and initial cooking condition parameters.

[0097] Initial cooking condition parameters are used to indicate the initial state of the cooking process, such as the initial state of the cooking equipment and / or at least part of the initial state of the object being cooked. The initial state of the cooking equipment includes at least one of the internal temperature or internal upper and lower temperature of the cooking equipment, humidity, and fan speed. The initial state of the object being cooked includes the temperature and / or moisture content of the object being cooked.

[0098] Step S12: Obtain the prediction model based on the cooking condition parameters, or based on the cooking condition parameters and the initial cooking condition parameters.

[0099] Optionally, multiple preset prediction models are provided for different cooking equipment, cooking functions, cooking stages, types of cooked objects, combinations of cooked objects, and quantities of cooked objects. A matching prediction model is selected from these multiple prediction models based on cooking condition parameters and used as the prediction model for cooking process control; alternatively, a matching prediction model is selected from these multiple prediction models based on cooking condition parameters and initial cooking condition parameters and used as the prediction model for cooking process control.

[0100] Optionally, the preset multiple prediction models are stored in local memory. For example, the cooking device includes a processing unit and a memory, which pre-stores multiple prediction models. The cooking device is communicatively connected to a cloud-based backend server. The processing unit can actively learn and continuously iterate and update the prediction models based on the historical cooking data of the cooking device and / or historical cooking data of other cooking devices of the same model obtained through the cloud-based backend server. Alternatively, the preset multiple prediction models are stored in a cloud-based backend server. The cloud-based backend server actively learns and continuously iterates and updates the prediction models based on historical cooking data of multiple cooking devices of the same model, and periodically sends the prediction model data to the cooking device. The cooking device receives the prediction model data and stores it in its memory.

[0101] Optionally, the prediction model can be a digital twin model or a neural network model.

[0102] Optionally, the target time is the time after the current time and a preset time T from the current time, where 20s ≤ T ≤ 30min, preferably 30s ≤ T ≤ 20min. For example, T can be 50s, 1min, 3min, 5min, 8min, 10min, 12min, 15min, or 25min. Thus, by setting the value of T, both the accuracy of predicting the cooking progress data and the efficiency of controlling the cooking process are balanced, avoiding a value of T that is too large leading to low prediction accuracy, or a value of T that is too small leading to an inability to adjust the cooking process in a timely manner.

[0103] In an alternative implementation, 0.05T L ≤T≤0.7T L T L This is the total cooking time for the current stage, preferably 0.08T. L ≤T≤0.6T L Specifically, T is 0.1T. L 0.2T L 0.3T L Or 0.5T L Therefore, the value of T is set according to the total duration of the current cooking stage, balancing the accuracy of predicting the cooking progress data with the efficiency of controlling the cooking process. This avoids the situation where a value of T is too large, resulting in low prediction accuracy, or a value of T is too small, resulting in an inability to make timely adjustments to the cooking process.

[0104] Step S104: If the predicted cooking progress data meets preset correction conditions, target cooking control data is obtained based on the predicted cooking progress data, expected cooking progress data, and baseline cooking control data. The expected cooking progress data represents the expected cooking progress of the cooking object at the target time, and the target cooking control data is used for cooking control. Optionally, the expected cooking progress data is obtained based on preset cooking progress information.

[0105] Specifically, the system determines whether cooking control parameters need to be corrected based on the predicted cooking progress data. If the predicted cooking progress data meets preset correction conditions, cooking correction processing is performed based on the predicted cooking progress data, expected cooking progress data, and baseline cooking control data to obtain target cooking control data. This allows for timely adjustments to the cooking behavior of the cooking equipment based on the predicted cooking progress of the object being cooked. This avoids delays in cooking adjustments due to the heat preservation and thermal inertia of the cooking equipment, improving the accuracy of cooking control and enabling the application of the desired cooking action to the object being cooked to achieve the desired cooking effect. Furthermore, it can promptly adjust the cooking behavior of the cooking equipment to improve the cooking effect, addressing discrepancies between the actual and expected cooking progress caused by differences in the pretreatment, type of object being cooked, and types of cooking accessories compared to the preset ideal conditions.

[0106] Optionally, before obtaining the target cooking control data based on the predicted cooking progress data, the desired cooking progress data, and the baseline cooking control data, the following steps are included:

[0107] Obtain preset cooking state information, which represents the cooking state of the object being cooked at different times during the cooking process;

[0108] Based on the cooking status information, the desired cooking progress data is obtained.

[0109] Optionally, the cooking progress information is used to indicate the volume state, weight state, and / or appearance color state of the cooked object at different times during the cooking process. For example, the cooking progress information includes at least one of volume curve data, expansion curve data, weight curve data, and appearance color curve data. The volume curve data represents the volume of the cooked object at different times during the cooking process, the expansion curve data represents the volume expansion rate of the cooked object at different times during the cooking process, the weight curve data represents the weight of the cooked object at different times during the cooking process, and the appearance color data represents the appearance color of the cooked object at different times during the cooking process.

[0110] Optionally, the expected cooking progress data is used to indicate the rate of volume expansion, rate of weight change, or rate of change of appearance color (e.g., rate of change of appearance brightness or rate of change of appearance hue) of the cooking object at the target time. For example, the expected cooking progress data is obtained based on the predicted cooking state of the cooking object at the target time and the initial cooking state of the cooking object at the current cooking stage. Thus, cooking control can be adjusted according to the rate of change of the cooking state of the cooking object from the current cooking stage to the target time, which can ensure the timeliness and stability of cooking control adjustment.

[0111] Preferably, the volume expansion rate characterizes how quickly the volume of the cooking object changes from the initial moment of the current cooking stage to the target moment, and the volume change rate is obtained based on the volume of the cooking object at the target moment and the initial volume of the cooking object at the current cooking stage.

[0112] Preferably, the weight change rate characterizes how quickly the weight of the cooking object changes from the initial moment of the current cooking stage to the target moment, and the weight change rate is obtained based on the weight of the cooking object at the target moment and the initial weight of the cooking object in the current cooking stage.

[0113] Preferably, the rate of change of the surface color characterizes how quickly the surface color of the cooking object changes from the initial moment of the current cooking stage to the target moment, and the rate of change of the surface color is obtained based on the surface color of the cooking object at the target moment and the initial surface color of the cooking object at the current cooking stage.

[0114] Figure 2 This diagram illustrates a flowchart of obtaining target cooking control data according to an embodiment of the present disclosure. The step of obtaining the target cooking control data based on predicted cooking progress data, desired cooking progress data, and baseline cooking control data includes:

[0115] Step S21: Obtain the correction parameters.

[0116] Specifically, the correction parameter is a preset correction constant. Optionally, at least one set of correction parameters is preset, preferably including 1-3 correction parameters, and the corresponding set of correction parameters is obtained based on the predicted cooking progress data and the expected cooking progress data. For example, the set of correction parameters includes a weight correction parameter k and a bias parameter b.

[0117] In one optional implementation, two sets of correction parameters are preset: a first set of correction parameters and a second set of correction parameters. The first set of correction parameters includes a first weight correction parameter k1 and a first bias parameter b1, and the second set of correction parameters includes a second weight correction parameter k2 and a second bias parameter b2. If the predicted cooking progress data and the expected cooking progress data meet a first preset correction condition, the first set of correction parameters is used for cooking correction; if the predicted cooking progress data and the expected cooking progress data meet a second preset correction condition, the second set of correction parameters is used for cooking correction.

[0118] In an alternative implementation, a set of correction parameters is preset, and the cooking correction is directly performed using this set of correction parameters.

[0119] Step S22: Obtain a deviation parameter based on the predicted cooking progress data and the expected cooking progress data. The deviation parameter characterizes the degree of deviation of the predicted cooking progress data from the expected cooking progress data.

[0120] Specifically, the deviation parameter y characterizes the predicted cooking progress data g. p Relative to the expected cooking progress data g 期 The degree of deviation, the deviation parameter y, is obtained according to the following formula:

[0121]

[0122] Step S23: Correct the baseline cooking control data according to the correction parameter and the deviation degree parameter to obtain the target cooking control data.

[0123] Specifically, in this embodiment, target cooking control data is obtained based on the correction of the baseline cooking control data. This correction process introduces correction parameters and deviation parameters, so that the correction of the cooking control parameters is related to the progress level and deviation of the predicted cooking progress data relative to the expected cooking progress data, thereby improving the accuracy of the correction of cooking control.

[0124] Optional, predict cooking progress data g p For the predicted rate of volume expansion, predicted degree of weight change, or predicted degree of color change of the object being cooked at the target time, the expected cooking progress data g is... 期 It refers to the expected rate of volume expansion, the expected degree of weight change, or the expected degree of appearance color change of the cooking object at the target time.

[0125] For example, the volume expansion rate m t The following formula is used to obtain:

[0126]

[0127] Where t is the time elapsed since the beginning of the current cooking stage, and M... t This refers to the volume of the cooking object at the current cooking stage, a time t from its initial moment. For example, this volume is the predicted or expected volume, where M0 is the initial volume of the cooking object in the current cooking stage. The predicted volume expansion rate m of the cooking object at the target time is also considered. p and the expected volume expansion rate m 期 All are obtained based on the above formula.

[0128] The desired volume expansion rate is 0-1 min. -1 Preferred time: 0-0.6 min -1 Specifically, 0-0.4min -1 For example, 0.05min -1 0.08min -1 0.1min -1 0.3min -1 0.7min -1 or 0.8min -1 The value of the expected volume expansion rate can change over time.

[0129] The cooking control data are parameters used for cooking control, such as cooking temperature, fan speed, or cooking humidity.

[0130] Optional, target cooking temperature d 目 The following formula is used to obtain:

[0131]

[0132] Where, d 基 The reference cooking temperature is the cooking temperature at the current cooking stage, determined based on the cooking parameters.

[0133] For embodiments that include a first set of correction parameters and a second set of correction parameters, k is k1 or k2, and b is b1 or b2.

[0134] Optional, in m p ≥m 期 In the case of +M1, the first set of correction parameters is used for control correction, i.e., k is k1, b is b1, and d... 目 The range of values ​​can be selected as follows: Optionally, M1 is a constant, ranging from 0.001 to 1 min. -1 For example, 0.1min -1 0.3min -1 0.5min -1 0.6min-1 or 0.8 min -1 ; alternatively, 0 < M1 ≤ 0.2 m 期 , preferably, 0.05 m 期 < M1 ≤ 0.15 m 期 .

[0135] optionally, when m p ≤ m 期 - M2, the second correction parameter set is used for control correction, that is, k is k2, b is b2, d 目 the value range can optionally be optionally, M2 is a constant, and the value range is 0.001-0.5 min -1 , for example 0.1 min -1 , 0.3 min -1 or 0.4 min -1 ; alternatively, 0 < M2 ≤ 0.2 m 期 , preferably, 0 < M2 ≤ 0.1 m 期 , particularly 0.05 m 期 < M2 ≤ 0.08 m 期 .

[0136] optionally, 0 < k1 ≤ 0.8, k1 is preferably 0.1-0.5, for example 0.3, 0.4, 0.55 or 0.6.

[0137] optionally, 0 < k2 ≤ 0.8, k2 is preferably 0.1-0.6, for example 0.3, 0.4, 0.45, 0.5 or 0.55.

[0138] optionally, 0.5d 基 ≤ b1 ≤ d 基 , for example b1 is 0.6d 基 , 0.8d 基 or 0.9d 基 .

[0139] optionally, 0.5d 基 ≤ b2 ≤ d 基 , for example b2 is 0.6d 基 , 0.8d 基 or 0.9d 基 .

[0140] In an optional embodiment, said obtaining target cooking control data based on predicted cooking progress data, expected cooking progress data and reference cooking control data when said predicted cooking progress data meets a preset correction condition comprises:

[0141] When the deviation between the predicted cooking progress data and the expected cooking progress data meets the preset deviation state condition, the target cooking control data is obtained based on the predicted cooking progress data, the expected cooking progress data, and the baseline cooking control data.

[0142] Therefore, when the predicted cooking progress data deviates significantly from the expected cooking progress data, the cooking control parameters are corrected to obtain the target cooking control parameters. For example, if δ p ≤δ 期 -δ1, or δ p ≥δ 期 If +δ2 is applied, then cooking control corrections are performed; where δ1 and δ2 are constants. Optionally, 0 < δ1 ≤ 0.2m 期 Preferably, 0 < δ1 ≤ 0.1m 期 Especially 0.05m 期 <δ1≤0.08m 期 ; 0 < δ² ≤ 0.2δ 期 Preferably, 0 < δ2 ≤ 0.1δ 期 Especially 0.05δ 期 <δ2≤0.15δ 期 .

[0143] Figure 3 A schematic flowchart illustrating the process of obtaining target cooking control data according to another embodiment of this disclosure is shown. In an alternative embodiment, the baseline cooking control data includes a set of baseline cooking control parameters, and obtaining the target cooking control data based on predicted cooking progress data, desired cooking progress data, and baseline cooking control data includes:

[0144] Step S31: Obtain the level information of the benchmark cooking control parameter set. The level information represents the level of the benchmark cooking control parameter set in multiple preset cooking control parameter sets. The benchmark cooking control parameter set includes at least one cooking control parameter.

[0145] Specifically, multiple preset cooking control parameter sets at different levels are provided. These preset cooking control parameter sets include cooking control parameters such as cooking temperature and / or fan speed, and different preset cooking control parameter sets correspond to different cooking intensities. For example, three preset cooking control parameter sets are provided, namely preset cooking control parameter sets at levels 1, 2, and 3. The level 1 preset cooking control parameter set corresponds to a first cooking temperature or a first cooking temperature curve, the level 2 preset cooking control parameter set corresponds to a second cooking temperature or a second cooking temperature curve, and the level 3 preset cooking control parameter set corresponds to a third cooking temperature or a third cooking temperature curve. At any given cooking time, the first cooking temperature is lower than the second cooking temperature, and the second cooking temperature is lower than the third cooking temperature.

[0146] The cooking functions include steaming, baking, steam-baking, hot air baking, fermentation, baking cookies or bread, etc.

[0147] Optionally, a set of preset cooking control parameters corresponding to at least one cooking function is provided, wherein the set of preset cooking control parameters includes multiple preset cooking control parameter sets at different levels. Optionally, the set of preset cooking control parameters includes 3-12 preset cooking control parameter sets at different levels, preferably 5-10 preset cooking control parameter sets, such as 6 or 8 preset cooking control parameter sets, thereby improving the accuracy of cooking control.

[0148] In an optional implementation, prior to acquiring the baseline cooking control data and cooking sensor data, the following steps are included:

[0149] Obtain cooking condition data;

[0150] A baseline cooking control parameter set is obtained by matching the cooking condition data and the multiple preset cooking control parameter sets.

[0151] Therefore, a set of preset cooking control parameters that matches the cooking condition data is selected from the plurality of preset cooking control parameter sets as the benchmark cooking control parameter set.

[0152] Step S32: Obtain a deviation parameter based on the predicted cooking progress data and the expected cooking progress data. The deviation parameter characterizes the degree of deviation of the predicted cooking progress data from the expected cooking progress data.

[0153] Step S33: Obtain level correction information based on the deviation degree parameter.

[0154] Specifically, the level correction information indicates the level adjustment level used for cooking control correction, thereby correcting the level of the baseline cooking control data according to the degree of deviation of the predicted cooking progress data from the expected cooking progress data, and improving the accuracy of cooking control correction.

[0155] Optionally, obtaining the level correction information based on the deviation degree parameter includes:

[0156] Obtain grade correction mapping information, which is used to indicate the cooking control grade difference corresponding to the degree of deviation of the predicted cooking progress data from the expected cooking progress data;

[0157] Based on the deviation degree parameter and the level correction mapping information, the level correction information is obtained.

[0158] Therefore, level correction information is obtained through preset level correction mapping information. The level correction mapping information is the mapping relationship information between the deviation degree parameter and the level difference, or the level correction mapping information is the correspondence information between the deviation degree parameter and the level difference. For example, each level difference corresponds to a certain deviation degree range. By comparing the deviation degree parameter with the deviation degree range corresponding to each level difference, the level difference corresponding to the deviation degree parameter, such as -1 level, -2 level or +1 level, is used as the level correction information.

[0159] Step S34: Based on the level information of the baseline cooking control data and the level correction information, target cooking control data is obtained, wherein the target cooking control data includes a set of target cooking control parameters, and the level corresponding to the set of target cooking control parameters is determined by the level information and the level correction information.

[0160] Therefore, this embodiment corrects the cooking control by adjusting the level of the baseline cooking control data according to the degree of deviation of the predicted cooking progress data from the expected cooking progress data. By setting a certain number of preset cooking control parameter sets, accurate cooking control can be achieved, and the computational cost and accuracy of cooking control can be effectively balanced. Moreover, the calculation process is simple and the computational cost is low, which can reduce production costs.

[0161] In an optional implementation, the cooking control method further includes:

[0162] If the predicted cooking progress data meets the preset cooking progress conditions, cooking control is performed based on the current cooking control data.

[0163] Therefore, if the predicted cooking progress data meets the preset cooking progress conditions, no cooking control correction is made, and the current cooking control data continues to be used for cooking control. For example, if the predicted cooking progress data does not deviate from the expected cooking progress data or the deviation from the expected cooking progress data is small, no correction is made to the cooking control parameters.

[0164] For example, if m 期 -M2 <m p <m 期 If +M1 is reached, it is determined that the predicted cooking progress data meets the preset cooking progress conditions, and the current cooking control data continues to be used for cooking control. Where 0 < δ1 ≤ 0.2δ 期 Preferably, 0 < δ1 ≤ 0.1δ 期 , 0 < δ² ≤ 0.2δ 期 Preferably, 0 < δ2 ≤ 0.1δ 期 .

[0165] In an optional implementation, for a cooking process comprising two or more cooking stages, the step of ending the current cooking stage includes:

[0166] Step S41: Obtain the cooking control data at the end of the current cooking stage, the baseline cooking control data corresponding to the current cooking stage, and the baseline cooking control data corresponding to the next cooking stage. The next cooking stage is the cooking stage that follows the current cooking stage and is adjacent to the current cooking stage.

[0167] Step S42: Determine the cooking control difference data between the cooking control data at the end of the current cooking stage and the baseline cooking control data corresponding to the current cooking stage.

[0168] Specifically, the cooking control difference data is used to indicate the cooking control difference between the cooking control data at the end of the current cooking stage and the baseline cooking control data corresponding to the current cooking stage. Optionally, the cooking control difference data is the difference in control value or level between the cooking control data at the end of the current cooking stage and the baseline cooking control data corresponding to the current cooking stage.

[0169] For example, the cooking control difference data includes cooking temperature difference data, which characterizes the temperature difference level between the cooking temperature parameter or cooking temperature curve at the end of the current cooking stage and the reference cooking temperature parameter or reference cooking temperature curve corresponding to the current cooking stage, and the cooking temperature difference data ΔT 温度差异 The following formula is used to obtain:

[0170] △T 温度差异 =T 结束烹饪温度 -T 基准烹饪温度

[0171] Among them, T 结束烹饪温度 The cooking temperature parameter T corresponds to the cooking temperature parameter at the end of the current cooking stage. 基准烹饪温度 This is the baseline cooking temperature parameter for the current cooking stage.

[0172] Step S43: Correct the baseline cooking control data corresponding to the next cooking stage according to the cooking control difference data to obtain the corrected baseline cooking control data, and use the corrected baseline cooking control data as the baseline cooking control data corresponding to the next cooking stage, so as to perform cooking control of the next cooking stage according to the corrected baseline cooking control data.

[0173] For example, the modified reference cooking control data includes a modified reference cooking temperature parameter, T′. 修正基温The following formula is used to obtain:

[0174] T′ 修正基温 =T′ 基温 +△T 温度差异

[0175] Among them, T′ 基温 This serves as the reference cooking temperature parameter for the next cooking stage.

[0176] Then, the baseline cooking control data T′ corresponding to the next cooking stage will be... 基温 Updated to T′ 修正基温 :T′ 修正基温 →T′ 基温 Then, proceed with the cooking control for the next cooking stage.

[0177] In an alternative implementation, the cooking control difference data includes cooking control level difference data, which indicates the level difference between the cooking control data at the end of the current cooking stage and the baseline cooking control data corresponding to the current cooking stage. The baseline cooking control data corresponding to the next cooking stage is corrected by adjusting the level of the baseline cooking control data based on the cooking control level difference data.

[0178] Therefore, for a cooking process that includes multiple cooking stages, the baseline cooking control data corresponding to each cooking stage after the first cooking stage is corrected and updated based on the cooking control correction behavior of the previous cooking stage. The corrected baseline cooking control data is then used to update the baseline cooking control data corresponding to the next cooking stage. The updated baseline cooking control data corresponding to the next cooking stage is the corrected baseline cooking control data. Thus, by importing the previous cooking corrections into the next cooking stage before proceeding, the accuracy of cooking control can be improved.

[0179] Figure 4 A block diagram of a cooking control device according to an embodiment of the present disclosure is shown; as follows: Figure 4 As shown, the above-mentioned device includes:

[0180] The data acquisition module is used to acquire baseline cooking control data and cooking sensor data;

[0181] The real-time cooking status determination module is used to determine the real-time cooking status of the cooking object based on cooking sensor data;

[0182] The prediction module is used to obtain predicted cooking progress data based on cooking sensor data when the real-time cooking state does not meet the preset end condition. The predicted cooking progress data represents the predicted cooking progress of the cooking object at a target time, where the target time is a time after the current time.

[0183] The control parameter correction module is used to obtain target cooking control data based on the predicted cooking progress data, expected cooking progress data, and baseline cooking control data, when the predicted cooking progress data meets the preset correction conditions. The expected cooking progress data represents the expected cooking progress of the cooking object at the target time, and the target cooking control data is used for cooking control.

[0184] In some embodiments, the cooking control device provided in this disclosure may have functions or include modules that can be used to execute the cooking control method described in the above embodiments. The specific implementation can be referred to the description in the above embodiments, and for the sake of brevity, it will not be described again here.

[0185] This disclosure also proposes a readable storage medium storing at least one instruction or at least one program, which is loaded and executed by a processor to implement the cooking control method as described above.

[0186] This disclosure also proposes a cooking device, including a cooking component and at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the at least one processor is used to control the cooking component to perform cooking, and the at least one processor implements the above-mentioned cooking control method by executing the instructions stored in the memory.

[0187] This disclosure also proposes an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor implements the cooking control method by executing the instructions stored in the memory.

[0188] Electronic devices can be provided as terminals, servers, or other forms of devices.

[0189] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A cooking control method, characterized in that, include: Acquire baseline cooking control data and cooking sensor data; Determine the real-time cooking status of the object being cooked based on cooking sensor data; If the real-time cooking state does not meet the preset end condition, predicted cooking progress data is obtained based on cooking sensor data. The predicted cooking progress data represents the predicted cooking progress of the cooking object at a target time, where the target time is a time after the current time. When the predicted cooking progress data meets the preset correction conditions, target cooking control data is obtained based on the predicted cooking progress data, the expected cooking progress data, and the baseline cooking control data. The expected cooking progress data represents the expected cooking progress of the cooking object at the target time, and the target cooking control data is used for cooking control. The baseline cooking control data includes a set of baseline cooking control parameters. The step of obtaining target cooking control data based on predicted cooking progress data, desired cooking progress data, and baseline cooking control data includes: Obtain the level information of the benchmark cooking control parameter set, wherein the level information represents the level of the benchmark cooking control parameter set in a plurality of preset cooking control parameter sets, and the preset cooking control parameter sets include at least one cooking control parameter; A deviation parameter is obtained based on the predicted cooking progress data and the expected cooking progress data, wherein the deviation parameter characterizes the degree of deviation of the predicted cooking progress data from the expected cooking progress data; The level correction information is obtained based on the deviation degree parameter; Based on the level information of the baseline cooking control data and the level correction information, target cooking control data is obtained, wherein the target cooking control data includes a set of target cooking control parameters, and the level corresponding to the set of target cooking control parameters is determined by the level information and the level correction information; After the current cooking stage is completed, including: The cooking control data at the end of the current cooking stage, the baseline cooking control data corresponding to the current cooking stage, and the baseline cooking control data corresponding to the next cooking stage are obtained. The next cooking stage is the cooking stage that follows the current cooking stage and is adjacent to the current cooking stage. Determine the cooking control difference data at the end of the current cooking stage relative to the baseline cooking control data corresponding to the current cooking stage; The baseline cooking control data corresponding to the next cooking stage is corrected based on the cooking control difference data to obtain corrected baseline cooking control data, and the corrected baseline cooking control data is used as the baseline cooking control data corresponding to the next cooking stage.

2. The cooking control method according to claim 1, characterized in that, The step of obtaining the level correction information based on the deviation degree parameter includes: Obtain grade correction mapping information, which is used to indicate the cooking control grade difference corresponding to the degree of deviation of the predicted cooking progress data from the expected cooking progress data; Based on the deviation degree parameter and the level correction mapping information, the level correction information is obtained.

3. The cooking control method according to claim 1 or 2, characterized in that, Before acquiring the baseline cooking control data and cooking sensor data, the following steps are included: Obtain cooking condition data; A baseline cooking control parameter set is obtained by matching the cooking condition data and the multiple preset cooking control parameter sets.

4. The cooking control method according to claim 1 or 2, characterized in that, The method further includes: If the predicted cooking progress data meets the preset cooking progress conditions, cooking control is performed based on the current cooking control data.

5. The cooking control method according to claim 1 or 2, characterized in that, When the predicted cooking progress data meets the preset correction conditions, the target cooking control data is obtained based on the predicted cooking progress data, the expected cooking progress data, and the baseline cooking control data, including: When the deviation between the predicted cooking progress data and the expected cooking progress data meets the preset deviation state condition, the target cooking control data is obtained based on the predicted cooking progress data, the expected cooking progress data, and the baseline cooking control data.

6. The cooking control method according to claim 1 or 2, characterized in that, The target time is the time after the current time, a preset time T away from the current time; 20s ≤ T ≤ 30min, or 0.05T. L ≤T≤0.7T L T L This is the total duration of the current cooking stage.

7. A cooking control device, characterized in that, include: The data acquisition module is used to acquire baseline cooking control data and cooking sensor data; The real-time cooking status determination module is used to determine the real-time cooking status of the cooking object based on cooking sensor data; The prediction module is used to obtain predicted cooking progress data based on cooking sensor data when the real-time cooking state does not meet the preset end condition. The predicted cooking progress data represents the predicted cooking progress of the cooking object at a target time, where the target time is a time after the current time. The control parameter correction module is used to obtain target cooking control data based on the predicted cooking progress data, expected cooking progress data, and baseline cooking control data, when the predicted cooking progress data meets the preset correction conditions. The expected cooking progress data represents the expected cooking progress of the cooking object at the target time, and the target cooking control data is used for cooking control. The baseline cooking control data includes a set of baseline cooking control parameters. The step of obtaining target cooking control data based on predicted cooking progress data, desired cooking progress data, and baseline cooking control data includes: Obtain the level information of the benchmark cooking control parameter set, wherein the level information represents the level of the benchmark cooking control parameter set in a plurality of preset cooking control parameter sets, and the preset cooking control parameter sets include at least one cooking control parameter; A deviation parameter is obtained based on the predicted cooking progress data and the expected cooking progress data, wherein the deviation parameter characterizes the degree of deviation of the predicted cooking progress data from the expected cooking progress data; The level correction information is obtained based on the deviation degree parameter; Based on the level information of the baseline cooking control data and the level correction information, target cooking control data is obtained, wherein the target cooking control data includes a set of target cooking control parameters, and the level corresponding to the set of target cooking control parameters is determined by the level information and the level correction information; After the current cooking stage is completed, including: The cooking control data at the end of the current cooking stage, the baseline cooking control data corresponding to the current cooking stage, and the baseline cooking control data corresponding to the next cooking stage are obtained. The next cooking stage is the cooking stage that follows the current cooking stage and is adjacent to the current cooking stage. Determine the cooking control difference data at the end of the current cooking stage relative to the baseline cooking control data corresponding to the current cooking stage; The baseline cooking control data corresponding to the next cooking stage is corrected based on the cooking control difference data to obtain corrected baseline cooking control data, and the corrected baseline cooking control data is used as the baseline cooking control data corresponding to the next cooking stage.

8. A readable storage medium, characterized in that, The readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the cooking control method as described in any one of claims 1 to 6.

9. A cooking device, characterized in that, The device includes a cooking component and at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the at least one processor being used to control the cooking component to perform cooking, and the at least one processor implementing the cooking control method as described in any one of claims 1 to 6 by executing the instructions stored in the memory.

Images