Method for determining drying power consumption, drying device, drying control method thereof, and electronic device

Abstract

The embodiment of the present disclosure provides a drying power consumption determination method, a drying device and a drying control method thereof, and an electronic device. The power consumption determination method comprises: determining a reference power consumption according to an accumulated temperature rising time length of a temperature rising stage, the temperature rising stage being a time stage in which the inlet air temperature of the inner drum of the drying device rises from the ambient temperature to the preset temperature, and the accumulated temperature rising time length being obtained by detecting the time length consumed in the temperature rising stage; determining a corrected temperature rising time length of the temperature rising stage according to a use cycle parameter of the drying device; and determining the actual power consumption of the drying device according to the accumulated temperature rising time length, the corrected temperature rising time length and the reference power consumption. The present disclosure can improve the prediction accuracy of power consumption.

Description

Technical Field

[0001] This disclosure relates to the field of drying technology, and in particular to a method for determining drying power consumption, drying equipment and its drying control method, and electronic equipment. Background Technology

[0002] With the increasing popularity of washer-dryer combos, users are more eager to understand the power consumption of the drying function in order to determine their usage needs. Therefore, accurately estimating the power consumption of the drying function of a washer-dryer without adding extra electrical components has become an urgent need for users. Summary of the Invention

[0003] This disclosure provides a method for determining drying power consumption, a drying device and its drying control method, and an electronic device to solve or alleviate one or more technical problems in the prior art.

[0004] As a first aspect of this disclosure, this disclosure provides a method for determining drying power consumption, including: The baseline power consumption is determined based on the cumulative heating time of the heating phase. The heating phase is the time it takes for the air inlet temperature of the drying equipment's inner cylinder to rise from the ambient temperature to the preset temperature. The cumulative heating time is the cumulative time consumed during the heating phase. Determine the corrected heating time for the heating stage based on the usage cycle parameters of the drying equipment; The actual power consumption of the drying equipment is determined based on the cumulative heating time, the corrected heating time, and the baseline power consumption.

[0005] In some embodiments, a baseline power consumption is determined based on the cumulative heating duration of the heating phase, including: Based on the weight of the load, a target calculation model is determined. The target calculation model is one of multiple first preset calculation models. The first preset calculation model is used to characterize the relationship between the heating time of the heating stage and the baseline power consumption. The multiple first preset calculation models are configured according to multiple different load weights. The baseline power consumption is determined based on the cumulative heating time and the target calculation model.

[0006] In some embodiments, it also includes: Based on the weight of the load, the power consumption of the drying equipment was tested under different heating times; Based on different heating times and the corresponding power consumption for each heating time, a first preset calculation model is obtained.

[0007] In some embodiments, determining the corrected heating duration for the heating phase based on the usage cycle parameters of the drying equipment includes: Based on the usage cycle parameter and the second preset calculation model, the corrected heating time is determined. The second preset calculation model is used to characterize the relationship between the usage cycle and the heating time.

[0008] In some embodiments, it also includes: The actual usage cycle of the drying equipment is obtained from the controller of the drying equipment, and the actual usage cycle is determined as the usage cycle parameter.

[0009] In some embodiments, it also includes: Obtain the actual temperature of the fan in the drying equipment at a preset time, which is after the end of the heating phase; Based on the actual temperature of the fan, the theoretical service life of the drying equipment is determined, and the theoretical service life is defined as the service life parameter.

[0010] In some embodiments, determining the theoretical service life of the drying equipment based on the actual temperature of the fan includes: Based on the actual temperature of the fan and the third preset calculation model, the theoretical service life is determined. The third preset calculation model is used to characterize the relationship between the inner cylinder temperature and the service life.

[0011] In some embodiments, the actual power consumption of the drying equipment is determined based on the cumulative heating time, the corrected heating time, and the baseline power consumption, including: Calculate the ratio of the corrected heating time to the cumulative heating time; The actual power consumption is determined by multiplying the ratio by the baseline power consumption.

[0012] As a second aspect of this disclosure, this disclosure provides a drying control method for a drying device, including: In response to the activation of the drying function, the power consumption of multiple different drying programs is displayed according to the weight of the load. The drying parameters of the multiple drying programs are different, including at least one of drying temperature and heating power. The power consumption is determined based on the drying program using any of the power consumption determination methods disclosed herein. In response to selecting a target drying program from multiple drying programs, the drying equipment is controlled to execute the target drying program.

[0013] As a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory that is communicatively connected to at least one processor; wherein, The memory stores instructions that can be executed by at least one processor to enable the at least one processor to perform any of the methods of this disclosure.

[0014] As a fourth aspect of the present disclosure, the present disclosure provides a drying device, including a motor, a fan, a heating device, and an inner cylinder. The motor is used to drive the inner cylinder to rotate. The drying device also includes a controller or the electronic device of the present disclosure, the controller being configured to execute the power consumption determination method of the present disclosure.

[0015] The technical solution of this disclosure determines the baseline power consumption based on the cumulative heating time of the heating stage, and corrects the heating time of the heating stage based on the usage cycle parameters of the drying equipment to obtain the corrected heating time of the heating stage. The corrected heating time can accurately reflect the influence of the usage cycle of the drying equipment on the heating time of the heating stage. Therefore, based on the cumulative heating time, the corrected heating time, and the baseline power consumption, the drying power consumption of the drying equipment can be determined more accurately, and the power consumption of the drying equipment can be accurately predicted. This provides a basis for users to select the drying program of the drying equipment and achieves the purpose of energy saving.

[0016] The above overview is for illustrative purposes only and is not intended to be limiting in any way. Further aspects, embodiments, and features of this disclosure will become readily apparent from the accompanying drawings and the following detailed description, in addition to the illustrative aspects, embodiments, and features described above. Attached Figure Description

[0017] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the various drawings denote the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments according to this disclosure and should not be construed as limiting the scope of this disclosure.

[0018] Figure 1 This is a flowchart illustrating a method for determining drying power consumption in one embodiment of the present disclosure; Figure 2 This is the fitted line plot corresponding to the data in Table 1; Figure 3 This is the fitted line plot corresponding to the data in Table 2; Figure 4 The fitted line plot corresponding to the data in Table 3; Figure 5 This is a flowchart illustrating the process of determining the power consumption for drying in one embodiment of this disclosure. Detailed Implementation

[0019] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of this disclosure, and different embodiments can be combined arbitrarily without conflict. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0020] To estimate the power consumption of washer-dryers or drying equipment, related technologies calculate the on / off times of various electrical components, combining the drying process with a power consumption model to obtain the power consumption of the drying function. However, the inventors have found that relying solely on the rated power of electrical equipment and its on / off times is inaccurate. Taking the two most power-consuming components in the drying process—the single-phase asynchronous AC fan and the electric heating element—as examples, the fan's power gradually decreases as the temperature rises, and this power variation is related to the amount of clothing loaded. Furthermore, the electric heating element, as a heating element, can be considered equivalent to a resistor; as the temperature rises, its resistance increases, naturally increasing its power consumption. However, throughout the drying process, the electric heating element is constantly switching on and off, and its power is constantly changing. Therefore, simply relying on its rated power and on / off times cannot provide an accurate estimate of the power consumption.

[0021] To more accurately estimate the power consumption of the drying function, this disclosure provides a method for determining the power consumption of drying. The technical solution of this disclosure is described in detail below through specific embodiments.

[0022] Figure 1 This is a flowchart illustrating a method for determining drying power consumption in one embodiment of the present disclosure, which includes steps S11 to S13.

[0023] In step S11, the baseline power consumption is determined based on the cumulative heating time of the heating stage. The heating stage is the time period during which the air inlet temperature of the inner cylinder of the drying equipment rises from the ambient temperature to the preset temperature. The cumulative heating time is the cumulative time consumed during the heating stage.

[0024] Drying equipment can include dryers with only drying functions, as well as washer-dryer combos. Drying equipment can have multiple different drying programs, also known as drying modes. They can be classified by drying temperature or intensity, such as strong, medium, or weak drying programs; they can also be classified by the material of the clothes being dried, such as cotton / linen programs, synthetic fiber programs, etc. Regardless of the type of drying program, its drying function includes a heating phase.

[0025] For drying equipment, the ambient temperature refers to the temperature of the indoor environment where the drying equipment is located. The specific value of the preset temperature is determined by the corresponding drying program. The time period during which the inlet air temperature of the drying equipment's inner drum rises from the ambient temperature to the preset temperature is called the heating stage. The temperature at the inner drum's air inlet can be detected; this temperature is the inner drum's inlet air temperature. During the heating stage, the inlet air temperature of the drying equipment's inner drum can be monitored in real time. When the detected inlet air temperature reaches the preset temperature, the heating stage is considered to have ended. The drying program may include a heating stage, a high-speed drying stage, and a low-speed drying stage; therefore, the heating stage is a stage in the drying program.

[0026] Understandably, the heating phase can be a slow heating process, during which the intake air temperature can rise continuously and slowly, or the intake air temperature can rise in stages until the intake air temperature reaches the preset temperature, at which point the heating phase ends.

[0027] During the heating process, the duration of each heating phase can be measured to obtain the cumulative heating time, which is the cumulative heating time of the heating phase. It is understandable that during the heating process, the surface of the clothes inside the drum heats up rapidly, and the heating process is a continuous accumulation of heat within the drum. The longer the cumulative heating time, the greater the power consumption of the drying equipment. Therefore, based on this cumulative heating time, a baseline power consumption can be determined.

[0028] In step S12, the corrected heating time for the heating stage is determined based on the usage cycle parameters of the drying equipment.

[0029] The usage cycle of a drying equipment can be understood as either the completion of a full drying process (recorded as one usage cycle) or the single use of the equipment. Each completion of a drying process adds one usage cycle to the equipment's lifespan. The inventors discovered that as the usage cycle increases, the fan airflow gradually decreases, leading to an increase in heating time and consequently, increased power consumption. The inventors have developed a method to obtain usage cycle parameters for the drying equipment. Based on these parameters, the heating time during the heating phase can be adjusted to obtain a corrected heating time.

[0030] In step S13, the actual power consumption of the drying equipment is determined based on the cumulative heating time, the corrected heating time, and the baseline power consumption.

[0031] Under the same drying process, as the drying equipment's usage cycle increases, the heating time of the heating phase will be affected, leading to changes in power consumption. Therefore, by determining the actual power consumption of the drying equipment based on the cumulative heating time, the corrected heating time, and the baseline power consumption, the actual power consumption can be determined more accurately. For example, the actual power consumption here can be understood as the actual power consumption during the heating phase.

[0032] In another embodiment, the actual power consumption during the heating phase is proportional to the total power consumption for completing the entire drying process. The actual power consumption during the heating phase can be multiplied by a proportionality factor to obtain the actual power consumption for the entire drying process.

[0033] The technical solution disclosed herein determines the baseline power consumption based on the cumulative heating time of the heating stage, and corrects the heating time of the heating stage based on the usage cycle parameters of the drying equipment to obtain the corrected heating time of the heating stage. The corrected heating time can accurately reflect the impact of the usage cycle of the drying equipment on the heating time of the heating stage. Therefore, based on the cumulative heating time, the corrected heating time, and the baseline power consumption, the drying power consumption of the drying equipment can be determined more accurately, and the power consumption of the drying equipment can be accurately predicted. This provides a basis for users to select the drying program of the drying equipment and achieves the purpose of energy saving.

[0034] In one embodiment, determining the baseline power consumption based on the cumulative heating time of the heating phase may include: determining a target calculation model based on the weight of the load, wherein the target calculation model is one of a plurality of first preset calculation models, the first preset calculation models being used to characterize the relationship between the heating time of the heating phase and the baseline power consumption, and the plurality of first preset calculation models being configured according to a plurality of different load weights; and determining the baseline power consumption based on the cumulative heating time and the target calculation model.

[0035] The power consumption of a drying equipment is related to the weight of the load, such as clothes. Under the same drying program, the greater the load weight, the greater the power consumption.

[0036] For each drying program, multiple preset calculation models can be configured based on various different load weights. One preset calculation model is configured for each load weight. The load weight corresponding to each preset calculation model can be a weight range.

[0037] When a load needs to be dried, the drying equipment can obtain the weight of the load. The method for detecting the load weight can be any method commonly used in the field, and is not specifically limited here. After obtaining the load weight, based on the load weight, a first preset calculation model matching the load weight can be selected from multiple first preset calculation models, i.e., the target calculation model.

[0038] The first preset calculation model is used to characterize the relationship between the heating duration and the baseline power consumption during the heating phase. This first preset calculation model can be a first neural network model or a functional relationship. After determining the cumulative heating duration, the baseline power consumption can be determined based on the target calculation model.

[0039] In one embodiment, the method for determining power consumption may further include: testing the power consumption of the drying equipment under different heating times based on the weight of the load; and obtaining a first preset calculation model based on different heating times and the power consumption corresponding to each heating time.

[0040] In the calculation of drying power consumption, the power consumption of electrical components varies depending on their operating state. During the drying process, the components with the greatest impact on power consumption are the AC fan, DC motor, and heating devices (such as electric heating elements). The power consumption of the DC motor can be obtained from the drive data of the drying equipment; therefore, only the power consumption of the AC fan and electric heating elements needs to be estimated. However, the surface temperature of the electric heating element is affected by the fan airflow, which in turn is affected by the amount and temperature of the clothes inside the drum. Furthermore, the efficiency of both the fan and the electric heating element also affects the power consumption calculation. Additionally, the airflow gradually decreases over the user's usage period. Therefore, it is difficult to accurately obtain the power consumption of the AC fan and electric heating elements using purely theoretical methods.

[0041] In this embodiment of the disclosure, a first preset calculation model can be established for each load weight, and the baseline power consumption can be predicted through the first preset calculation model.

[0042] For example, the power consumption of the fan and electric heating can be collected separately and multiple times under different load levels to obtain calculation models for the heating time and the baseline power consumption of the drying equipment under different load weight levels.

[0043] For example, for a 1kg load, the heating time during the heating phase is denoted as... t 0, the power consumption during the heating stage of the drying equipment is recorded as P 0. In the drying equipment, different heating times were simulated and the power consumption corresponding to different heating times was collected. Thus, multiple sets of heating time and power consumption data can be obtained, as shown in Table 1.

[0044] Table 1 shows the data on heating time and power consumption for a 1kg load at a preset temperature under different heating times.

[0045] During the heating process, the power consumption of the DC motor can be obtained through the drive of the drying equipment. A power meter can be used to detect the power consumption of the AC fan and the electric heating device separately. The power consumption of these three devices can be summed to obtain the power consumption of the drying equipment. P 0.

[0046] Using the data in Table 1, and based on the different heating times and the corresponding power consumption for each heating time, a first preset calculation model can be obtained by fitting. Figure 2For the fitted line plot corresponding to the data in Table 1, in Figure 2 In the figure, the horizontal axis represents the heating time (i.e., heating duration), and the vertical axis represents the power consumption, resulting in the fitted curve. =0.1542+0.08244 Therefore, in this embodiment, the first preset calculation model is a first functional relationship, namely, the functional relationship between heating time and power consumption. By substituting the cumulative heating time of the heating stage into the functional relationship between heating time and power consumption, the power consumption corresponding to the heating time can be calculated.

[0047] In another embodiment, a first neural network model can be constructed, using different heating durations and corresponding power consumption for each heating duration, with the heating duration as input and power consumption as output, to train the first neural network model, resulting in a trained first neural network model. Inputting the cumulative heating duration of each heating stage into the trained first neural network model yields the power consumption corresponding to that heating duration.

[0048] Under the same drying program, different load weights can correspond to different first preset calculation models. After the load to be dried is placed in the drying equipment, the target calculation model can be determined based on the weight of the load; by detecting the cumulative heating time during the heating stage, the baseline power consumption of the drying equipment under this drying program can be determined based on the cumulative heating time and the target calculation model.

[0049] In one embodiment, determining the corrected heating duration for the heating phase based on the usage cycle parameters of the drying equipment may include: determining the corrected heating duration based on the usage cycle parameters and a second preset calculation model, wherein the second preset calculation model is used to characterize the relationship between the usage cycle and the heating duration.

[0050] It is understandable that the second preset calculation model is configured in correspondence with the drying program, and the second preset calculation model may be different for different drying programs.

[0051] For example, a prototype drying equipment is used to test the heating time of the heating stage under different usage cycles; based on different usage cycles and the heating time corresponding to each usage cycle, a second preset calculation model is obtained.

[0052] As the drying equipment's usage cycle increases, the fan airflow gradually decreases, leading to a longer heating time and an increased actual drying time, resulting in higher power consumption. The relationship between usage cycle and heating time can be tested under the same test conditions as the first preset calculation model. Table 2 shows the data for a 1kg load.

[0053] Table 2 shows the data on different usage cycles and heating times for a 1kg load at a preset temperature.

[0054] Since the heating time remains essentially constant when the usage cycle does not change significantly, the usage cycle in Table 2 is as follows: T 0 is a range. For example, for 100-200, it represents the lifespan of the drying equipment. T When the number of cycles is between 100 and 200, the heating time is... t 1. Approximately 12 minutes. Using the data in Table 2, based on different usage cycles... T 0 and each usage cycle T 0 corresponds to heating time t 1. A second preset calculation model can be obtained by fitting. Figure 3 For the fitted line plot corresponding to the data in Table 2, Figure 3 In the figure, the horizontal axis represents the usage cycle of the drying equipment, and the vertical axis represents the heating time. The resulting fitted curve is as follows: =11.25+0.001417 +0.000016 Therefore, in this embodiment, the second preset calculation model is a second functional relationship, namely, the functional relationship between the heating time and the usage cycle. By substituting the usage cycle of the drying equipment into the second functional relationship, the heating time corresponding to the usage cycle can be calculated, and this heating time is the corrected heating time.

[0055] In another embodiment, a second neural network model can be constructed, using different usage periods and corresponding heating durations for each usage period. The usage period is used as input, and the heating duration is used as output to train the second neural network model, resulting in a trained second neural network model. Inputting the usage period into the trained second neural network model yields the corresponding heating duration for that usage period.

[0056] The inventors discovered that the load weight has little impact on the relationship between the usage cycle and the heating time. Therefore, the second preset calculation model can be applied to any load weight, thereby reducing the amount of data collected.

[0057] In one embodiment, the method for determining the power consumption of drying may further include: obtaining the actual usage cycle of the drying equipment from the controller of the drying equipment, wherein the actual usage cycle is determined as a usage cycle parameter.

[0058] Each time a drying cycle is completed, the controller of the drying equipment increments the usage cycle by 1. Therefore, the actual usage cycle can be obtained from the controller and determined as the usage cycle parameter of the drying equipment, thereby determining the corrected heating time. In this embodiment, it is assumed that the user's usage of the drying equipment is the same each time, that is, the material, weight, and moisture content of the clothes to be dried are within the required range each time the drying equipment is used. Therefore, the actual usage cycle can be determined as the usage cycle parameter.

[0059] It's understandable that different users may use the drying equipment to varying degrees. For example, for users engaged in heavy labor, the material, weight, and moisture content of the clothes to be dried might exceed the drying equipment's requirements, or be at the upper limit of those requirements. For student users, however, the material, weight, and moisture content of the clothes might be at the lower limit of those requirements. Therefore, different users may use the drying equipment to varying degrees. For users who use the drying equipment heavily, their actual usage cycle might be 200 times, but due to the heavy usage, the theoretical usage cycle of the drying equipment might reach 300 times. Conversely, for users who use the drying equipment lightly, their actual usage cycle might be 200 times, but due to the light usage, the theoretical usage cycle (or theoretical usage cycle) might only reach 100 times. Therefore, although the actual usage cycle is 200 times for both users, the theoretical usage cycle is different.

[0060] In one embodiment, when the second preset calculation model is used to determine the corrected heating time, the usage cycle parameter used can be understood as the theoretical usage cycle.

[0061] In one embodiment, the method for determining the power consumption of drying may further include: obtaining the actual temperature of the fan of the drying equipment at a preset time; determining the theoretical service life of the drying equipment based on the actual temperature of the fan, wherein the theoretical service life is determined as a service life parameter, and the preset time is after the end of the heating phase.

[0062] The inventors discovered that considering only airflow attenuation results in an unstable calculated heating time, leading to errors. They further found that varying user loads result in different lint buildup states in the dryer's filter, affecting airflow changes in impact on heating time. The temperature sensor at the fan reflects the actual fan temperature. As the drying cycle increases, airflow decreases, causing the actual fan temperature measured by the sensor to decrease compared to normal airflow, albeit slightly. In other words, the actual fan temperature at the end of the heating phase or after heating is complete reflects the lint buildup state and thus the theoretical lifespan of the dryer. A temperature sensor can be installed near the fan; the temperature detected by this sensor can be considered the actual fan temperature.

[0063] The actual temperature of the fan in the drying equipment can be collected at a preset time, which is either the end of the heating phase or a time after the end of the heating phase. Based on the actual temperature of the fan, the theoretical service life of the drying equipment can be determined, and this theoretical service life can be used as the service life parameter of the drying equipment.

[0064] In this embodiment, the actual temperature of the fan after the heating stage is completed is used to correct the service life of the drying equipment, which can improve the robustness of the first preset calculation model and the second preset calculation model.

[0065] In one embodiment, determining the theoretical service life of the drying equipment based on the actual temperature of the fan includes: determining the theoretical service life based on the actual temperature of the fan and a third preset calculation model, wherein the third preset calculation model is used to characterize the relationship between the inner cylinder temperature and the service life.

[0066] It is understood that the third preset calculation model is configured correspondingly to the drying program, and the third preset calculation model may be different for different drying programs. In another embodiment, since the third preset calculation model is used to characterize the relationship between the inner cylinder temperature and the usage cycle, it is independent of the preset temperature. Therefore, the third preset calculation model can be applied to any drying program.

[0067] For example, the actual temperature of the fan of the drying equipment is tested under different usage cycles using a prototype drying equipment; based on the different usage cycles and the actual fan temperature corresponding to each usage cycle, a third preset calculation model is obtained.

[0068] The service life under normal use was determined by testing the drying equipment. T 0 and the corresponding actual temperature of the fan F 0, resulting in the data in Table 3.

[0069] Table 3 shows the actual temperature data of the fan for different usage periods.

[0070] In Table 3, the usage cycle T 0 represents a specific cycle; in actual implementation, the cycle used is... T 0 represents a possible cycle range. Using the data in Table 3, based on different usage cycles... T 0 and each usage cycle T 0 corresponds to the actual temperature of the fan F 0, a fitting method can be used to obtain the third preset calculation model. Figure 4 For the fitted line plot corresponding to the data in Table 3, Figure 4 In the figure, the horizontal axis represents the service life (theoretical service life) of the drying equipment, and the vertical axis represents the actual temperature of the fan. The resulting fitted curve is as follows: =50.01-0.001014 -0.000007 Therefore, in this embodiment, the third preset calculation model is the third functional relationship, that is, the functional relationship between the actual temperature of the fan and the usage cycle. By substituting the inner cylinder temperature of the drying equipment into the third functional relationship, the usage cycle of the drying equipment corresponding to that inner cylinder temperature can be calculated, that is, the theoretical usage cycle.

[0071] In another embodiment, a third neural network model can be constructed using different usage cycles and the corresponding actual fan temperatures for each usage cycle. The actual fan temperature is used as input, and the usage cycle is used as output to train the third neural network model, resulting in a trained model. Inputting the actual fan temperature into the trained third neural network model yields the theoretical usage cycle corresponding to the inner cylinder temperature.

[0072] In one embodiment, determining the actual power consumption of the drying equipment based on the cumulative heating time, the corrected heating time, and the baseline power consumption includes: calculating the ratio of the corrected heating time to the cumulative heating time; and determining the actual power consumption based on the product of the ratio and the baseline power consumption.

[0073] The actual power consumption is P 实 The ratio of the corrected heating time to the cumulative heating time can be calculated. Based on the product of this ratio and the baseline power consumption, the actual power consumption can be determined. P 实 For example, the actual power consumption can be calculated using formula (1): = Formula (1) Figure 5This is a flowchart illustrating the process of determining the drying power consumption in one embodiment of this disclosure. (Refer to the following...) Figure 5 Detailed explanation of the process for determining drying power consumption. (Reference) Figure 5 The heating phase begins, and the cumulative heating duration of the heating phase is detected. t 0 and the actual temperature of the fan F 0; based on cumulative warming duration t Using a target calculation model, the baseline power consumption is calculated. P 0; using the actual temperature of the fan F 0-correction service cycle, i.e., based on the actual temperature of the fan. F Using the 0th and third preset calculation models, the theoretical usage period is calculated. T 0; based on the theoretical usage cycle T 0 and the second preset calculation model are used to calculate the corrected heating time. t 1; Based on baseline power consumption P 0. Cumulative warming time t 0 and corrected heating time t 1. Calculate the actual power consumption. P 实 .

[0074] It's understandable that the power consumption of a drying device during the heating phase is directly proportional to the overall power consumption of that drying program. Therefore, when the power consumption during the heating phase of a particular drying program is high, the power consumption of the entire drying program will also be high. Determining the actual power consumption of the drying device during the heating phase of a drying program reflects the overall power consumption of the drying device to complete the entire drying process using that program. Therefore, users can refer to the actual power consumption during the heating phase of each drying program and select the program with the lowest actual power consumption to dry clothes, thus achieving energy savings.

[0075] An embodiment of this disclosure also provides a drying control method for a drying device, comprising: in response to the activation of the drying function, displaying the drying power consumption of multiple different drying programs according to the weight of the load, wherein the drying parameters of the multiple drying programs are different, and the drying parameters include at least one of drying temperature and heating power, and the drying power consumption is determined based on the drying program using the drying power consumption determination method of this disclosure; and in response to selecting a target drying program from the multiple drying programs, controlling the drying device to execute the target drying program.

[0076] As mentioned above, drying programs can be categorized by drying temperature or intensity, including strong, medium, or weak drying programs. They can also be categorized by the material of the clothes being dried, including cotton / linen programs, synthetic fiber programs, etc. For each drying program, due to differences in washing rhythm, drying effect, and load type, corresponding first, third, and second preset calculation models are established, and the drying power consumption is determined using the method of this embodiment. The calculated drying power consumption is stored based on the user's historical usage data. When the user activates the drying function, in response to the activation of the drying function, the power consumption of multiple different drying programs is displayed to the user based on the weight of the load, serving as a reminder. The user can select a suitable target drying program from among the multiple programs according to their needs. In response to selecting the target drying program from among the multiple drying programs, the drying equipment is controlled to execute the target drying program to dry the clothes.

[0077] According to embodiments of this disclosure, an electronic device is also provided. The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform the methods of any embodiment of this disclosure.

[0078] This disclosure also provides a readable storage medium storing a computer program that, when executed by a processor, implements the methods as described in any embodiment of this disclosure.

[0079] This disclosure also provides a drying apparatus, which includes a motor, a fan, a heating device, and an inner drum. The motor drives the inner drum to rotate. The drying apparatus also includes a controller or an electronic device according to this disclosure. The controller is configured to perform the methods of this disclosure.

[0080] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0081] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0082] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0083] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0084] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0085] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0086] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0087] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this disclosure, "multiple" means two or more, unless otherwise explicitly specified.

[0088] In this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a communication connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure according to the specific circumstances.

[0089] The foregoing disclosure provides many different implementations or examples for carrying out different structures of this disclosure. To simplify this disclosure, the components and arrangements of specific examples are described above. Of course, these are merely examples and are not intended to limit this disclosure. Furthermore, reference numerals and / or reference letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various implementations and / or arrangements discussed.

[0090] The above are merely specific embodiments of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure, and any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed herein, and the combination of different parts of different embodiments without conflict, should all be covered within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for determining the power consumption of drying, characterized in that, include: The baseline power consumption is determined based on the cumulative heating time of the heating stage. The heating stage is the time period during which the air inlet temperature of the inner cylinder of the drying equipment rises from the ambient temperature to the preset temperature. The cumulative heating time is the cumulative time consumed during the heating stage. The corrected heating duration for the heating stage is determined based on the usage cycle parameters of the drying equipment. The actual power consumption of the drying equipment is determined based on the cumulative heating time, the corrected heating time, and the baseline power consumption.

2. The method according to claim 1, characterized in that, The determination of the baseline power consumption based on the cumulative heating time during the heating phase includes: Based on the weight of the load, a target calculation model is determined. The target calculation model is one of a plurality of first preset calculation models. The first preset calculation model is used to characterize the relationship between the heating time of the heating stage and the baseline power consumption. The plurality of first preset calculation models are configured according to a plurality of different load weights. The baseline power consumption is determined based on the cumulative heating time and the target calculation model.

3. The method according to claim 2, characterized in that, Also includes: Based on the weight of the load, the power consumption of the drying equipment was tested under different heating times; The first preset calculation model is obtained based on the different heating times and the power consumption corresponding to each heating time.

4. The method according to claim 1, characterized in that, The step of determining the corrected heating duration for the heating stage based on the usage cycle parameters of the drying equipment includes: The corrected heating time is determined based on the usage cycle parameter and the second preset calculation model, whereby the second preset calculation model is used to characterize the relationship between the usage cycle and the heating time.

5. The method according to any one of claims 1-4, characterized in that, Also includes: The actual usage cycle of the drying equipment is obtained from the controller of the drying equipment, and the actual usage cycle is determined as the usage cycle parameter.

6. The method according to any one of claims 1-4, characterized in that, Also includes: The actual temperature of the fan of the drying equipment at a preset time is obtained, wherein the preset time is after the end of the heating phase; The theoretical service life of the drying equipment is determined based on the actual temperature of the fan, and the theoretical service life is defined as the service life parameter.

7. The method according to claim 6, characterized in that, The step of determining the theoretical service life of the drying equipment based on the actual temperature of the fan includes: Based on the actual temperature of the fan and the third preset calculation model, the theoretical service life is determined. The third preset calculation model is used to characterize the relationship between the inner cylinder temperature and the service life.

8. The method according to claim 1, characterized in that, The step of determining the actual power consumption of the drying equipment based on the cumulative heating time, the corrected heating time, and the baseline power consumption includes: Calculate the ratio of the corrected heating time to the cumulative heating time; The actual power consumption is determined by multiplying the ratio by the baseline power consumption.

9. A drying control method for a drying device, characterized in that, include: In response to the activation of the drying function, the power consumption of multiple different drying programs is displayed according to the weight of the load. The drying parameters of the multiple drying programs are different, and the drying parameters include at least one of drying temperature and heating power. The power consumption is determined based on the drying program using the method described in any one of claims 1-8. In response to selecting a target drying program from a plurality of drying programs, the drying equipment is controlled to execute the target drying program.

10. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.

11. A drying device, characterized in that, The device includes a motor, a fan, a heating device, and an inner drum, wherein the motor drives the inner drum to rotate, and the drying equipment further includes a controller or the electronic device of claim 10, wherein the controller is configured to perform the method of any one of claims 1-9.

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