CN108060548B - Washing machine system based on big data and washing control method - Google Patents
Washing machine system based on big data and washing control method Download PDFInfo
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- CN108060548B CN108060548B CN201810133207.4A CN201810133207A CN108060548B CN 108060548 B CN108060548 B CN 108060548B CN 201810133207 A CN201810133207 A CN 201810133207A CN 108060548 B CN108060548 B CN 108060548B
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- 238000005406 washing Methods 0.000 title claims abstract description 286
- 238000000034 method Methods 0.000 title claims description 32
- 238000012545 processing Methods 0.000 claims abstract description 45
- 230000005611 electricity Effects 0.000 claims description 122
- 238000005265 energy consumption Methods 0.000 claims description 40
- 238000004140 cleaning Methods 0.000 claims description 27
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 17
- 230000003749 cleanliness Effects 0.000 claims description 14
- 238000010438 heat treatment Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 4
- 238000011086 high cleaning Methods 0.000 claims description 3
- 230000001172 regenerating effect Effects 0.000 claims description 3
- 238000002791 soaking Methods 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims 1
- 239000007924 injection Substances 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 6
- 238000001035 drying Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 3
- 238000004659 sterilization and disinfection Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 2
- 230000001954 sterilising effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
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- D—TEXTILES; PAPER
- D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
- D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
- D06F33/00—Control of operations performed in washing machines or washer-dryers
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Abstract
The invention discloses a washing machine system based on big data, which comprises a central processing module, a washing control module, a washing module, a positioning module and an access gateway, wherein the access gateway is accessed to the Internet through a wireless route, and the washing machine system also comprises a washing machine manufacturer cloud server connected with the washing control module through the Internet and an urban government affair platform server connected with the washing machine manufacturer cloud server; the central processing module is respectively connected with the washing control module, the positioning module and the access gateway; the washing control module is connected with the washing module and is used for controlling the washing module to carry out washing operation.
Description
Technical Field
The invention relates to the field of washing machines, in particular to a washing machine system based on big data and a washing control method.
Background
At present, the market popularity of washing machines in China exceeds 76%, the market of towns exceeds 96%, and the market of rural areas exceeds 53% from the national scale, and washing machine enterprises aim at the rural market with larger consumption potential along with the national development of the policies of household appliances going to the countryside and expanding internal needs. In the coming years, the market demand growth space of the washing machine in China mainly comes from the first demand mainly based on the urbanization and rural market and the updating demand mainly based on the urban market consumption upgrading, and the market demand of the whole washing machine is kept in a mild growth state in the coming years.
In 2010, the total sales of washing machines in China is about 5000 more than ten thousand, the year-by-year increase is close to 30%, the highest level of history is created by the increase amplitude, wherein 3300 more than ten thousand washing machines are sold in China, the year-by-year increase is about 28%, 1600 more than ten thousand washing machines are sold in China, the year-by-year increase is more than 30%, and the highest increase speed of history is created uniformly.
From different products, the total sales of the drum washing machines in China in 2010 reaches over 1100 thousands of machines, the sales increase is more than 50% on year-by-year basis, and the sales of the drum washing machines in the year-by-year basis is increased from less than 20% to more than 20%. Wherein, the sales in each month in the fourth quarter exceed 110 million, and the share of the total sales in the market of the washing machine exceeds 21 percent.
Water conservation becomes the key development direction of future washing machines, and the industrial targets of the washing machines mainly cover three major directions of electricity and water conservation, product functions and green design. In the technical route diagrams of refrigerators, air conditioners and washing machines compiled by the Chinese household electrical appliance Association, the technical route diagrams of the refrigerators, the air conditioners and the washing machines are made in the aspect of electricity saving and water saving, in 2015, the impeller type double-drum washing machine reaches the national energy efficiency level 2, the impeller type full-automatic washing machine reaches the national energy efficiency level 1, the drum type full-automatic washing machine with the energy efficiency level 1 meets the requirements of European Union A + level electricity consumption and water consumption, and the drum type washing and drying integrated machine meets the requirements of GB/T23118 national standard A level electricity consumption and water consumption. In 2020, the roller washing machine reaches the requirement of European Union A + + + grade power consumption and water consumption, the impeller type full-automatic washing machine reaches the requirement of national standard A + grade power consumption and water consumption, and the roller type washing and drying integrated machine reaches the requirement of national standard A + grade power consumption and water consumption. In terms of product functions, the development direction of the washing machine is high capacity, low noise and low vibration.
The traditional washing machine can only wash according to the instruction requirement of a user, but cannot wash according to the power consumption condition of washing and the historical use condition of washing, which is a problem to be solved.
Disclosure of Invention
An object of the present invention is to provide a washing machine system and a washing control method based on big data, which enable a washing machine to wash clothes according to the power consumption of the washing machine and the historical use of the washing machine.
Specifically, the invention is realized by the following technical scheme:
a washing machine system based on big data comprises a central processing module, a washing control module, a washing module, a positioning module and an access gateway, wherein the access gateway is accessed to the Internet through a wireless route, and further comprises a washing machine manufacturer cloud server connected with the washing control module through the Internet and an urban government affair platform server connected with the washing machine manufacturer cloud server; the central processing module is respectively connected with the washing control module, the positioning module and the access gateway; the washing control module is connected with the washing module and is used for controlling the washing module to carry out washing operation.
A laundry control method of big data based washing machine system using the aforementioned big data based washing machine system, the method comprising the steps of:
s1: the central processing module detects whether the washing machine is started for the first time or whether a positioning change signal is received, if so, S2 is executed;
s2: the central processing module calls the positioning module to determine the geographical position of the current washing machine and determine the city information of the washing machine;
s3: according to the city information, the central processing module finds out the government affair platform server address of the corresponding city from the locally stored city government affair platform server addresses;
s4: the central processing module accesses the government affair platform server through the gateway;
s5: the central processing unit obtains the current time;
s6: the central processing unit calls historical electricity utilization information of a user in a preset time range before and after the current time from the government affair platform server according to the current time;
s7: the central processing unit calls a washing machine use record in a preset time range before and after the current moment according to the current moment, wherein the washing machine use record comprises the use time of the washing machine and the washing step;
s8: the central processing unit counts the historical electricity utilization information and the use record of the washing machine within the preset duration range, determines the relation between the washing time and the electricity consumption, and calculates the average electricity consumption at the current washing time;
s9: the central processing unit calls the washing control module to control the washing module to wash, predicts the electricity consumption of each washing step in real time in the washing process, and gives an alarm when the total predicted electricity consumption of a plurality of washing steps is larger than the average electricity consumption.
Preferably, the S9 includes:
s91: the washing control module receives a washing instruction input by a user, wherein the washing instruction comprises an execution sequence of washing steps and an execution time of each washing step;
s92: determining the electricity price time period of each washing step; and predicting the electricity consumption of each washing step according to the preset energy consumption of each washing step and the electricity price of the electricity price time period, and giving an alarm to a user if the total predicted electricity consumption is greater than the average electricity consumption.
Preferably, after S92, the method further includes:
s93: determining a high-electricity-price time period washing step and a low-electricity-price time period washing step;
s94: reducing the energy consumption of a washing step in a high electricity price period, and increasing the energy consumption of the washing step in a low electricity price period so as to reduce the total electricity price of the total washing step, wherein the total electricity price is the sum of the product of the unit energy consumption electricity price of each stage and the energy consumption of the stage;
s95: and regenerating a new washing step, wherein the washing control module controls the washing module to wash according to the new washing step.
Preferably, after the S93 and before the S94, the method further comprises:
s931: a washing step of determining a high-electricity-rate period, and a cleaning energy consumption rate per washing step of the high-electricity-rate period, and
determining a washing step in a low-electricity-price period, and a cleaning energy consumption rate of each washing step in the low-electricity-price period;
the S94 includes:
the energy consumption of the washing step with low cleaning energy consumption rate in a high electricity price period is reduced, and the energy consumption of the washing step with high cleaning energy consumption rate in a low electricity price period is correspondingly improved, so that the total electricity price of the total washing step is reduced, and the total cleanliness is not reduced.
Preferably, after S93 and before S94, the method further comprises:
s931': judging whether the low electricity price period occurs before the high electricity price period during the washing step execution period, if so, executing S932'; if not, go to S94;
s932': reducing the execution time of the non-washing step in the low electricity price period, then re-determining the electricity price period in which each washing step is located, and then executing S933';
s933': the high-electricity-rate period washing step and the low-electricity-rate period washing step are determined, after which S94 is performed.
Preferably, the S932' further includes: the execution time of the washing step, which is low in cleanliness and takes a long time, is reduced during the low electricity price period, and then S933' is performed.
Preferably, the reducing of the execution time of the washing step in which the cleanliness is low but the time consumption is long in the low electricity price period includes:
calculating the ratio of the cleaning degree value of each washing step in the low electricity price period to the duration of the step as a cleaning rate, and determining the step of the minimum cleaning rate;
reducing the length of the step in which the cleaning rate is minimized.
Preferably, the washing step includes a soaking step, a heating step and a washing step.
Preferably, the non-washing step includes a water filling step and a water draining step.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a big data-based washing machine system according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a laundry control method of a big data based washing machine system according to a second embodiment of the present invention;
fig. 3 is a schematic diagram of a laundry control method of a big data based washing machine system according to a third embodiment of the present invention;
fig. 4 is a schematic diagram of a laundry control method of a washing machine system based on big data according to a fourth embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
The present invention will be described in detail below by way of examples.
The invention provides a washing machine system based on big data, which comprises a central processing module, a washing control module, a washing module, a positioning module and an access gateway, wherein the access gateway is accessed to the Internet through a wireless route, and further comprises a washing machine manufacturer cloud server connected with the washing control module through the Internet and an urban government affair platform server connected with the washing machine manufacturer cloud server; the central processing module is respectively connected with the washing control module, the positioning module and the access gateway; the washing control module is connected with the washing module and is used for controlling the washing module to carry out washing operation.
The present invention also provides a laundry control method of a big data based washing machine system, as shown in fig. 2, the method includes the steps of:
s1: the central processing module detects whether the washing machine is currently started for the first time or whether the positioning changing signal is received, and if so, S2 is executed.
The washing machine in the big data based washing machine system is provided with a positioning module, and the current position can be automatically positioned through the positioning module and a network. When the washing machine is started, the washing machine can detect whether the washing machine is started for the first time at present, if so, the washing machine is started for the first time after the washing machine is purchased at present, and the central processing module calls the positioning module to determine the geographical position of the current washing machine and determine the city information of the washing machine; specifically, the central processing unit of the washing machine may open a storage space in the memory space to perform a storage area for a first start flag, and clear the first start flag when leaving the factory, and when the washing machine is started, the central processing unit first checks whether the first start flag is 0, and if so, the central processing unit calls the positioning module to perform positioning to obtain the longitude and latitude of the current washing machine, and determines the administrative area where the current washing machine is located according to the longitude and latitude information. In addition, considering that the washing machine is moved to different urban areas after being used, at this time, the user can click the repositioning key on the control panel to send a repositioning signal to the central processing module, and the central processing module also calls the positioning module again to perform positioning after receiving the repositioning signal.
S2: the central processing module calls the positioning module to determine the geographical position of the current washing machine and determine the city information of the washing machine.
Specifically, the comparison table of the city information and the geographic position may be pre-stored in a cloud server of a washing machine manufacturer, the central processing module calls the positioning module to determine the geographic position information of the current washing machine, and then sends the geographic position information to the cloud server, and after receiving the geographic position information, the cloud server determines the city where the washing machine is located according to the comparison table of the city information and the geographic position.
S3: and according to the city information, the central processing module finds out the government affair platform server address of the corresponding city from the locally stored city government affair platform server addresses.
The central processing module locally stores the addresses of the government affair platform servers of all cities, and after the city is determined, the address of the government affair platform server of the corresponding city can be found from the locally stored addresses of the government affair platform servers of the cities.
S4: and the central processing module accesses the government affair platform server through the gateway.
S5: the central processing unit obtains the current time.
S6: and the central processing unit calls historical electricity utilization information of the user within a preset time range before and after the current moment from the government affair platform server according to the current moment.
The electricity utilization conditions of the users are regular, and the rules are stored in the government affair platform server in the form of historical electricity utilization information, wherein the historical electricity utilization information comprises the electricity consumption data of the current users in each time period.
Further, the government affair platform server also receives a washing machine manufacturer cloud server address stored in the central processing unit, retrieves historical electricity utilization information of a user within a preset time range before and after the current time, and sends the historical electricity utilization information to a manufacturer cloud server corresponding to the washing machine manufacturer cloud server address. And the manufacturer cloud server generates portrait data of the user according to the historical electricity utilization information, matches the portrait data of the user with consumption prediction data stored in the manufacturer cloud server, and determines the electricity consumption capacity of the current user.
S7: and the central processing unit calls a washing machine use record in a preset time range before and after the current time according to the current time, wherein the washing machine use record comprises the use time of the washing machine and the washing step.
For example, it is shown in the history that the electricity consumption of the user exceeds the average level of the local area after the current time of each day in the history, which indicates that the electricity consumption capacity of the user is strong, if the electricity consumption of the user intermittently changes after the current time, the change rule of the electricity consumption of the user is counted, the electricity consumption capacity of the user in different periods is determined, and finally, the electricity consumption capacity of the user after the current time can be counted, for example, the electricity consumption capacity of the user 30 minutes after the current time is strong, the electricity consumption capacity of the user 20 minutes after the current time is weak, and the electricity consumption capacity of the user 30 minutes after the current time is strong, and different washing steps are recommended and suggested to the user according to the electricity consumption capacities of the user in different periods.
S8: and the central processing unit counts the historical electricity utilization information and the use record of the washing machine within the preset duration range, determines the relation between the washing time and the electricity consumption, and calculates the average electricity consumption at the current washing time.
In step S7, the power consumption capacity of the user at different periods has been determined, after which the CPU counts the historical power consumption information and the usage record of the washing machine within the preset time period, determines the relationship between the washing time and the power consumption, and calculates the average power consumption at the current washing time, for example, the current time is 18:00, the information obtained in the usage record of the washing machine is that 18: 53900 2 18:05 is in the water inlet stage, the power consumption is 1 power consumption unit, 18:05 ~: 10 is in the water temperature heating stage, the power consumption is 10 power consumption units, 18:10 ~: 30 is in the washing stage, the power consumption is 30 power consumption units, 18:30 ~: 50 is in the rinsing stage, the power consumption is 20 power consumption units, 18:50 ~: 10 is in the spin drying stage, and the power consumption is 20 power consumption units.
S9: the central processing unit calls the washing control module to control the washing module to wash, predicts the electricity consumption of each washing step in real time in the washing process, and gives an alarm when the total predicted electricity consumption of a plurality of washing steps is larger than the average electricity consumption.
When the washing steps and the electricity consumption in the time period taking the current moment as the starting point in the historical record are mastered, the electricity consumption can be taken as a comparison standard, and when the total predicted electricity consumption is larger than the average electricity consumption, an alarm is given to remind a user of possible excessive use of electricity.
Further, as shown in fig. 3, the S9 includes:
s91: the washing control module receives a washing instruction input by a user, wherein the washing instruction comprises an execution sequence of washing steps and an execution time of each washing step.
The washing instructions input by the user include the execution sequence of the washing steps and the execution time of each washing step, and for example, the washing instructions input by the user are as follows: the water inlet step is performed for 3 minutes, the heating step is performed for 5 minutes, the washing step is performed for 30 minutes, the rinsing step is performed for 20 minutes, the spin-drying step is performed for 20 minutes, the drying step is performed for 20 minutes, and the ultraviolet ray disinfection is performed for 20 minutes.
S92: determining the electricity price time period of each washing step; and predicting the electricity consumption of each washing step according to the preset energy consumption of each washing step and the electricity price of the electricity price time period, and giving an alarm to a user if the total predicted electricity consumption is greater than the average electricity consumption.
After the central controller knows the electricity price time period of each washing step and the execution time of each washing step input by a user, the central processor can determine the electricity consumed by each washing step through an electricity price time formula, so that the electricity use condition in the whole washing process is estimated, an electricity-time relation curve graph is estimated and generated, the electricity consumption change trend in the washing process can be displayed on the whole time length by the relation curve graph, and then the central processor can compare the estimated and generated electricity-time relation curve graph with an electricity-time relation obtained from historical electricity consumption information, wherein the specific comparison method comprises the following steps: the method comprises the steps of cutting the 'electric quantity-time' relation curve graph into different curve segments according to a time sequence, determining each maximum value point of each curve segment according to each cut curve segment, then determining a moment value corresponding to each maximum value point, obtaining a plurality of points with transverse and longitudinal coordinates respectively being 'moment, maximum value', analyzing each 'moment, maximum value' point, recording the maximum value as an ultra-average maximum value when the maximum value of the current point is found to exceed the average electric quantity value of the time segment corresponding to the moment through analysis, and after all the maximum value points are traversed, if the obtained average value of all the ultra-average maximum values exceeds a preset threshold value, indicating that the electric quantity of the current time segment is dangerous when the average electric quantity value of the time segment exceeds the average electric quantity value of the time segment.
Further, as shown in fig. 4, after the S92, the method further includes:
s93: determining a high-electricity-price time period washing step and a low-electricity-price time period washing step;
the central processing unit obtains the electricity prices in different time periods from the government affair platform server, determines the high electricity price time period and the low electricity price time period, and determines the washing step in the high electricity price time period and the washing step in the low electricity price time period.
S94: reducing the energy consumption of a washing step in a high electricity price period, and increasing the energy consumption of the washing step in a low electricity price period so as to reduce the total electricity price of the total washing step, wherein the total electricity price is the sum of the product of the unit energy consumption electricity price of each stage and the energy consumption of the stage;
s95: and regenerating a new washing step, wherein the washing control module controls the washing module to wash according to the new washing step.
By adopting the mode, the power consumption can be reduced on the premise of ensuring the laundry quality.
Further, after the S93 and before the S94, the method further comprises:
s931: a washing step of determining a high-power-rate period, and a cleaning energy consumption rate per washing step of the high-power-rate period, and a washing step of determining a low-power-rate period, and a cleaning energy consumption rate per washing step of the low-power-rate period.
Here, the cleaning energy consumption rate is a ratio of the detergency of the laundry to the corresponding energy consumption, that is, an increased degree of cleanliness of the laundry per unit of consumed electric energy. The energy consumption rate of cleaning of each step in the washing step is different, such as the ultraviolet sterilization step, no matter how much electric energy is consumed in this step, the added cleanliness of the clothes is always 0, because the ultraviolet sterilization step cannot influence the cleanliness of the clothes, and similarly, the washing step, the rinsing step and the heating step consume different energy, which all influence the added cleanliness of the clothes, and generally we only know that the added cleanliness of the clothes is strongest in the washing step, but generally neglect the step, which is also the step consuming the most energy, and if only from the perspective of the energy consumption rate of cleaning, perhaps the energy consumption rate of cleaning of the washing step is not very high. According to the invention, a large number of experiments are carried out on various clothes and various combinations of dirt degrees by a washing machine manufacturer, so that the cleaning energy consumption rates of different washing steps under different dirt degrees of the clothes are obtained, and the cleaning energy consumption rates are stored in a cloud server of the washing machine manufacturer and are used by the washing machine.
Further, the S94 includes:
the energy consumption of the washing step with low cleaning energy consumption rate in a high electricity price period is reduced, and the energy consumption of the washing step with high cleaning energy consumption rate in a low electricity price period is correspondingly improved, so that the total electricity price of the total washing step is reduced, and the total cleanliness is not reduced.
Further, after the S93 and before the S94, the method further comprises:
s931': judging whether the low electricity price period occurs before the high electricity price period during the washing step execution period, if so, executing S932'; if not, go to S94;
s932': reducing the execution time of the non-washing step in the low electricity price period, then re-determining the electricity price period in which each washing step is located, and then executing S933';
s933': the high-electricity-rate period washing step and the low-electricity-rate period washing step are determined, after which S94 is performed.
Further, the S932' further includes: the execution time of the washing step, which is low in cleanliness and takes a long time, is reduced during the low electricity price period, and then S933' is performed.
Further, the reducing the execution time of the washing step having low cleanliness but long time consumption in the low electricity price period includes:
calculating the ratio of the cleaning degree value of each washing step in the low electricity price period to the duration of the step as a cleaning rate, and determining the step of the minimum cleaning rate;
reducing the length of the step in which the cleaning rate is minimized.
Further, the washing step includes a soaking step, a heating step, and a washing step.
Further, the non-washing step includes a water filling step and a water draining step.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. A washing control method of a washing machine system based on big data is used, the washing machine system comprises a central processing module, a washing control module, a washing module, a positioning module and an access gateway, the access gateway is accessed to the Internet through a wireless route, the washing machine system also comprises a washing machine manufacturer cloud server connected with the washing control module through the Internet, and an urban government affair platform server connected with the washing machine manufacturer cloud server; the central processing module is respectively connected with the washing control module, the positioning module and the access gateway; the washing control module is connected with the washing module and is used for controlling the washing module to carry out washing operation;
characterized in that the method comprises the steps of:
s1: the central processing module detects whether the washing machine is started for the first time or whether a positioning change signal is received, if so, S2 is executed;
s2: the central processing module calls the positioning module to determine the geographical position of the current washing machine and determine the city information of the washing machine;
s3: according to the city information, the central processing module finds out the government affair platform server address of the corresponding city from the locally stored city government affair platform server addresses;
s4: the central processing module accesses the government affair platform server through the gateway;
s5: the central processing unit obtains the current time;
s6: the central processing unit calls historical electricity utilization information of a user in a preset time range before and after the current time from the government affair platform server according to the current time;
s7: the central processing unit calls a washing machine use record in a preset time range before and after the current moment according to the current moment, wherein the washing machine use record comprises the use time of the washing machine and the washing step;
s8: the central processing unit counts the historical electricity utilization information and the use record of the washing machine within the preset duration range, determines the relation between the washing time and the electricity consumption, and calculates the average electricity consumption at the current washing time;
s9: the central processing unit calls the washing control module to control the washing module to wash, the electricity consumption of each washing step is predicted in real time in the washing process, and when the total predicted electricity consumption of the washing steps is larger than the average electricity consumption, an alarm is sent to a user.
2. A laundry control method according to claim 1, wherein the S9 includes:
s91: the washing control module receives a washing instruction input by a user, wherein the washing instruction comprises an execution sequence of washing steps and an execution time of each washing step;
s92: determining the electricity price time period of each washing step; and predicting the electricity consumption of each washing step according to the preset energy consumption of each washing step and the electricity price of the electricity price time period, and giving an alarm to a user if the total predicted electricity consumption is greater than the average electricity consumption.
3. A laundry control method according to claim 2, further comprising, after the S92:
s93: determining a high-electricity-price time period washing step and a low-electricity-price time period washing step;
s94: reducing the energy consumption of a washing step in a high electricity price period, and increasing the energy consumption of the washing step in a low electricity price period so as to reduce the total electricity price of the total washing step, wherein the total electricity price is the sum of the product of the unit energy consumption electricity price of each stage and the energy consumption of the stage;
s95: and regenerating a new washing step, wherein the washing control module controls the washing module to wash according to the new washing step.
4. A laundry control method according to claim 3, wherein after the S93 and before the S94, the method further comprises:
s931: a washing step of determining a high-electricity-rate period, and a cleaning energy consumption rate per washing step of the high-electricity-rate period, and
determining a washing step in a low-electricity-price period, and a cleaning energy consumption rate of each washing step in the low-electricity-price period;
the S94 includes:
the energy consumption of the washing step with low cleaning energy consumption rate in a high electricity price period is reduced, and the energy consumption of the washing step with high cleaning energy consumption rate in a low electricity price period is correspondingly improved, so that the total electricity price of the total washing step is reduced, and the total cleanliness is not reduced.
5. A laundry control method according to claim 3, wherein after S93 and before S94, the method further comprises:
s931': judging whether the low electricity price period occurs before the high electricity price period during the washing step execution period, if so, executing S932'; if not, go to S94;
s932': reducing the execution time of the non-washing step in the low electricity price period, then re-determining the electricity price period in which each washing step is located, and then executing S933';
s933': the high-electricity-rate period washing step and the low-electricity-rate period washing step are determined, after which S94 is performed.
6. A laundry control method according to claim 5, wherein the S932' further includes: the execution time of the washing step, which is low in cleanliness and takes a long time, is reduced during the low electricity price period, and then S933' is performed.
7. The laundry control method according to claim 6, wherein the reducing the execution time of the laundry step having low cleanliness but long time consumption in the low electricity price period comprises:
calculating the ratio of the cleaning degree value of each washing step in the low electricity price period to the duration of the step as a cleaning rate, and determining the step of the minimum cleaning rate;
reducing the length of the step in which the cleaning rate is minimized.
8. A laundry control method according to claim 1, wherein the washing step comprises a soaking step, a heating step and a washing step.
9. A laundry control method according to claim 5, wherein the non-laundry step includes a water injection step and a water drainage step.
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| CN111434827A (en) * | 2018-12-25 | 2020-07-21 | 珠海格力电器股份有限公司 | Washing method and device of washing machine |
| CN112095290B (en) * | 2019-05-28 | 2023-11-17 | 天津海尔洗涤电器有限公司 | Intelligent washing system |
| CN111676655A (en) * | 2020-05-26 | 2020-09-18 | 珠海格力电器股份有限公司 | Control method of washing equipment and washing equipment |
| CN114075743A (en) * | 2020-08-21 | 2022-02-22 | 无锡小天鹅电器有限公司 | Clothes processing device, control method, control device, server and storage medium |
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| CN1343806A (en) * | 2000-09-11 | 2002-04-10 | 东芝株式会社 | Clothes washing system |
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| CN1465765A (en) * | 2002-07-05 | 2004-01-07 | 乐金电子(天津)电器有限公司 | Long distance diagnosis system and method for washing machine |
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