A pulsator washing machine washing control method based on high-power variable frequency motor

Abstract

The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency motor and relates to the technical field of washing machine control. The application discloses a pulsator washing machine washing control method based on a high-power variable-frequency

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of washing machine control, in particular to a pulsator washing machine washing control method based on a high-power variable frequency motor. BACKGROUND

[0002] The high-power variable frequency pulsator washing machine mainly relies on a variable frequency motor to achieve precise control of the speed and torque by adjusting the motor frequency, and takes into account efficient washing and energy saving and noise reduction. The prior art with publication number CN117684351A discloses a control method and device for a pulsator washing machine and a pulsator washing machine. The method includes determining the target water level when the pulsator washing machine is washing clothes, then performing the water inlet operation, controlling the speed of the motor to rise to the maximum speed value corresponding to the state of no spraying water flow in the pulsator washing machine, and running according to the value. During this process, it is detected whether the pulsator washing machine has reached the critical state of no spraying water flow and spraying water flow, if so, it is detected whether the electrical parameters of the motor exceed the electrical parameter threshold, if so, the motor is controlled to continue running at the maximum speed value to perform the cleaning operation, if not, the motor is controlled to run faster, and then the cleaning operation is performed. The prior art solves the technical problems of uneven detergent dissolution, incomplete washing of clothes, water splashing, and overloading of the motor in the prior art, which leads to reduced service life of the washing machine and poor user experience.

[0003] However, although the high-power pulsator washing machine has stronger cleaning power and can maintain good cleaning effect on large clothes and more clothes, continuous high-power operation not only increases power consumption, but also may cause greater friction between clothes, increasing the wear of clothes. A smaller power may not be able to ensure good cleaning effect when large clothes or a large number of clothes are washed at the same time, so how to control the power consumption of the pulsator washing machine while ensuring the cleaning effect and wear degree of the clothes is a problem to be solved. SUMMARY

[0004] The purpose of the present application is to provide a pulsator washing machine washing control method based on a high-power variable frequency motor to solve the above-mentioned deficiencies in the prior art.

[0005] In order to achieve the above-mentioned purpose, the present application provides the following technical solution: a pulsator washing machine washing control method based on a high-power variable frequency motor, comprising the following steps:

[0006] S1, according to the type of clothes to be washed, a plurality of sets of control parameters are set, and a plurality of washing schemes are generated, each of the type of clothes to be washed corresponding to the proportion of each material of clothes contained in the clothes to be washed; the control parameters are obtained by testing the motor frequency, motor speed, impeller speed and direction conversion period of the high-power variable frequency motor and the impeller when the impeller rotates to generate various water flow patterns; wherein the type of clothes to be washed is the proportion of all materials of clothes that need to be washed at the same time by the impeller washing machine, further, the type of clothes to be washed can be clothes of a single material, i.e. the proportion of clothes of a certain material is 1, or it can be a mixture of clothes of multiple materials, i.e. the clothes to be washed at the same time by the impeller washing machine contain clothes of multiple materials; further, the proportion of each material of clothes for the type of clothes to be washed can be set by obtaining the proportion of clothes materials that people often mix and wash together in each season.

[0007] S2, obtaining the scheme optimal control parameter data, the scheme optimal water turbidity change rate data, and the scheme water turbidity change rate data of the clothes type when the scheme is used to wash the clothes type of the remaining washing schemes for each washing scheme;

[0008] S3, calculating and processing the error and the variance of the error of the scheme water turbidity change rate data of the clothes type when the scheme is used to wash the clothes type and the scheme optimal water turbidity change rate data for each washing scheme, respectively generating the scheme error data of the clothes type and the scheme error variance data of the clothes type;

[0009] S4, selecting the washing scheme with the smallest clothes type washing error variance data as the initial washing scheme to wash the clothes to be washed, and obtaining the water turbidity change rate data of the clothes to be washed;

[0010] S5, calculating the error of the water turbidity change rate data of the clothes to be washed and the scheme optimal water turbidity change rate data of the current washing scheme, and generating real-time error data;

[0011] S6, if the real-time error data is less than the set error threshold, it is determined that the current washing scheme is used; otherwise, based on the error characteristics corresponding to the real-time error data and the error characteristics corresponding to the scheme error data of the clothes type corresponding to the initial washing scheme, the washing scheme search processing of the error characteristics corresponding to the clothes type is performed, the washing scheme adjustment data is generated, and the process returns to S5.

[0012] Further, according to the set plurality of types of clothes to be washed, the water turbidity change rate data and the clothes wear degree data of different control parameters in each washing stage are tested, and the preliminary control parameters that make the water turbidity change rate data fastest and the clothes wear degree smallest in each washing stage during the test process of each type of clothes to be washed are obtained.

[0013] Further, the scheme optimal control parameter data is obtained by the following steps:

[0014] For each washing scheme, the washing machine is controlled to wash clothes of the corresponding washing clothes type according to the corresponding control parameter;

[0015] Based on the optical sensor or the turbidity sensor, water quality turbidity change data in the washing machine barrel over time is obtained, and the water quality turbidity change data is first-order and second-order differentiated to calculate water quality turbidity change speed data over time and water quality turbidity change acceleration data over time respectively; the corresponding clothes wear data is obtained by collecting fiber debris (weighing / counting) in the washing liquid, measuring weight loss / color change using a standard wear cloth block, and obtaining washing machine power change data over time by a power meter, and calculating and analyzing the energy consumption data when the washing clothes turbidity meets the washing completion turbidity threshold to generate scheme water quality turbidity change rate data, scheme clothes wear data, and scheme energy consumption data;

[0016] Based on the optical sensor or the turbidity sensor, water quality turbidity change data in the washing machine barrel over time is obtained, and the water quality turbidity change data is first-order and second-order differentiated to calculate water quality turbidity change speed data over time and water quality turbidity change acceleration data over time respectively; the corresponding clothes wear data is obtained by collecting fiber debris (weighing / counting) in the washing liquid, measuring weight loss / color change using a standard wear cloth block, and obtaining washing machine power change data over time by a power meter, and calculating and analyzing the energy consumption data when the washing clothes turbidity meets the washing completion turbidity threshold to generate scheme water quality turbidity change rate data, scheme clothes wear data, and scheme energy consumption data;

[0017] Based on the scheme water quality turbidity change rate data, the scheme clothes wear data, and the scheme energy consumption data of each washing scheme, a target function is constructed, which simultaneously satisfies the maximum scheme water quality turbidity change rate data, the minimum scheme clothes wear data, and the minimum scheme energy consumption data, and a constraint condition is solved to obtain the control parameter corresponding to each washing clothes type, and the scheme optimal control parameter data of each washing scheme is generated. The constraint condition includes a control parameter constraint condition, such as a variable frequency motor speed in a set speed interval, a direction conversion period in a set conversion period interval, etc.; a final water quality turbidity in a set turbidity interval, a water quality turbidity change rate (speed, acceleration) in a set change rate (speed, acceleration) interval, a clothes wear degree in a set wear degree interval, a scheme energy consumption in a set energy consumption interval, and a washing time in a set washing time interval, etc.

[0018] Further, the scheme optimal water quality turbidity change rate data is obtained by the following steps:

[0019] For each washing scheme, the washing machine is controlled to wash clothes of the corresponding washing clothes type according to the corresponding scheme optimal control parameter data;

[0020] The corresponding water quality turbidity change rate data is obtained to generate the corresponding scheme optimal water quality turbidity change rate data.

[0021] Further, the scheme obtains the water quality turbidity change rate data of the clothes type by the following steps:

[0022] The drum washing machine controls the clothes of the clothes type according to the optimal control parameter data of the corresponding scheme for each washing scheme control, and washes the clothes.

[0023] The water quality turbidity change rate data of the clothes type of each washing scheme is obtained, and the corresponding scheme clothes type washing water quality turbidity change rate data is generated.

[0024] Further, the S3 includes the following steps:

[0025] S3.1, the first derivative and the second derivative of the scheme clothes type washing water quality turbidity change rate data and the scheme optimal water quality turbidity change rate data of each washing scheme are carried out respectively, the scheme clothes type washing water quality turbidity change speed characteristic, the scheme clothes type washing water quality turbidity change acceleration characteristic, the scheme optimal water quality turbidity change speed characteristic and the scheme optimal water quality turbidity change acceleration characteristic are obtained, the scheme clothes type washing water quality turbidity characteristic vector and the scheme optimal water quality turbidity characteristic vector are generated, that is, the scheme clothes type washing water quality turbidity characteristic vector=(scheme clothes type washing water quality turbidity change speed characteristic, scheme clothes type washing water quality turbidity change acceleration characteristic), the scheme optimal water quality turbidity characteristic vector=(scheme optimal water quality turbidity change speed characteristic, scheme optimal water quality turbidity change acceleration characteristic);

[0026] S3.2, the error vector of the scheme clothes type washing water quality turbidity characteristic vector and the scheme optimal water quality turbidity characteristic vector of all the scheme clothes type washing water quality turbidity characteristic vectors of the washing scheme is calculated, and the scheme clothes type washing error vector is generated;

[0027] S3.3, the error norm calculation processing is carried out on the error vector of each scheme clothes type washing, and the error data of the scheme clothes type washing is generated;

[0028] S3.4, the error variance calculation processing is carried out on the error data of the scheme clothes type washing based on all the scheme clothes type washing error data of the same washing scheme, and the error variance data of the scheme clothes type washing is generated.

[0029] Further, the S4 includes the following steps:

[0030] S4.1, the error variance data of the scheme clothes type washing of all the washing schemes is compared, and the minimum error variance data of the scheme clothes type washing is obtained;

[0031] S4.2, set the cleaning program corresponding to the minimum program-to-clothes type cleaning error variance data as the initial cleaning program; wherein the initial cleaning program is a cleaning program that the pulsator washing machine executes by default when performing cleaning.

[0032] In one embodiment, the user can also autonomously select a cleaning program before the pulsator washing machine starts cleaning, so that the pulsator washing machine performs cleaning according to the autonomously selected cleaning program. When cleaning according to the autonomously selected cleaning program, steps S5-S6 are no longer executed, but the water quality turbidity change data over time and the water quality turbidity change rate data of the clothes to be cleaned are obtained according to the optimal control parameter data of the autonomously selected initial cleaning program, and it is judged whether the cleaning capacity is excessive or insufficient by comparing the water quality turbidity change rate data of the clothes to be cleaned with the set turbidity change rate threshold value. If it is excessive, the frequency control speed of the variable frequency motor is reduced, and if it is insufficient, the frequency of the variable frequency motor is increased to increase the speed. The current water quality turbidity is obtained through the water quality turbidity change data over time, and the current water quality turbidity is compared with the set cleaning completion turbidity threshold value to judge whether the clothes are clean, so as to dynamically extend or reduce the cleaning time. Finally, the cleaning time needs to meet the constraint condition, i.e. within the set cleaning time interval.

[0033] S4.3, the pulsator washing machine performs cleaning for a set test duration according to the optimal control parameter data of the initial cleaning program, and obtains water quality turbidity change rate data of the clothes to be cleaned. The clothes to be cleaned are one or more clothes that the user actually wants to clean using the pulsator washing machine.

[0034] Further, the S5 includes the following steps:

[0035] S5.1, obtain program optimal water quality turbidity change rate data of the current cleaning program;

[0036] S5.2, calculate the error between the water quality turbidity change rate data of the clothes to be cleaned and the program optimal water quality turbidity change rate data of the current cleaning program, and generate real-time error data.

[0037] Further, the S6 includes the following steps:

[0038] S6.1, judge whether the real-time error data is less than the set error threshold value, if yes, set the current cleaning program as the final cleaning program;

[0039] S6.2, if not, collect all program-to-clothes type cleaning error vectors of all cleaning programs, and generate a program-to-clothes type cleaning error vector set;

[0040] S6.3、based on the water turbidity change rate data of the clothes to be washed and the scheme optimal water turbidity change rate data of the current washing scheme, the error vector of the current washing scheme for washing the clothes to be washed is calculated, the real-time washing error vector is generated, and the calculation principle is referred to S3.1-S3.2;

[0041] S6.4、based on the nearest neighbor algorithm, searching for the scheme clothes type washing error vector most similar to the real-time washing error vector in the scheme clothes type washing error vector set, and outputting the corresponding washing scheme to generate washing scheme adjustment data;

[0042] S6.5、the impeller washing machine sets the test duration of the clothes to be washed according to the optimal control parameter data of the washing scheme adjustment data, acquires and updates the water turbidity change rate data of the clothes to be washed, and returns to S5.

[0043] 1、Compared with the prior art, the washing control method of the impeller washing machine based on the high-power variable frequency motor provided by the application can analyze the control parameters of the impeller washing machine with the best washing effect, the lowest fabric wear degree and the lowest energy consumption when washing clothes with different washing scheme and corresponding fabric material mixing ratio, so as to balance the fabric wear degree and energy consumption while ensuring the washing effect of the clothes.

[0044] 2、Compared with the prior art, the washing control method of the impeller washing machine based on the high-power variable frequency motor provided by the application can collect the mixing ratio of each fabric material mixed together during washing, and set the washing scheme one by one, so as to ensure that the mixing ratio of the clothes to be washed has a corresponding washing scheme to control the fabric wear degree and energy consumption while ensuring the washing effect.

[0045] 3、Compared with the prior art, the washing control method of the impeller washing machine based on the high-power variable frequency motor provided by the application can extract the error characteristics of the water turbidity change rate of the current washing scheme for washing the clothes to be washed and the scheme optimal water turbidity change rate of the current washing scheme, and the error characteristics of the water turbidity change rate of the clothes of other washing scheme corresponding to the washing clothes type washed by the current washing scheme and the scheme optimal water turbidity change rate of the current washing scheme, and match the error characteristics, analyze the most matched washing clothes type of the clothes to be washed, so as to determine the most matched washing scheme, achieve the effect of self-adaptive matching of the washing scheme to the clothes to be washed, and cooperate with the high-power variable frequency motor to ensure that the impeller washing machine can reach the control parameters corresponding to the best washing scheme when washing a large amount of mixed clothes and large clothes, and ensure the washing power of the clothes. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below only show some embodiments of the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0047] Figure 1 The method step diagram provided for the embodiments of the present application;

[0048] Figure 2 The S3 step diagram provided for the embodiments of the present application;

[0049] Figure 3 The S4 step diagram provided for the embodiments of the present application;

[0050] Figure 4 The S5-S6 step diagram provided for the embodiments of the present application. DETAILED DESCRIPTION

[0051] In order to make those skilled in the art better understand the technical solutions of the present application, the present application will be further described in detail below with reference to the drawings.

[0052] In the following, example embodiments will be described more fully with reference to the accompanying drawings, in which example embodiments can be embodied in different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0053] In the case of no conflict, each embodiment of the present disclosure and each feature in the embodiments can be combined with each other.

[0054] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0055] The terms used herein are only used to describe specific embodiments, and are not intended to limit the present disclosure. As used herein, the singular forms "a" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprise" and / or "consist of" are used in the specification, the specified features, integers, steps, operations, elements, and / or components are present, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0056] Embodiments described herein can be described with reference to plan views and / or cross-sectional views by virtue of the fact that the disclosed embodiments can be idealized to facilitate description. Accordingly, example illustrations can be modified according to manufacturing techniques and / or tolerances. Therefore, embodiments are not limited to the illustrated examples and include modifications based on manufacturing processes. Thus, the illustrated zones in the drawings have schematic properties and the illustrated shapes of the zones shown in the drawings do not intend to be limiting, but rather illustrate specific shapes of zones of elements.

[0057] Referring to Figure 1 A washing control method of a pulsator washing machine based on a high-power variable frequency motor, comprising the following steps:

[0058] S1, according to the type of clothes to be washed, set multiple groups of control parameters to generate multiple washing schemes, each type of clothes to be washed corresponds to the proportion of each material of the clothes to be washed.

[0059] Among them, the type of clothes to be washed is the proportion of all materials of clothes to be washed by the pulsator washing machine at the same time, further, the type of clothes to be washed can be a single material of clothes, that is, the proportion of a certain material of clothes is 1, or it can be a mixture of multiple materials of clothes, that is, the clothes to be washed by the pulsator washing machine contain multiple materials of clothes; further, the proportion of each material of clothes of the type of clothes to be washed can be set by obtaining the proportion of the material of clothes commonly washed together in each season.

[0060] The control parameters are obtained by testing the motor frequency, motor speed, pulsator speed, and rotation direction conversion period of the high-power variable frequency motor and the pulsator when the pulsator rotates to generate various water flow patterns.

[0061] In one embodiment, when setting the control parameters of different washing schemes, the Navier-Stokes equation can be referred to:

[0062]

[0063] ρ is the density of water, v is the water flow velocity vector, p is the water pressure, μ is the dynamic viscosity of water, and f is the driving force of the pulsator;

[0064] By controlling the frequency of the high-power variable frequency motor to control the rotational acceleration, angular velocity and steering sequence of the pulsator, the spatio-temporal distribution of f is adjusted, so that different water flow patterns can be generated: strong turbulence: high angular velocity, high Reynolds number, which can be used to peel off stains; laminar flow: low angular velocity, low Reynolds number, which can be used to reduce the entanglement of clothes.

[0065] For example, the motor frequency can be set to 70-100 Hz, the motor speed to 420-600 RPM, the impeller angular velocity to 44.0-62.8 rad / s, and the forward-reverse switching period to 0.5 s to generate a high-frequency water hammer effect, impact the deep part of the fiber, and improve the cleaning effect on the clothes, especially for oil stains.

[0066] The motor frequency can be set to 50-70 Hz, the motor speed to 300-420 RPM, the impeller angular velocity to 9.4-18.8 rad / s, and the forward-reverse switching period to 1-1.5 s to form a large range of reciprocating water flow, which is suitable for high-intensity detergent dissolution and removal of common stains, and is suitable for general dirty fabrics such as cotton bedding and towels.

[0067] The motor frequency can be set to 15-30 Hz, the motor speed to 90-180 RPM, the impeller angular velocity to 31.4-44.0 rad / s, the one-way duration to 1-2 s, and the rotation stop ratio to 1:1.2-2 to simulate the effect of hand washing, which can balance cleaning and wear;

[0068] The impeller is driven to rotate at different angular velocities and rotation sequences by a high-power variable frequency motor, which can ensure sufficient angular velocity of the impeller when there are many clothes and the weight is large, provide strong turbulent flow and water hammer effect, and ensure the cleaning effect of large and large clothes. Then, according to the set multiple cleaning clothes types, the water turbidity change rate data and the clothes wear degree data of different control parameters in each cleaning stage are tested, and the preliminary control parameters that make the water turbidity change rate data fastest and the clothes wear degree smallest in each cleaning stage during the test process of each cleaning clothes type are obtained. The control parameters used in each cleaning stage correspond to the water flow pattern, which can ensure good cleaning effect and low wear rate when cleaning clothes of the corresponding type, so as to analyze the optimal control parameter data of each cleaning scheme on the basis of the preliminary control parameters, reduce the analysis amount and difficulty during analysis.

[0069] S2, obtaining the optimal control parameter data of each cleaning scheme, the optimal water turbidity change rate data, and the clothes type cleaning water turbidity change rate data of the scheme when cleaning clothes of other cleaning schemes.

[0070] Further, the optimal control parameter data is obtained by the following steps:

[0071] A1, for each cleaning scheme, the impeller washing machine is controlled according to the corresponding control parameters to clean the clothes of the corresponding cleaning clothes type.

[0072] A2, based on optical sensors or turbidity sensors, obtain the water quality turbidity change data in the drum of the pulsator washing machine over time, and first and second derivatives of the water quality turbidity change data are taken to calculate the water quality turbidity change speed data and the water quality turbidity change acceleration data over time, respectively; the corresponding clothes wear data is obtained by collecting the fiber scraps in the washing liquid (weighing / counting), measuring the weight loss / color change using standard abrasive cloth blocks, etc., and the pulsator washing machine power change data over time is obtained by directly reading the electric energy meter or by a power meter, and the energy consumption data when the cleaning clothes turbidity meets the cleaning completion turbidity threshold is obtained through calculation and analysis, to generate the scheme water quality turbidity change rate data, the scheme clothes wear data and the scheme energy consumption data;

[0073] Wherein, the detection of water quality turbidity in the drum of the pulsator washing machine based on optical sensors or turbidity sensors is a known common sense in the prior art, and is directly applied without change, so no specific description is made in this technical solution, and it will not cause any trouble in this technical field.

[0074] A3, based on the scheme water quality turbidity change rate data, the scheme clothes wear data and the scheme energy consumption data of each cleaning scheme, a target function is constructed, which simultaneously satisfies the maximum scheme water quality turbidity change rate data, the minimum scheme clothes wear data and the minimum scheme energy consumption data, and the control parameters corresponding to each cleaning clothes type are solved under the constraint conditions to generate the scheme optimal control parameter data of each cleaning scheme;

[0075] Wherein, the constraint conditions include control parameter constraint conditions, such as the speed of the variable frequency motor in the set speed range, the direction conversion period in the set conversion period range, etc.; the final water quality turbidity in the set turbidity range, the water quality turbidity change rate (speed, acceleration) in the set change rate (speed, acceleration) range, the clothes wear degree in the set wear degree range, the scheme energy consumption in the set energy consumption range, the cleaning time in the set cleaning time range, etc.

[0076] Further, the scheme optimal control parameter data of each cleaning scheme can be obtained by adjusting the parameters based on the preliminary control parameters.

[0077] Further, the scheme optimal water quality turbidity change rate data is obtained by the following steps:

[0078] B1, for each cleaning scheme, the pulsator washing machine is controlled according to the corresponding scheme optimal control parameter data to clean the clothes of the corresponding clothes type;

[0079] B2, the corresponding water quality turbidity change rate data is obtained to generate the corresponding scheme optimal water quality turbidity change rate data.

[0080] Furthermore, the solution obtains data on the rate of change in turbidity of water used for washing different types of clothing through the following steps:

[0081] C1. For each cleaning program, the pulsator washing machine is controlled to clean the types of clothes to be cleaned by other cleaning programs according to the optimal control parameter data of the corresponding program.

[0082] C2. Obtain the water turbidity change rate data for each type of clothing under each cleaning scheme, and generate the corresponding water turbidity change rate data for each type of clothing under each scheme.

[0083] S3. For each cleaning scheme, calculate and process the error and variance of the turbidity change rate data of the water quality for each type of clothing and the optimal turbidity change rate data of the scheme, and generate the scheme-specific cleaning error data and scheme-specific cleaning error variance data for each type of clothing, including the following steps:

[0084] S3.1. For each cleaning scheme, the first and second derivatives of the turbidity change rate data of the water quality for the clothing type and the optimal turbidity change rate data of the scheme are respectively obtained to obtain the turbidity change rate feature, the turbidity change acceleration feature, the optimal turbidity change rate feature, and the optimal turbidity change acceleration feature of the water quality for the clothing type. This generates the turbidity feature vector for the clothing type and the optimal turbidity feature vector, i.e., the turbidity feature vector for the clothing type = (turbidity change rate feature, turbidity change acceleration feature), and the optimal turbidity feature vector = (optimal turbidity change rate feature, optimal turbidity change acceleration feature).

[0085] S3.2 Calculate the error vector between the turbidity feature vector of the water quality for all the cleaning schemes of this cleaning scheme and the optimal water quality turbidity feature vector of the scheme, and generate the error vector of the scheme for the cleaning of clothing type.

[0086] S3.3 Calculate the error norm of the cleaning error vector for each clothing type for each scheme to generate cleaning error data for each clothing type.

[0087] S3.4. Based on the same cleaning plan, calculate the error variance of the clothing type cleaning error data for all plans and generate the clothing type cleaning error variance data for the plan.

[0088] S4. Select the cleaning scheme with the smallest variance in cleaning error data for the corresponding type of clothing as the initial cleaning scheme, and clean the clothing to be cleaned. Obtain the turbidity change rate data of the water quality of the clothing to be cleaned, including the following steps:

[0089] S4.1, compare the cleaning error variance data of all program-to-clothing types for all cleaning programs, and obtain the minimum program-to-clothing type cleaning error variance data;

[0090] S4.2, set the cleaning program corresponding to the minimum program-to-clothing type cleaning error variance data as the initial cleaning program; wherein the initial cleaning program is a cleaning program that the drum washing machine executes by default when performing cleaning.

[0091] In one embodiment, the user can also independently select a cleaning program before the drum washing machine starts cleaning, so that the drum washing machine performs cleaning according to the independently selected cleaning program. When cleaning according to the independently selected cleaning program, steps S5-S6 are no longer executed, but the water turbidity change data over time and the water turbidity change rate data of the clothes to be cleaned are obtained according to the optimal control parameter data of the initial independently selected cleaning program, the cleaning capacity is judged by comparing the water turbidity change rate data of the clothes to be cleaned with the set turbidity change rate threshold value, and the frequency control speed of the variable frequency motor is reduced if the cleaning capacity is excessive, or the frequency of the variable frequency motor is increased if the cleaning capacity is insufficient; the current water turbidity is obtained through the water turbidity change data over time, and the current water turbidity is compared with the set cleaning completion turbidity threshold value to judge whether the clothes are clean, so as to dynamically extend or reduce the cleaning time, and finally the cleaning time needs to meet the constraint condition, i.e. within the set cleaning time interval.

[0092] S4.3, the drum washing machine performs cleaning for a set test duration according to the optimal control parameter data of the initial cleaning program, and obtains the water turbidity change rate data of the clothes to be cleaned. The clothes to be cleaned are one or more clothes that the user actually wants to clean using the drum washing machine.

[0093] S5, calculate the error of the water turbidity change rate data of the clothes to be cleaned and the program optimal water turbidity change rate data of the current cleaning program, generate real-time error data, including the following steps:

[0094] S5.1, obtain the program optimal water turbidity change rate data of the current cleaning program;

[0095] S5.2, calculate the error of the water turbidity change rate data of the clothes to be cleaned and the program optimal water turbidity change rate data of the current cleaning program, and generate real-time error data.

[0096] S6, if the real-time error data is less than the set error threshold, it is determined that the current cleaning scheme is used; otherwise, based on the error characteristics corresponding to the real-time error data and the error characteristics of the clothes type cleaning error data corresponding to the initial cleaning scheme, the cleaning scheme search processing of the clothes type corresponding to the error characteristics corresponding to the real-time error data is performed, and the cleaning scheme adjustment data is generated, and S5 is returned, including the following steps:

[0097] S6.1, it is judged whether the real-time error data is less than the set error threshold, if yes, the current cleaning scheme is set as the final cleaning scheme;

[0098] S6.2, if not, all scheme-clothes type cleaning error vectors of all cleaning schemes are collected to generate a scheme-clothes type cleaning error vector set;

[0099] S6.3, based on the water turbidity change rate data of the clothes to be cleaned and the scheme optimal water turbidity change rate data of the current cleaning scheme, the error vector of the current cleaning scheme for cleaning the clothes to be cleaned is calculated, and the real-time cleaning error vector is generated, and the calculation principle is referred to S3.1-S3.2;

[0100] S6.4, based on the nearest neighbor algorithm, the scheme-clothes type cleaning error vector most similar to the real-time cleaning error vector is searched in the scheme-clothes type cleaning error vector set, and the corresponding cleaning scheme is output to generate cleaning scheme adjustment data;

[0101] S6.5, the pulsator washing machine sets the best control parameter data of the cleaning scheme adjustment data to the clothes to be cleaned for a test cleaning of a set time, acquires and updates the water turbidity change rate data of the clothes to be cleaned, and returns to S5.

[0102] Through this step, the error characteristics of the water turbidity change rate of the current cleaning scheme for cleaning the clothes to be cleaned and the scheme optimal water turbidity change rate of the current cleaning scheme, and the error characteristics of the water turbidity change rate of the clothes of other cleaning schemes corresponding to the current cleaning scheme for cleaning the clothes to be cleaned and the scheme optimal water turbidity change rate of the current cleaning scheme are extracted, and the error characteristics are matched, and the most matched cleaning clothes type of the clothes to be cleaned is analyzed.

[0103] The above only describes some exemplary embodiments of the application in a descriptive manner, and it is needless to say that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the application. Therefore, the above figures and description are illustrative in nature and should not be understood as limiting the scope of protection of the claims of the application.

Claims

1. A washing control method for a pulsator washing machine based on a high-power variable frequency motor, characterized in that, Includes the following steps: S1. Based on the type of clothing to be cleaned, set multiple sets of control parameters to generate multiple cleaning plans. Each type of clothing to be cleaned corresponds to the proportion of each material in the clothing to be cleaned. The control parameters are obtained by testing the motor frequency, motor speed, impeller speed, and rotation direction conversion cycle of the high-power variable frequency motor and impeller when the impeller rotates to generate various water flow patterns. S2. Obtain the optimal control parameter data, the optimal water turbidity change rate data, and the water turbidity change rate data for each cleaning scheme when cleaning the other cleaning schemes for different types of clothing. S3. Calculate and process the error and variance of the turbidity change rate data of the water quality for each cleaning scheme and the optimal turbidity change rate data of the scheme, and generate the scheme-to-clothes-type cleaning error data and the scheme-to-clothes-type cleaning error variance data respectively. S4. Select the cleaning scheme with the smallest cleaning error variance data for the corresponding type of clothing as the initial cleaning scheme to clean the clothing to be cleaned, and obtain the turbidity change rate data of the clothing to be cleaned. S5. Calculate the error between the turbidity change rate data of the water quality of the clothes to be cleaned and the optimal turbidity change rate data of the current cleaning scheme, and generate real-time error data. S6. If the real-time error data is less than the set error threshold, then the current cleaning solution will be used. Otherwise, based on the error characteristics corresponding to the real-time error data and the scheme corresponding to the initial cleaning scheme, the cleaning scheme search processing corresponding to the error characteristics of the clothing type cleaning error data is performed to generate cleaning scheme adjustment data and return to S5. The method also includes: based on the various types of clothes to be washed, testing the water turbidity change rate data and clothing abrasion data of different control parameters at each washing stage, and obtaining the preliminary control parameters that make the water turbidity change rate data the fastest and the clothing abrasion the least during each washing stage of each type of clothes to be washed. The optimal control parameter data for the proposed scheme are obtained through the following steps: For each cleaning program, the pulsator washing machine is controlled to clean the corresponding type of clothing according to the corresponding control parameters; Acquire data on the change of water turbidity in the drum of a pulsator washing machine over time, corresponding data on the wear and tear of clothes, and energy consumption data when the turbidity of the washed clothes meets the turbidity threshold for completion of washing. Generate data on the rate of change of water turbidity, data on the wear and tear of clothes, and data on the energy consumption of the solution, respectively. Based on the water turbidity change rate data, clothing wear data, and energy consumption data of each cleaning scheme, an objective function is constructed that simultaneously maximizes the water turbidity change rate data, minimizes the clothing wear data, and minimizes the energy consumption data. Constraints are then applied to solve for the control parameters corresponding to each type of clothing to be cleaned, generating the optimal control parameter data for each cleaning scheme.

2. The washing control method for a pulsator washing machine based on a high-power variable frequency motor according to claim 1, characterized in that, The optimal water turbidity change rate data for the proposed scheme is obtained through the following steps: For each cleaning program, the pulsator washing machine is controlled to clean the corresponding type of clothing according to the optimal control parameter data of the corresponding program; Obtain the corresponding water turbidity change rate data and generate the optimal water turbidity change rate data for the corresponding scheme.

3. The washing control method for a pulsator washing machine based on a high-power variable frequency motor according to claim 1, characterized in that: The proposed method obtains data on the rate of change in turbidity of water used for washing different types of clothing through the following steps: For each cleaning program, the pulsator washing machine is controlled to clean the same type of clothing as other cleaning programs based on the optimal control parameters for that program. Obtain the water turbidity change rate data for each type of clothing under each cleaning scheme, and generate the corresponding water turbidity change rate data for each type of clothing under each scheme.

4. The washing control method for a pulsator washing machine based on a high-power variable frequency motor according to claim 1, characterized in that, S3 includes the following steps: S3.1 For each cleaning scheme, the first and second derivatives of the turbidity change rate data of the water quality for the type of clothing and the optimal turbidity change rate data of the scheme are respectively obtained to obtain the turbidity change rate feature of the water quality for the type of clothing, the turbidity change acceleration feature of the water quality for the type of clothing, the optimal turbidity change rate feature of the scheme, and the optimal turbidity change acceleration feature of the scheme. The turbidity feature vector of the water quality for the type of clothing and the optimal turbidity feature vector of the scheme are generated. S3.2 Calculate the error vector between the turbidity feature vector of the water quality for all the cleaning schemes of this cleaning scheme and the optimal water quality turbidity feature vector of the scheme, and generate the error vector of the scheme for the cleaning of clothing type. S3.3 Calculate the error norm of the cleaning error vector for each clothing type for each scheme to generate cleaning error data for each clothing type. S3.

4. Based on the same cleaning plan, calculate the error variance of the clothing type cleaning error data for all plans and generate the clothing type cleaning error variance data for the plan.

5. A washing control method for a pulsator washing machine based on a high-power variable frequency motor according to claim 1, characterized in that, S4 includes the following steps: S4.1 Compare the variance data of the cleaning error for all clothing types for all cleaning schemes, and obtain the scheme with the smallest variance data of the cleaning error for clothing types. S4.2 Set the cleaning scheme corresponding to the smallest variance data of the cleaning error for each type of clothing as the initial cleaning scheme; S4.3 The pulsator washing machine performs a test wash on the clothes to be washed based on the optimal control parameter data of the initial washing program, and obtains the turbidity change rate data of the water quality of the clothes to be washed.

6. The washing control method for a pulsator washing machine based on a high-power variable frequency motor according to claim 4, characterized in that, S5 includes the following steps: S5.1 Obtain the optimal water turbidity change rate data for the current cleaning scheme; S5.2 Calculate the error between the turbidity change rate data of the water quality of the clothes to be washed and the optimal turbidity change rate data of the current washing scheme, and generate real-time error data.

7. A washing control method for a pulsator washing machine based on a high-power variable frequency motor according to claim 4, characterized in that, S6 includes the following steps: S6.1 Determine whether the real-time error data is less than the set error threshold. If so, set the current cleaning scheme as the final cleaning scheme. S6.2 If not, then collect the cleaning error vectors of all cleaning schemes for all clothing types and generate a set of cleaning error vectors of all schemes for clothing types. S6.3 Based on the turbidity change rate data of the water quality of the clothes to be cleaned and the optimal turbidity change rate data of the current cleaning scheme, calculate the error vector of the current cleaning scheme for cleaning the clothes to be cleaned, and generate a real-time cleaning error vector. S6.4 Based on the nearest neighbor algorithm, search for the cleaning error vector of the clothing type that is most similar to the real-time cleaning error vector in the set of cleaning error vectors of the clothing type, and output the corresponding cleaning scheme to generate cleaning scheme adjustment data. S6.5 The pulsator washing machine adjusts the optimal control parameter data of the cleaning scheme to perform a set test duration cleaning of the clothes to be cleaned, obtains and updates the turbidity change rate data of the water quality of the clothes to be cleaned, and returns to S5.

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