Electric fan and control method, device, storage medium and program product thereof

Abstract

The application discloses a control method and device of an electric fan, the electric fan, a storage medium and a computer program product, and relates to the technical field of electric fan control. The method comprises the following steps: performing data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and a human body temperature and a wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; the current human body temperature and the current wind speed of the electric fan are brought into the relationship between the comfort parameter and the human body temperature and the wind speed of the electric fan, and a current comfort parameter is calculated; and the wind speed of the electric fan is controlled according to the size of the current comfort parameter. According to the scheme, the comfort parameter is calculated by combining the human body temperature and the wind speed of the electric fan, and the wind speed of the electric fan is controlled according to the comfort parameter, so that the user is always in a comfortable state, and the use experience is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of electric fans, and particularly relates to a control method and device of an electric fan, the electric fan, a storage medium and a computer program product, in particular to a control method and device of an electric fan changing the wind speed of the electric fan according to the human body temperature, the electric fan, a storage medium and a computer program product. BACKGROUND

[0002] For the automatic adjustment of the wind speed of the electric fan, the related scheme is to adjust the rotating speed of the electric fan according to the size of the environmental temperature. However, when a person enters a relatively cold environment where the electric fan is located from a hot environment, the body surface temperature of the person is relatively high, and the body surface temperature needs to be reduced, and the electric fan needs to be set to a high wind speed. At this time, the environmental temperature is relatively low, that is, the difference between the environmental temperature and the body surface temperature is relatively large, and if the rotating speed of the fan is adjusted according to the environmental temperature, the wind speed required by the person cannot be accurately adjusted, and the use experience is poor.

[0003] The above content is only used to assist in understanding the technical solutions of the present application and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0004] The purpose of the present application is to provide a control method and device of an electric fan, the electric fan, a storage medium and a computer program product, to solve the problem that the wind speed of the electric fan cannot be accurately adjusted to the required wind speed when the difference between the environmental temperature and the body surface temperature is relatively large in the related scheme, to achieve the effect of calculating a comfort parameter by combining the human body temperature and the wind speed of the electric fan, controlling the wind speed of the electric fan according to the comfort parameter, and making the user always in a comfortable state, thereby improving the use experience.

[0005] The present application provides a control method of an electric fan, the method comprising: obtaining the current human body temperature and the current wind speed of the electric fan when the electric fan is running; performing data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; the current human body temperature and the current wind speed of the electric fan are brought into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan to calculate the current comfort parameter; and the wind speed of the electric fan is controlled according to the size of the current comfort parameter.

[0006] In some embodiments, the data fitting according to the pre-stored sample data to obtain the relationship between the comfort parameter and the human body temperature and the electric fan comprises: performing linear regression fitting according to a pre-set mean thermal sensation index, a pre-set blowing sensation index and a pre-set thermal sensation vote index to obtain an evaluation model of the comfort parameter; and the evaluation model of the comfort parameter is:

[0007] P = a * PMV + b * TSV + c * DR;

[0008] wherein, P is the comfort parameter; a, b, c are preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation vote index; DR is the draught rate index;

[0009] According to the evaluation model of the comfort parameter, pre-stored sample data is fitted to obtain a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan; the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is:

[0010] P = a1 + b1 * t + c1 * v;

[0011] wherein, P is the comfort parameter; a1, b1, c1 are preset parameters; t is the human body temperature; v is the wind speed of the electric fan.

[0012] In some embodiments, the wind speed of the electric fan is controlled according to the size of the current comfort parameter, including: after obtaining the current comfort parameter, the current comfort parameter is corrected to obtain a corrected comfort parameter; the wind speed of the electric fan is controlled according to the size of the corrected comfort parameter.

[0013] In some embodiments, the current comfort parameter is corrected to obtain a corrected comfort parameter, including: judging whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than the upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; if the current comfort parameter is not within the preset range and is less than the lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

[0014] In some embodiments, the wind speed of the electric fan is controlled according to the size of the corrected comfort parameter, including: judging the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, the wind speed of the electric fan is increased; if the corrected comfort parameter is less than a second preset value, the wind speed of the electric fan is decreased; if the corrected comfort parameter is between the first preset value and the second preset value, the wind speed of the electric fan is kept unchanged; the first preset value > the second preset value.

[0015] According to the method, the application provides a control device of an electric fan, which comprises: an acquisition unit configured to acquire a current human body temperature and a current wind speed of the electric fan when the electric fan is running; a calculation unit configured to perform data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether a human body is in a comfortable state; the calculation unit is further configured to bring the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan to calculate the current comfort parameter; and a control unit configured to control the wind speed of the electric fan according to the size of the current comfort parameter.

[0016] In some embodiments, the calculation unit performs data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the human body temperature and the electric fan, which comprises: performing linear regression fitting according to a pre-set average thermal sensation index, a pre-set draught rate index and a pre-set thermal sensation vote index to obtain an evaluation model of the comfort parameter; the evaluation model of the comfort parameter is:

[0017] P=a*PMV+b*TSV+c*DR;

[0018] wherein P is the comfort parameter; a, b and c are pre-set parameters; PMV is the average thermal sensation index; TSV is the thermal sensation vote index; and DR is the draught rate index.

[0019] The calculation unit performs data fitting according to the evaluation model of the comfort parameter and pre-stored sample data to obtain a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan; the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is:

[0020] P=a1+b1*t+c1*v;

[0021] wherein P is the comfort parameter; a1, b1 and c1 are pre-set parameters; t is the human body temperature; and v is the wind speed of the electric fan.

[0022] In some embodiments, the control unit controls the wind speed of the electric fan according to the size of the current comfort parameter, which comprises: after obtaining the current comfort parameter, correcting the current comfort parameter to obtain a corrected comfort parameter; and controlling the wind speed of the electric fan according to the size of the corrected comfort parameter.

[0023] In some embodiments, the control unit corrects the current comfort parameter to obtain a corrected comfort parameter, including: determining whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than an upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; if the current comfort parameter is not within the preset range and is less than a lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

[0024] In some embodiments, the control unit controls the wind speed of the electric fan according to the size of the corrected comfort parameter, including: determining the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the corrected comfort parameter is less than a second preset value, reducing the wind speed of the electric fan; if the corrected comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value > the second preset value.

[0025] To match the above device, the present application further provides an electric fan, including: the above-mentioned control device of the electric fan.

[0026] To match the above method, the present application further provides a storage medium, including a stored program, wherein when the program runs, the device where the storage medium is located executes the above-mentioned control method of the electric fan.

[0027] To match the above method, the present application further provides a computer program product, including a computer program, and the computer program product is processed to realize the steps of the above-mentioned control method of the electric fan.

[0028] The scheme of the present application performs data fitting according to the pre-stored sample data of human body temperature and electric fan wind speed, obtains the relationship between the comfort parameter and the human body temperature and the electric fan wind speed, then brings the current human body temperature and the current electric fan wind speed into the relationship to obtain the current comfort parameter, and controls the wind speed of the electric fan according to the size of the comfort parameter. Thus, the comfort parameter is calculated by combining the human body temperature and the electric fan wind speed, the wind speed of the electric fan is controlled according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0029] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application.

[0030] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 Flowchart of an embodiment of the control method of the electric fan of the present application;

[0032] Figure 2 Structural diagram of an embodiment of the control device of the electric fan of the present application;

[0033] Figure 3 Structural block diagram of the control system of the electric fan of the present application;

[0034] Figure 4 Flowchart of the wind speed control method of the electric fan of the present application.

[0035] In combination with the accompanying drawings, the reference signs in the embodiments of the present application are as follows:

[0036] 101 - acquisition unit; 102 - calculation unit; 103 - control unit. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely below in combination with specific embodiments of the present application and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0038] According to an embodiment of the present application, a control method of an electric fan is provided, as shown in Figure 1 Flowchart of an embodiment of the method of the present application. The control method of the electric fan can include steps S110 to S140.

[0039] At step S110, when the electric fan is running, the current human body temperature and the current wind speed of the electric fan are acquired.

[0040] At step S120, data fitting is performed according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state.

[0041] The pre-stored human body temperature and the pre-stored wind speed of the electric fan for data fitting can be experimental data, historical data, simulated data, user-input data, etc., or real-time detected data.

[0042] In some embodiments, in step S120, the data fitting is performed according to the pre-stored sample data to obtain a specific process of a relationship between the comfort parameter and the human body temperature and the electric fan, which includes steps S210 and S220.

[0043] In step S210, a linear regression fitting is performed according to the preset average thermal sensation index, the preset blowing sensation index, and the preset thermal sensation vote index to obtain an evaluation model of the comfort parameter.

[0044] The evaluation model of the comfort parameter is:

[0045] P = a * PMV + b * TSV + c * DR;

[0046] wherein P is the comfort parameter; a, b, and c are preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation vote index; and DR is the blowing sensation index.

[0047] In order to accurately determine the influence of the electric fan wind speed on the user comfort, the present scheme performs linear regression fitting on the average thermal sensation index PMV, the thermal sensation vote index TSV, and the blowing sensation index DR to obtain the comfort parameter evaluation model.

[0048] The average thermal sensation index PMV (Predicted Mean Vote) is a comprehensive evaluation index considering many factors related to human thermal comfort, which is based on the basic equation of human body heat balance and the grade of subjective thermal sensation in psychophysiology. The theoretical basis is that when the human body is in a steady-state thermal environment, the greater the human body heat load, the farther the human body deviates from the thermal comfort state. That is, the greater the positive value of the human body heat load, the hotter the person feels, and the greater the negative value, the colder the person feels. The calculation formula of PMV is:

[0049]

[0050] In the formula, M is the human body energy metabolism rate, which is determined by the activity size of the human body, and the unit is W / m 2 ; W is the mechanical work done by the human body, and the unit is W / m 2 ; P a is the partial pressure of water vapor around the human body, and the unit is kPa; t a is the temperature of the air around the human body, and the unit is ℃; t cl is the temperature of the clothing surface, and the unit is ℃; f cl is the ratio of the body surface area when dressed to the body surface area when naked; is the average radiation temperature, and the unit is ℃; hc is the convective heat transfer coefficient, and the unit is W / (m 2 ·℃); Icl Clothing thermal resistance, unit: (m 2 v ar Air flow rate, unit: m / s.

[0051] Draft rating index DR is an index of user's dissatisfaction caused by draft. Draft rating index depends on air velocity, temperature, turbulence intensity, and user's activity and clothing condition. The calculation formula of draft rating index DR is as follows:

[0052] DR j = (34 - t a )(v a - 0.05) 0 .62(3.37 x v a x T u + 3.14);

[0053] In the formula, t a is the average air temperature around human body, unit: ℃; v a is air flow rate, unit: m / s, if v a ≤ 0.05 m / s, then v a = 0.05 m / s; T u is local turbulence intensity, %, that is, the ratio of standard deviation of local air flow rate to local average air flow rate is between 10% and 60%, if unknown, 40% is taken, and the calculation method is as follows:

[0054]

[0055] Wherein, N v is the number of wind speed recorded by the measuring point within a specified time, v ai is the local instantaneous air flow rate at i moment, unit: m / s.

[0056] Thermal sensation vote TSV is obtained by questionnaire survey, and the experimenter scores the current environment and takes the average value: 3, hot; 2, warm; 1, slightly warm; 0, moderate, -1, slightly cool; -2, cool; -3, cold. The questionnaire results and air velocity during experience at different temperatures are data fitted to obtain the following formula to calculate TSV. The data fitting process of TSV is as follows:

[0057]

[0058] The evaluation model of the comfort parameter is obtained by linear regression fitting of the combination of the average thermal sensation index PMV, the thermal sensation vote index TSV and the draught sensation index DR, and then the comfort parameter is calculated according to the human body temperature and the environmental condition to control the rotating speed of the electric fan, thereby improving the accuracy of the control and making the user feel comfortable.

[0059] In step S220, the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is obtained by data fitting according to the evaluation model of the comfort parameter and pre-stored sample data.

[0060] The relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is:

[0061] P=a1+b1*t+c1*v;

[0062] wherein P is the comfort parameter, a1, b1 and c1 are preset parameters, the value range of which is related to the environmental humidity, t is the human body temperature, and v is the wind speed of the electric fan.

[0063] The comfort parameter P, the human body temperature t and the wind speed v of the electric fan are regression fitted to obtain the calculation formula of the comfort parameter. The value ranges of the parameters a1, b1 and c1 are different under different humidity ranges, and specifically:

[0064] When the environmental humidity is less than 30%, a1 is in the range of [-7.2, -6.9), b1 is in the range of [0.2, 0.32], and c1 is in the range of [-0.04, -0.06].

[0065] When the environmental humidity is in the range of [30%, 40%], a1 is in the range of [-7.25, -7.06), b1 is in the range of [0.22, 0.34], and c1 is in the range of [-0.059, -0.048].

[0066] When the environmental humidity is in the range of [40%, 50%], a1 is in the range of [-7.38, -7.12), b1 is in the range of [0.28, 0.35], and c1 is in the range of [-0.058, -0.049].

[0067] When the environmental humidity is in the range of [50%, 60%], a1 is in the range of [-7.32, -7.19), b1 is in the range of [0.26, 0.31], and c1 is in the range of [-0.057, -0.05].

[0068] When the environmental humidity is in the range of [60%, 70%], a1 is in the range of [-7.45, -7.3), b1 is in the range of [0.29, 0.36], and c1 is in the range of [-0.056, -0.051].

[0069] When the environmental humidity is in the interval [70%, 80%], a6 is in the interval [-7.52, -7.39), b6 is in the interval [0.27, 0.41], and c6 is in the interval [-0.053, -0.052].

[0070] When the comfort parameter is linearly regressed with the human body temperature and the air speed of the electric fan, in order to reflect the difference between the prediction result and the actual data, a loss function can be introduced to guide the training process of the model, and then the model is adjusted to improve the accuracy of the model. Specifically, if the objective function is P(x) = ap(x) + b, then the loss function is:

[0071]

[0072] The loss function is differentiated with respect to a and b, and the point where the derivative is equal to 0 is the extreme value, then:

[0073]

[0074] The gradient descent method is used for optimization:

[0075]

[0076] Wherein, alpha is the learning rate. By calculating the gradient of the loss function with respect to the model parameters, the update direction and step size of the parameters can be determined to optimize the model.

[0077] At step S130, the current human body temperature and the current air speed of the electric fan are brought into the relationship between the comfort parameter and the current human body temperature and the current air speed of the electric fan, and the current comfort parameter is calculated.

[0078] At step S140, the air speed of the electric fan is controlled according to the size of the current comfort parameter.

[0079] In some embodiments, the specific process of controlling the air speed of the electric fan according to the size of the current comfort parameter in step S140 includes steps S310 and S320.

[0080] Step S310, after obtaining the current comfort parameter, the current comfort parameter is corrected to obtain the corrected comfort parameter.

[0081] In some embodiments, in step S310, the specific process of modifying the current comfort parameter to obtain the modified comfort parameter includes: determining whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the modified comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than an upper limit value of the preset range, the upper limit value of the preset range is determined as the modified comfort parameter; if the current comfort parameter is not within the preset range and is less than a lower limit value of the preset range, the lower limit value of the preset range is determined as the modified comfort parameter.

[0082] The value range of the comfort parameter is [-3, 3], if the comfort parameter calculated according to the current human body temperature and the wind speed of the electric fan is within [-3, 3], the wind speed of the electric fan is controlled according to the comfort parameter. If the calculated comfort parameter is greater than 3, the comfort parameter is adjusted to 3; if the calculated comfort parameter is less than -3, the comfort parameter is adjusted to -3. By limiting the range of the comfort parameter, the amplitude of adjusting the wind speed of the electric fan is avoided to affect the user experience.

[0083] In step S320, the wind speed of the electric fan is controlled according to the size of the modified comfort parameter.

[0084] In some embodiments, in step S320, the specific process of controlling the wind speed of the electric fan according to the size of the modified comfort parameter includes: determining the size of the modified comfort parameter; if the modified comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the modified comfort parameter is less than a second preset value, decreasing the wind speed of the electric fan; if the modified comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value is greater than the second preset value.

[0085] The first preset value can be set to 1, and the second preset value can be set to -1. The numerical size of the comfort parameter reflects the current body temperature state of the user, when the comfort parameter is greater than 1, it is considered that the body surface temperature of the user is higher, at this time, the wind speed of the electric fan is increased to quickly cool down; when the comfort parameter is less than -1, it is considered that the body surface temperature of the user is lower, at this time, the wind speed of the electric fan is decreased to avoid the user feeling uncomfortable; when 1 is greater than or equal to the comfort parameter and is greater than or equal to -1, it is considered that the body surface temperature of the user is normal, at this time, the wind speed of the electric fan is kept unchanged. The adjustment amount of increasing and decreasing the wind speed of the electric fan can be set according to the actual situation, for example, the adjustment amount is one wind speed.

[0086] After adjusting the fan speed according to the comfort parameter, the user's body surface temperature and ambient temperature and humidity are re-detected after a period of time, and the comfort parameter is calculated to determine whether the fan speed needs to be adjusted.

[0087] By monitoring human body temperature and ambient temperature and humidity in real time, the fan speed is dynamically adjusted to ensure users experience neither excessively cold nor excessively hot, achieving optimal comfort. By factoring in not only the impact of temperature but also humidity on comfort, the fan's adjustment is more intelligent, meeting users' comfort needs in a variety of temperature and humidity conditions.

[0088] Figure 4 FIG. 1 is a flow chart of a method for controlling the wind speed of an electric fan according to the present invention, as shown in FIG. Figure 4 As shown, the method includes:

[0089] Step 1: The infrared image sensor on the electric fan obtains the human body temperature and the current wind speed value of the electric fan, and calculates the comfort parameter P based on the human body temperature and wind speed value.

[0090] Step 2: Determine the range of the comfort parameter P. If P > 1, increase the fan speed; if P < -1, reduce the fan speed; if 1 ≥ P ≥ -1, maintain the current speed.

[0091] The technical solution of this embodiment uses pre-stored sample data of human body temperature and fan speed to perform data fitting to obtain a relationship between the comfort parameter, human body temperature, and fan speed. The current human body temperature and fan speed are then substituted into this relationship to obtain the current comfort parameter. The fan speed is then controlled based on the comfort parameter. Thus, by combining human body temperature and fan speed to calculate the comfort parameter and then controlling the fan speed based on the comfort parameter, the user remains in a comfortable state, improving the user experience.

[0092] According to an embodiment of the present invention, a control device for an electric fan corresponding to the control method for the electric fan is also provided. Figure 2 The structure diagram of an embodiment of the device of the present invention is shown in FIG. The control device of the electric fan may include: an acquisition unit 101 , a calculation unit 102 , and a control unit 103 .

[0093] The acquisition unit 101 is configured to acquire the current human body temperature and the current wind speed of the electric fan when the electric fan is running. The specific functions and processing of the acquisition unit 101 are shown in step S110.

[0094] The computing unit 102 is configured to perform data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and a current human body temperature and a current wind speed of the electric fan, the comfort parameter being used to evaluate whether the human body is in a comfortable state. The specific functions and processes of the computing unit 102 are described with reference to step S120.

[0095] The pre-stored human body temperature and the pre-stored wind speed of the electric fan for data fitting can be experimental data, historical data, simulation data, user input data, or real-time detected data.

[0096] In some embodiments, the computing unit 102 performs data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the human body temperature and the electric fan, including:

[0097] The computing unit 102 is specifically further configured to perform linear regression fitting according to a pre-set average thermal sensation index, a pre-set draught rate index, and a pre-set thermal sensation vote index to obtain an evaluation model of the comfort parameter. The specific functions and processes of the computing unit 102 are described with reference to step S210.

[0098] The evaluation model of the comfort parameter is:

[0099] P = a * PMV + b * TSV + c * DR;

[0100] wherein P is the comfort parameter; a, b, and c are pre-set parameters; PMV is the average thermal sensation index; TSV is the thermal sensation vote index; and DR is the draught rate index.

[0101] In order to accurately determine the influence of the wind speed of the electric fan on the comfort of the user, the present scheme performs linear regression fitting on the average thermal sensation index PMV, the thermal sensation vote index TSV, and the draught rate index DR to obtain an evaluation model of the comfort parameter.

[0102] The average thermal sensation index PMV (Predicted Mean Vote) is a comprehensive evaluation index considering many factors related to human thermal comfort, which is based on the basic equation of human body heat balance and the grade of subjective thermal sensation in psychophysiology. The theoretical basis is that when the human body is in a steady-state thermal environment, the greater the heat load of the human body, the farther the human body deviates from the state of thermal comfort. That is, the greater the positive value of the heat load of the human body, the hotter the person feels, and the greater the negative value, the colder the person feels. The calculation formula of PMV is:

[0103]

[0104] In the formula, M is the energy metabolism rate of the human body, which is determined by the activity size of the human body, and the unit is W / m 2; W is the mechanical work done by the human body, unit is W / m 2 ; P a is the water vapor partial pressure around the human body, unit is kPa; t a is the air temperature around the human body, unit is ℃; t cl is the clothing surface temperature, unit is ℃; f cl is the ratio of the body surface area of the person wearing clothes to the body surface area of the person without wearing clothes; is the mean radiant temperature, unit is ℃; h c is the convective heat transfer coefficient, unit is W / (m 2 ·℃) ; I cl is the clothing thermal resistance, unit is (m 2 ·℃ / W) ; v ar is the air flow rate, unit is m / s.

[0105] The draft rating index DR is an index of the degree of dissatisfaction of the user caused by the draft. The draft rating index depends on the speed, temperature, turbulence intensity of the air flow, and the activity and clothing condition of the user. The calculation formula of the draft rating index DR is:

[0106] DR j = (34-t a )(v a -0.05) 0.62 (3.37×v a ×T u +3.14) ;

[0107] In the formula, t a is the average air temperature around the human body, unit is ℃; v a is the air flow rate, unit is m / s, if v a ≤ 0.05 m / s, then v a = 0.05 m / s; T u is the local turbulence intensity, %, that is, the ratio of the standard deviation of the local air flow rate to the local average air flow rate is between 10% and 60%, if unknown, take 40%, the calculation method is:

[0108]

[0109] Wherein, N v is the number of wind speed recorded by the measuring point within a specified time, v ai is the local instantaneous air flow rate at the i-th moment, unit is m / s.

[0110] The thermal sensation vote index TSV (Thermal Sensation Vote) is obtained by questionnaire survey, and the experimenter scores the current environment and takes the average value: 3, hot; 2, warm; 1, slightly warm; 0, moderate, -1, slightly cool; -2, cool, -3, cold. The questionnaire results at different temperatures and the wind speed during the experience are fitted to obtain the following formula to calculate TSV. The data fitting process is as follows:

[0111]

[0112] By combining the average thermal sensation index PMV, the thermal sensation vote index TSV, and the blowing sensation index DR to perform linear regression fitting, an evaluation model of the comfort parameter is obtained, and then the comfort parameter is calculated according to the human body temperature and the environmental conditions to control the speed of the electric fan, which improves the accuracy of the control and makes the user feel comfortable.

[0113] The calculation unit 102 is specifically further configured to perform data fitting on the pre-stored sample data according to the evaluation model of the comfort parameter, to obtain a relationship formula between the comfort parameter and the current human body temperature and the current wind speed of the electric fan. For specific functions and processing of the calculation unit 102, refer to step S220.

[0114] The relationship formula between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is as follows:

[0115] P = a1 + b1 * t + c1 * v;

[0116] wherein P is the comfort parameter; a1, b1, and c1 are all preset parameters, and the value range is related to the environmental humidity; t is the human body temperature; and v is the wind speed of the electric fan.

[0117] The comfort parameter P, the human body temperature t, and the wind speed v of the electric fan are regressed and fitted to obtain a calculation formula of the comfort parameter. In different humidity ranges, the value ranges of the parameters a1, b1, and c1 are different, and specifically:

[0118] When the environmental humidity is < 30%, a1 ∈ [-7.2, -6.9), b1 ∈ [0.2, 0.32], and c1 ∈ [-0.04, -0.06].

[0119] When the environmental humidity is in the interval [30%, 40%], a1 ∈ [-7.25, -7.06), b1 ∈ [0.22, 0.34], and c1 ∈ [-0.059, -0.048].

[0120] When the environmental humidity is in the interval [40%, 50%], a1 ∈ [-7.38, -7.12), b1 ∈ [0.28, 0.35], and c1 ∈ [-0.058, -0.049].

[0121] When the environmental humidity is in the interval [50%, 60%], a1∈[-7.32, -7.19), b1∈[0.26, 0.31], c1∈[-0.057, -0.05].

[0122] When the environmental humidity is in the interval [60%, 70%], a1∈[-7.45, -7.3), b1∈[0.29, 0.36], c1∈[-0.056, -0.051].

[0123] When the environmental humidity is in the interval [70%, 80%], a6∈[-7.52, -7.39), b6∈[0.27, 0.41], c6∈[-0.053, -0.052].

[0124] In the linear regression fitting of the comfort parameter with the human body temperature and the wind speed of the electric fan, in order to reflect the difference between the prediction result and the actual data, a loss function can be introduced to guide the training process of the model, and then the model is adjusted to improve the accuracy of the model. Specifically, if the target function is P(x) = ap(x) + b, then the loss function is:

[0125]

[0126] The loss function is differentiated with respect to a and b, and the point where the derivative is equal to 0 is the extreme value, then:

[0127]

[0128]

[0129] The gradient descent method is used for optimization:

[0130]

[0131] Where α is the learning rate. By calculating the gradient of the loss function with respect to the model parameters, the update direction and step size of the parameters can be determined to optimize the model.

[0132] The computing unit 102 is also configured to bring the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan, and calculate the current comfort parameter. For specific functions and processing of the computing unit 102, see step S130.

[0133] The control unit 103 is configured to control the wind speed of the electric fan according to the size of the current comfort parameter. For specific functions and processing of the control unit 103, see step S140.

[0134] In some embodiments, the control unit 103 controls the wind speed of the electric fan according to the size of the current comfort parameter, including:

[0135] The control unit 103 is specifically further configured to correct the current comfort parameter to obtain a corrected comfort parameter after obtaining the current comfort parameter. For specific functions and processes of the control unit 103, see step S310.

[0136] In some embodiments, the control unit 103 corrects the current comfort parameter to obtain a corrected comfort parameter, including: determining whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than the upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; if the current comfort parameter is not within the preset range and is less than the lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

[0137] The value range of the comfort parameter is [-3, 3], if the comfort parameter calculated according to the current human body temperature and the wind speed of the electric fan is within [-3, 3], the wind speed of the electric fan is controlled according to the comfort parameter. If the calculated comfort parameter is > 3, the comfort parameter is adjusted to 3; if the calculated comfort parameter is < -3, the comfort parameter is adjusted to -3. By limiting the range of the comfort parameter, the amplitude of adjusting the wind speed of the electric fan is avoided to be too large to affect the user experience.

[0138] The control unit 103 is specifically further configured to control the wind speed of the electric fan according to the size of the corrected comfort parameter. For specific functions and processes of the control unit 103, see step S320.

[0139] In some embodiments, the control unit 103 controls the wind speed of the electric fan according to the size of the corrected comfort parameter, including: determining the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the corrected comfort parameter is less than a second preset value, decreasing the wind speed of the electric fan; if the corrected comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value > the second preset value.

[0140] The first preset value can be set as 1, and the second preset value can be set as -1. The value of the comfort parameter reflects the current body temperature state of the user. When the comfort parameter is greater than 1, it is considered that the body surface temperature of the user is relatively high, and the wind speed of the electric fan is increased to rapidly reduce the temperature. When the comfort parameter is less than -1, it is considered that the body surface temperature of the user is relatively low, and the wind speed of the electric fan is reduced to avoid the user from feeling uncomfortable. When 1 is greater than or equal to the comfort parameter and is greater than or equal to -1, it is considered that the body surface temperature of the user is normal, and the wind speed of the electric fan can be maintained unchanged. The adjustment amount of the wind speed of the electric fan when the wind speed is increased or reduced can be set according to actual conditions, for example, the adjustment amount is one wind speed.

[0141] After the wind speed of the electric fan is adjusted according to the size of the comfort parameter, the body surface temperature of the user and the environmental temperature and humidity are detected again after a period of time, and the comfort parameter is calculated to determine whether the wind speed of the electric fan needs to be adjusted.

[0142] By monitoring the body temperature and the environmental temperature and humidity in real time, the wind speed of the electric fan is dynamically adjusted to ensure that the user does not feel too cold or too hot, thereby achieving the best comfortable state. Not only the influence of temperature on comfort is considered, but also the effect of humidity is considered, so that the adjustment of the electric fan is more intelligent, and the comfort demand of the user under various temperature and humidity conditions is met.

[0143] Figure 4 A flowchart of the wind speed control method of the electric fan of the present application is shown in FIG. 1. Figure 4 The method comprises the following steps.

[0144] In step 1, the infrared image sensor on the electric fan acquires the body temperature, and acquires the wind speed value of the current electric fan, and calculates the comfort parameter P according to the body temperature and the wind speed value.

[0145] In step 2, the range in which the comfort parameter P is located is judged. If P is greater than 1, the wind speed of the electric fan is increased. If P is less than -1, the wind speed of the electric fan is reduced. If 1 is greater than or equal to P and is greater than or equal to -1, the current wind speed is maintained unchanged.

[0146] Since the processing and functions realized by the device of the present embodiment are basically corresponding to the embodiments, principles and examples of the foregoing method, the description of the present embodiment is not detailed, and the related description in the foregoing embodiments can be referred to, which is not repeated here.

[0147] According to the technical scheme of the present application, the sample data of the body temperature and the wind speed of the electric fan are pre-stored, data fitting is performed, a relationship between the comfort parameter and the body temperature and the wind speed of the electric fan is obtained, the current body temperature and the current wind speed of the electric fan are brought into the relationship, the current comfort parameter is obtained, and the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, the comfort parameter is calculated by combining the body temperature and the wind speed of the electric fan, the wind speed of the electric fan is controlled according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0148] According to an embodiment of the present application, an electric fan corresponding to the control device of the electric fan is also provided. The electric fan can comprise the control device of the electric fan described above.

[0149] Since the processing and functions realized by the electric fan of the present embodiment are basically corresponding to the embodiments, principles and examples of the aforementioned device, the descriptions of the present embodiment that are not elaborated can be referred to the relevant descriptions in the aforementioned embodiments, which will not be repeated here.

[0150] According to the technical solution of the present application, the sample data of the human body temperature and the electric fan wind speed are pre-stored, and data fitting is performed to obtain a relationship between the comfort parameter and the human body temperature and the electric fan wind speed. Then, the current human body temperature and the current electric fan wind speed are brought into the relationship to obtain the current comfort parameter. The wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, the comfort parameter is calculated by combining the human body temperature and the electric fan wind speed, and the wind speed of the electric fan is controlled according to the comfort parameter, so that the user is always in a comfortable state, and the use experience is improved.

[0151] According to an embodiment of the present application, a storage medium corresponding to the control method of the electric fan is also provided. The storage medium comprises a stored program, wherein when the program is running, the device where the storage medium is located performs the control method of the electric fan described above.

[0152] Since the processing and functions realized by the storage medium of the present embodiment are basically corresponding to the embodiments, principles and examples of the aforementioned method, the descriptions of the present embodiment that are not elaborated can be referred to the relevant descriptions in the aforementioned embodiments, which will not be repeated here.

[0153] According to the technical solution of the present application, the sample data of the human body temperature and the electric fan wind speed are pre-stored, and data fitting is performed to obtain a relationship between the comfort parameter and the human body temperature and the electric fan wind speed. Then, the current human body temperature and the current electric fan wind speed are brought into the relationship to obtain the current comfort parameter. The wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, the comfort parameter is calculated by combining the human body temperature and the electric fan wind speed, and the wind speed of the electric fan is controlled according to the comfort parameter, so that the user is always in a comfortable state, and the use experience is improved.

[0154] According to an embodiment of the present application, a computer program product corresponding to the control method of the electric fan is also provided. The computer program product comprises a computer program, and the computer program product is processed to realize the steps of the control method of the electric fan.

[0155] Since the processing and functions realized by the computer program product of the embodiment are basically corresponding to the embodiments, principles and examples of the foregoing method, the description of the embodiment is not described in detail, and the related description in the foregoing embodiments can be referred to, and will not be described here.

[0156] According to the technical scheme of the present application, the sample data of human body temperature and electric fan wind speed are pre-stored, data fitting is performed, a relationship between the comfort parameter and the human body temperature and the electric fan wind speed is obtained, the current human body temperature and the current electric fan wind speed are brought into the relationship, the current comfort parameter is obtained, and the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, the comfort parameter is calculated by combining the human body temperature and the electric fan wind speed, the wind speed of the electric fan is controlled according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0157] In summary, those skilled in the art can easily understand that the above-mentioned advantageous modes can be freely combined and superimposed without conflict.

[0158] The above only describes the embodiments of the present application and is not used to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of the claims of the present application.

Claims

1. A control method of an electric fan, characterized by, The method comprises: acquiring a current human body temperature and a current wind speed of the electric fan when the electric fan is running; performing data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether a human body is in a comfortable state; the sample data comprises human body temperature sample data and electric fan wind speed sample data; bringing the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan to calculate the current comfort parameter; controlling the wind speed of the electric fan according to the size of the current comfort parameter; wherein the data fitting according to the pre-stored sample data to obtain the relationship between the comfort parameter and the human body temperature and the wind speed of the electric fan comprises: performing linear regression fitting according to a pre-set average thermal sensation index, a pre-set draught rate index and a pre-set thermal sensation vote index to obtain an evaluation model of the comfort parameter; the evaluation model of the comfort parameter is: P = a * PMV + b * TSV + c * DR; wherein P is the comfort parameter; a, b and c are pre-set parameters; PMV is the average thermal sensation index; TSV is the thermal sensation vote index; and DR is the draught rate index; performing data fitting according to the evaluation model of the comfort parameter and pre-stored sample data to obtain the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan; the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is: P = a1 + b1 * t + c1 * v; wherein P is the comfort parameter; a1, b1 and c1 are pre-set parameters; t is the human body temperature; and v is the wind speed of the electric fan.

2. The control method of the electric fan according to claim 1, characterized by, controlling the wind speed of the electric fan according to the size of the current comfort parameter comprises: after obtaining the current comfort parameter, correcting the current comfort parameter to obtain a corrected comfort parameter; controlling the wind speed of the electric fan according to the size of the corrected comfort parameter.

3. The control method of the electric fan according to claim 2, characterized by, correcting the current comfort parameter to obtain a corrected comfort parameter comprises: judging whether the current comfort parameter is within a pre-set range; if the current comfort parameter is within the pre-set range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the pre-set range and is greater than an upper limit value of the pre-set range, the upper limit value of the pre-set range is determined as the corrected comfort parameter; if the current comfort parameter is not within the pre-set range and is less than a lower limit value of the pre-set range, the lower limit value of the pre-set range is determined as the corrected comfort parameter.

4. The control method of an electric fan according to claim 2 or 3, characterized in that, controlling the wind speed of the electric fan according to the size of the corrected comfort parameter comprises: judging the size of the corrected comfort parameter; If the comfort parameter after the correction is greater than a first preset value, the wind speed of the electric fan is increased. If the comfort parameter after the correction is less than a second preset value, the wind speed of the electric fan is decreased. If the comfort parameter after the correction is between the first preset value and the second preset value, the wind speed of the electric fan is kept unchanged; the first preset value is greater than the second preset value.

5. A control device for an electric fan, characterized by The control device comprises: An acquisition unit configured to acquire a current body temperature and a current wind speed of the electric fan when the electric fan is running; A calculation unit configured to perform data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; The calculation unit is further configured to bring the current body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current body temperature and the current wind speed of the electric fan to calculate the current comfort parameter; A control unit configured to control the wind speed of the electric fan according to the size of the current comfort parameter; The calculation unit performs data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the body temperature and the wind speed of the electric fan, comprising: Linear regression fitting is performed according to a pre-set average thermal sensation index, a pre-set draught rate index, and a pre-set thermal sensation vote index to obtain an evaluation model of the comfort parameter; the evaluation model of the comfort parameter is: P = a * PMV + b * TSV + c * DR; Wherein, P is the comfort parameter; a, b, and c are pre-set parameters; PMV is the average thermal sensation index; TSV is the thermal sensation vote index; and DR is the draught rate index; Data fitting is performed according to the evaluation model of the comfort parameter and pre-stored sample data to obtain a relationship between the comfort parameter and the current body temperature and the current wind speed of the electric fan; the relationship between the comfort parameter and the current body temperature and the current wind speed of the electric fan is: P = a1 + b1 * t + c1 * v; Wherein, P is the comfort parameter; a1, b1, and c1 are pre-set parameters; t is the body temperature; and v is the wind speed of the electric fan.

6. An electric fan characterized by comprising: Comprise: The control device of the electric fan according to claim 5.

7. A storage medium, characterized by The storage medium comprises a stored program, wherein when the program is running, the device where the storage medium is located performs the control method of the electric fan according to any one of claims 1 to 4.

8. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the method according to any one of claims 1 to 4.

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