A wireless charging adapter, a wireless charging method, a device and a system

Abstract

The present application relates to the field of wireless charging technology, and specifically to a wireless charging adapter, a wireless charging method, a device and a system, the method comprising: collecting temperature data during the operation of the wireless charging adapter, determining the temperature regulation disorder of the mobile phone temperature sequence based on the difference between the positive and negative values ​​of the differential values ​​of the temperature data of all time periods and the temperature fluctuation, and combining the change difference of the mobile phone temperature regulation index in adjacent time periods to determine the smoothing response coefficient, adjust the smoothing coefficient of the cubic exponential smoothing algorithm, and obtain the mobile phone temperature prediction result of the mobile phone temperature sequence; adjust the output power of the wireless charging adapter based on the mobile phone temperature prediction result. The present application aims to improve the accuracy of the prediction effect of the mobile phone temperature data, and then accurately adjust the output power of the wireless charging adapter based on the prediction result of the mobile phone temperature.

Description

Technical Field

[0001] The present application relates to the field of wireless charging technology, and in particular to a wireless charging adapter, a wireless charging method, a device and a system. Background Art

[0002] While people are enjoying the wonderful life brought by mobile phones, frequent charging of mobile phones makes people feel distressed. Wireless charging technology has brought great convenience to mobile phone charging, so mobile phone wireless charging technology is very popular among mobile phone consumers. Wireless charging technology, also known as inductive charging technology, is currently relatively mature in electromagnetic induction wireless charging technology, but it still has shortcomings in the application of mobile phone charging. When using a wireless charging adapter to charge a mobile phone, the output power of the wireless charging adapter is not constant. When the output power of the wireless charging adapter is high, it often causes the temperature of the mobile phone to be too high, which is easy to damage the mobile phone; and when the output power of the wireless charging adapter is low, it often causes the charging efficiency of the mobile phone to decrease.

[0003] With the continuous development of machine learning, the prediction algorithm is used to predict the temperature of mobile phones. The output power of wireless charging adapters can be adjusted based on the predicted results of mobile phone temperature, which can effectively take into account the problems of excessively high mobile phone temperature and low charging efficiency. Common prediction algorithms include the cubic exponential smoothing algorithm, which can quickly predict mobile phone temperature time series with linear trends and seasonal characteristics. However, the selection of smoothing coefficients in this algorithm is difficult, which can easily lead to poor prediction of mobile phone temperature, and thus fail to accurately adjust the output power of wireless charging adapters based on the predicted results of mobile phone temperature. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a wireless charging adapter, a wireless charging method, a device and a system. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a wireless charging method, the method comprising the following steps:

[0006] The temperature sensor is used to collect the heat sink temperature data and the mobile phone temperature data during the operation of the wireless charging adapter, and obtain the heat sink temperature sequence and the mobile phone temperature sequence;

[0007] Based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence, the heat dissipation effectiveness value of each time period is determined; based on the temperature fluctuation of the temperature data of each time period in the mobile phone temperature sequence, the temperature stability of the mobile phone in each time period is determined; combining the heat dissipation effectiveness value and the temperature stability of the mobile phone, the temperature regulation index of the mobile phone in each time period is determined;

[0008] The distribution disorder of the mobile phone temperature adjustment index in all time periods is used as the temperature adjustment disorder of the mobile phone temperature series; the smoothing response coefficient is determined by combining the temperature adjustment disorder and the change difference of the mobile phone temperature adjustment index in all adjacent time periods;

[0009] The smoothed response coefficient is used as the smoothing coefficient of the cubic exponential smoothing algorithm to obtain the mobile phone temperature prediction result of the mobile phone temperature series;

[0010] The output power of the wireless charging adapter is adjusted based on the mobile phone temperature prediction results.

[0011] Preferably, the method for determining the heat dissipation effectiveness value in each time period includes:

[0012] Differentiate the temperature data of each time period in the heat sink temperature series;

[0013] Calculate the product of the number of negative elements in the difference value after difference in each time period and the absolute value of the cumulative sum of all negative elements as the numerator; calculate the product of the number of positive elements in the difference value after difference in each time period and the cumulative sum of all positive elements as the denominator;

[0014] The ratio of the numerator to the denominator is used as the heat dissipation effectiveness value for each time period.

[0015] Preferably, the method for determining the temperature stability of the mobile phone in each time period includes:

[0016] The extreme point detection algorithm is used to obtain the extreme points in the temperature data of each time period in the mobile phone temperature series;

[0017] When the number of extreme value points in the temperature data of each time period is less than or equal to a preset value, the temperature stability of the mobile phone in each time period is set to 1;

[0018] On the contrary, the fluctuation of the temperature data of all extreme points in each time period is calculated, the number of extreme points and the fluctuation are fused, and the inverse of the fusion result is used as the temperature stability of the mobile phone in each time period.

[0019] Preferably, the method for determining the temperature adjustment index of the mobile phone in each time period includes:

[0020] The inverse number of the temperature stability of the mobile phone in each time period is used as the exponent of an exponential function with a natural constant as the base, and the product of the calculation result of the exponential function and the heat dissipation effectiveness value of the corresponding time period is used as the temperature adjustment index of the mobile phone in the corresponding time period.

[0021] Preferably, the temperature adjustment disorder of the mobile phone temperature sequence is the information entropy of the mobile phone temperature adjustment index in all time periods.

[0022] Preferably, the method for determining the smoothing response coefficient includes:

[0023] Calculate the difference between the temperature adjustment index of the mobile phone in each adjacent time period, and calculate the cumulative sum of the differences in all adjacent time periods;

[0024] Calculating the product of the cumulative sum and the temperature regulation disorder as the regulation factor;

[0025] A smoothing response coefficient is determined based on the adjustment factor; wherein the adjustment factor is positively correlated with the smoothing response coefficient.

[0026] Preferably, adjusting the output power of the wireless charging adapter based on the prediction result of the mobile phone temperature includes:

[0027] When there is mobile phone temperature data higher than the preset rated temperature in the mobile phone temperature prediction result, the output power of the wireless charging adapter is reduced by a preset adjustment power value; otherwise, it is not adjusted.

[0028] In a second aspect, an embodiment of the present application provides a wireless charging adapter, the wireless charging adapter comprising:

[0029] The wireless charging temperature acquisition module is used to collect the heat sink temperature data and the mobile phone temperature data during the operation of the wireless charging adapter through the temperature sensor to obtain the heat sink temperature sequence and the mobile phone temperature sequence;

[0030] The wireless charging temperature processing module is used to determine the heat dissipation effectiveness value of each time period based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence; determine the temperature stability of the mobile phone in each time period based on the temperature fluctuation of the temperature data of each time period in the mobile phone temperature sequence; determine the temperature adjustment index of the mobile phone in each time period in combination with the heat dissipation effectiveness value and the temperature stability of the mobile phone; use the distribution disorder of the mobile phone temperature adjustment index of all time periods as the temperature adjustment disorder of the mobile phone temperature sequence; determine the smoothing response coefficient in combination with the temperature adjustment disorder and the change difference of the mobile phone temperature adjustment index of all adjacent time periods;

[0031] A mobile phone temperature prediction module is used to use the smoothing response coefficient as the smoothing coefficient of the cubic exponential smoothing algorithm to obtain the mobile phone temperature prediction result of the mobile phone temperature sequence;

[0032] The charging power adjustment module is used to adjust the output power of the wireless charging adapter based on the mobile phone temperature prediction result.

[0033] In a third aspect, an embodiment of the present application further provides a wireless charging device, wherein the wireless charging device stores a computer program, and when the computer program is executed by a processor, a wireless charging method as described in the first aspect is implemented.

[0034] In a fourth aspect, an embodiment of the present application further provides a wireless charging system, the system comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of a wireless charging method as described in the first aspect are implemented.

[0035] It can be seen from the above embodiments that the wireless charging adapter, wireless charging method, device and system provided in the embodiments of the present application have at least the following beneficial effects:

[0036] The present application uses a cubic exponential smoothing algorithm to obtain a prediction result of the mobile phone temperature, and adjusts the output power of the wireless charging adapter based on the prediction result of the mobile phone temperature. Compared with the prior art, when the cubic exponential smoothing algorithm is used to predict the mobile phone temperature, the unreasonable value of the smoothing coefficient will lead to a poor prediction effect on the mobile phone temperature, and thus the output power of the wireless charging adapter cannot be accurately adjusted based on the prediction result of the mobile phone temperature. The present application determines the heat dissipation effectiveness value of each time period based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence. The beneficial effect is that by analyzing the heat dissipation of the wireless charging adapter The change in thermal conditions between adjacent temperature data can evaluate the heat dissipation effect of the wireless charging adapter during operation; the present application determines the temperature stability of the mobile phone in each time period based on the temperature fluctuation of the temperature data in each time period in the mobile phone temperature sequence. The beneficial effect is that the stability of the output power of the wireless charging adapter can be reflected by analyzing the temperature fluctuation characteristics of the mobile phone temperature sequence in each time period. That is, the greater the temperature fluctuation of the mobile phone temperature sequence in each time period, the smaller the stability of the output power of the wireless charging adapter, and the stronger the regulating effect on the mobile phone temperature at this time; the present application combines the heat dissipation effectiveness value and the temperature stability of the mobile phone to determine the temperature regulation of the mobile phone in each time period. The temperature adjustment index has the beneficial effect of combining the above two indicators to reflect the ability to adjust the temperature of the mobile phone during the wireless charging process in each time period to a certain extent; the application uses the distribution disorder of the mobile phone temperature adjustment index in all time periods as the temperature adjustment disorder of the mobile phone temperature sequence, and the beneficial effect is that by analyzing the inconsistency of the changes between the mobile phone temperature adjustment indexes in different time periods from an overall perspective, the response speed of the mobile phone temperature data change is analyzed to improve the prediction effect of the mobile phone temperature during the wireless charging process; the application combines the temperature adjustment disorder and the change difference of the mobile phone temperature adjustment index in all adjacent time periods to determine the smoothing response coefficient, and the beneficial effect is that when using the wireless charging adapter, the change of the mobile phone temperature may fluctuate more frequently in a short period of time, as well as the degree of inconsistency at the overall level, so that a smoothing response coefficient that is more suitable for a specific scenario can be selected; the application uses the smoothing response coefficient as the smoothing coefficient of the cubic exponential smoothing algorithm, obtains the mobile phone temperature prediction result of the mobile phone temperature sequence, and adjusts the output power of the wireless charging adapter based on the mobile phone temperature prediction result, and the beneficial effect is that by adaptively obtaining the smoothing coefficient in the cubic exponential smoothing algorithm, the accuracy of the prediction effect of the mobile phone temperature data is improved, and then the output power of the wireless charging adapter can be accurately adjusted based on the prediction result of the mobile phone temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A flowchart of a wireless charging method provided in accordance with an embodiment of the present application;

[0039] Figure 2 A flowchart of specific steps for obtaining a smooth response coefficient based on temperature distribution characteristics provided in one embodiment of the present application;

[0040] Figure 3 A flow chart of a method for determining a heat dissipation effectiveness value for each time period provided in one embodiment of the present application;

[0041] Figure 4 A flow chart of a method for determining the temperature stability of a mobile phone in each time period provided in one embodiment of the present application;

[0042] Figure 5 A flow chart of a method for determining a smoothing response coefficient provided in one embodiment of the present application;

[0043] Figure 6 A schematic diagram of a mobile phone temperature prediction result provided by an embodiment of the present application;

[0044] Figure 7 A schematic diagram of the structure of a wireless charging adapter provided in one embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation, structure, features and effects of a wireless charging adapter, wireless charging method, device and system proposed in the present application in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0046] Unless otherwise specified and limited, terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application.

[0047] The following describes in detail a wireless charging adapter, a wireless charging method, a device and a system provided by the present application in conjunction with the accompanying drawings.

[0048] Please see attached Figure 1 , which shows a flow chart of a wireless charging method provided by an embodiment of the present application, the method comprising the following steps:

[0049] In the first step, the temperature sensor is used to collect the heat sink temperature data and the mobile phone temperature data during the operation of the wireless charging adapter to obtain the heat sink temperature sequence and the mobile phone temperature sequence.

[0050] The purpose of this solution is to improve the prediction effect of the mobile phone temperature during the wireless charging process, and then accurately adjust the output power of the wireless charging adapter based on the predicted result of the mobile phone temperature, so as to effectively take into account the problems of excessively high mobile phone temperature and low charging efficiency.

[0051] The mobile phone is wirelessly charged through a wireless charging adapter, and the wireless charging adapter is equipped with a wireless charging temperature acquisition module, a wireless charging temperature processing module, a mobile phone temperature prediction module and a charging power adjustment module. The wireless charging temperature acquisition module is used to collect temperature data during the wireless charging process, the wireless charging temperature processing module is used to analyze the temperature change characteristics of the temperature data during the wireless charging process, the mobile phone temperature prediction module is used to predict the future temperature of the mobile phone, and the charging power adjustment module is used to use the mobile phone temperature prediction result to adjust the output power of the wireless charging adapter at the current moment.

[0052] When the wireless charging adapter is used to wirelessly charge the mobile phone, the temperature sensor is used to collect the temperature data of the heat sink in the wireless charging adapter, and the digital spot thermometer is used to collect the temperature data of the mobile phone during the wireless charging process, wherein the digital spot thermometer is installed at the center of the mobile phone screen. In this embodiment, the data collection time interval is 1s, and the data collection time is 10min.

[0053] In order to facilitate the subsequent accurate prediction of the mobile phone temperature, the collected heat sink temperature data and mobile phone temperature data are respectively arranged in a sequence in ascending time order as a heat sink temperature sequence and a mobile phone temperature sequence.

[0054] In this step, there is a wireless charging temperature acquisition module for collecting temperature data during the wireless charging process. In the second step, there is a wireless charging temperature processing module for analyzing the temperature change characteristics of the temperature data during the wireless charging process. In the third step, there is a mobile phone temperature prediction module for predicting the future temperature of the mobile phone. In the fourth step, there is a charging power adjustment module for adjusting the output power of the wireless charging adapter at the current moment using the mobile phone temperature prediction result.

[0055] The second step is to analyze the temperature data of all time periods in the heat sink temperature series and the mobile phone temperature series, extract the temperature distribution characteristics, and obtain the smooth response coefficient.

[0056] Furthermore, under normal circumstances, the output power of the wireless charging adapter is not constant, and due to the heat dissipation function of the wireless charging adapter, the heat sink temperature and the mobile phone temperature will fluctuate. At the same time, the heat sink temperature is closely related to the change of the mobile phone temperature and the output power of the wireless charging adapter. When the input power is large, the heat dissipation function cannot effectively dissipate heat, which will cause the temperature to rise rapidly; when the output power is small, the heat dissipation function can effectively exert its heat dissipation capacity, which will cause the temperature to show a stable or slowly decreasing trend.

[0057] In order to analyze the effectiveness of heat dissipation in different time periods, the heat sink temperature sequence and the mobile phone temperature sequence are evenly divided into 20 subsequences respectively, and the heat sink temperature subsequence and the mobile phone temperature subsequence of each time period are obtained.

[0058] In one embodiment of the present application, the temperature data of all time periods in the heat sink temperature sequence and the mobile phone temperature sequence are analyzed to extract the temperature distribution characteristics, and the specific steps of obtaining the smooth response coefficient based on the temperature distribution characteristics are shown in the attached flowchart. Figure 2 As shown, specifically:

[0059] A1, based on the quantitative difference and the numerical difference between the positive value and the negative value in the differential value of the temperature data in each time period in the heat sink temperature series, the heat dissipation effectiveness value of each time period is determined.

[0060] Usually, when the heat dissipation capacity of the heat sink is strong, the temperature of the heat sink is stable and even shows a slowly decreasing trend. Accordingly, this embodiment obtains the first-order difference sequence of the heat sink temperature subsequence in each time period, and counts the number of all negative elements and the number of positive elements in the first-order difference sequence of the heat sink temperature subsequence in each time period. The calculation of the first-order difference sequence is a well-known technology, and the specific process will not be repeated here.

[0061] Based on the above analysis, in this application, the heat dissipation effectiveness value of each time period is determined based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence, specifically:

[0062] The temperature data of each time period in the heat sink temperature series is differentiated; the product of the number of negative elements in the differential value after differentiation in each time period and the absolute value of the cumulative sum of all negative elements is calculated as the numerator; the product of the number of positive elements in the differential value after differentiation in each time period and the cumulative sum of all positive elements is calculated as the denominator; the ratio of the numerator to the denominator is used as the heat dissipation effectiveness value of each time period.

[0063] This embodiment takes the i-th time period as an example for analysis. When calculating the heat dissipation effectiveness value of the i-th time period, the denominator may be 0. In order to avoid the denominator being 0, a preset parameter is added when calculating the denominator. , in this embodiment, the value is 1.

[0064] In other embodiments of the present application, when calculating the heat dissipation effectiveness value of each time period, the difference between the numerator and the denominator of each time period mentioned above can also be used as the heat dissipation effectiveness value of the corresponding time period. The specific calculation method is analyzed by the implementer based on actual conditions.

[0065] It should be understood that, when the proportion of the product of the number of negative elements in the first-order difference sequence of the heat sink temperature subsequence in a certain time period and the absolute value of the cumulative sum of all negative elements is larger, it indicates to a certain extent that the heat sink temperature shows a slow downward trend, resulting in more temperature difference values ​​being negative. At this time, the better the heat dissipation effect of the heat sink, the greater the heat dissipation effectiveness value in a certain time period.

[0066] In one embodiment of the present application, a flow chart of a method for determining the heat dissipation effectiveness value in each time period is shown in the attached figure. Figure 3 shown.

[0067] A2, based on the temperature fluctuation of the temperature data in each time period in the temperature sequence of the mobile phone, determines the temperature stability of the mobile phone in each time period.

[0068] The temperature fluctuation characteristics within the mobile phone temperature subsequence can reflect the stability of the wireless charging adapter output power. That is, the greater the temperature fluctuation within the mobile phone temperature subsequence, the less stable the wireless charging adapter output power is, and the stronger the regulating effect on the mobile phone temperature is.

[0069] Based on this, the temperature data in the mobile phone temperature subsequence in each time period is used as the input of the extreme point detection algorithm, and the output of the extreme point detection algorithm is used as all extreme points in the mobile phone temperature subsequence in each time period. The extreme point detection algorithm is a well-known technology and the specific process will not be repeated here.

[0070] Based on the above analysis, in this application, the temperature stability of the mobile phone in each time period is determined based on the temperature fluctuation of the temperature data in each time period in the mobile phone temperature sequence, specifically:

[0071] An extreme point detection algorithm is used to obtain the extreme points in the temperature data of each time period in the mobile phone temperature sequence; when the number of extreme points in the temperature data of each time period is less than or equal to the preset value, the temperature stability of the mobile phone in each time period is set to 1; otherwise, the fluctuation of the temperature data of all extreme points in the temperature data of each time period is calculated, the number of extreme points and the fluctuation are fused, and the inverse of the fusion result is used as the temperature stability of the mobile phone in each time period.

[0072] The preset value is 1 in this embodiment, and the implementer can set it according to the specific situation.

[0073] In some embodiments of the present application, when calculating the fluctuation of the temperature data at all extreme points, the mean square error, variance, entropy, etc. of the temperature data at all extreme points can be calculated as the fluctuation of the temperature data at all extreme points, which can be specifically set by the implementer according to the actual situation.

[0074] It can be understood that fusion can be divided into forward fusion and reverse fusion. This embodiment adopts the forward fusion method. Forward fusion is a fusion method such as addition and multiplication between data. The specific forward fusion method is determined by the implementer according to the actual situation. The application does not impose any special restrictions.

[0075] In some embodiments of the present application, the product of the number of extreme points and the fluctuation situation can be used as the fusion result, or the sum of the number of extreme points and the fluctuation situation can be used as the fusion result, which is specifically set by the implementer according to the actual situation.

[0076] This embodiment takes the i-th time period as an example for analysis. When calculating the temperature stability of the mobile phone in the i-th time period, in order to avoid the possibility that the inverse of the fusion result may be 0, a positive number is added when calculating the denominator. In this embodiment, the value is 1.

[0077] It should be understood that the more extreme points there are and the greater the fluctuation, the more times the temperature of the mobile phone fluctuates in the mobile phone temperature subsequence in the time period, and the greater the discreteness of the temperature fluctuation. At this time, the more obvious the change characteristics of the output power of the wireless charging adapter are, that is, the lower the temperature stability of the mobile phone.

[0078] In one embodiment of the present application, a flow chart of a method for determining the temperature stability of a mobile phone in each time period is shown in the attached figure. Figure 4 shown.

[0079] A3, combining the heat dissipation effectiveness value and the temperature stability of the mobile phone, determines the temperature regulation index of the mobile phone in each time period.

[0080] Under normal circumstances, the higher the heat dissipation effect of the wireless charging adapter in a certain period of time, and the lower the stability of the output power of the wireless charging adapter, the stronger the regulation effect on the temperature of the mobile phone during the wireless charging process, and the less likely the temperature of the mobile phone will show the characteristic of continuous increase;

[0081] Based on the above analysis, in this application, the temperature adjustment index of the mobile phone in each time period is determined by combining the heat dissipation effectiveness value and the temperature stability of the mobile phone, specifically:

[0082] The heat dissipation effectiveness value of each time period is integrated with the temperature stability of the mobile phone to obtain the temperature adjustment index of the mobile phone in each time period; wherein the temperature adjustment index of the mobile phone is positively correlated with the heat dissipation effectiveness value and negatively correlated with the temperature stability of the mobile phone.

[0083] It can be understood that fusion can be divided into forward fusion and reverse fusion. This embodiment adopts the reverse fusion method. Reverse fusion is a fusion method such as subtraction and division between data. The specific reverse fusion method is determined by the implementer according to the actual situation. The application does not impose any special restrictions.

[0084] In addition, it can be understood that a positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases; a negative correlation means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. The positive correlation and negative correlation are determined by actual applications, and this application does not impose any special restrictions.

[0085] In this embodiment, the inverse number of the temperature stability of the mobile phone in each time period is used as the exponent of an exponential function with a natural constant as the base, and the product of the calculation result of the exponential function and the heat dissipation effectiveness value of the corresponding time period is used as the temperature adjustment index of the mobile phone in the corresponding time period.

[0086] In another embodiment of the present application, the ratio of the heat dissipation effectiveness value in each time period to the temperature stability of the mobile phone can be used as the temperature adjustment index of the mobile phone in the corresponding time period. The specific acquisition process is set by the implementer based on the actual situation and will not be repeated in this embodiment.

[0087] In other embodiments of the present application, the difference between the heat dissipation effectiveness value and the temperature stability of the mobile phone in each time period can also be used as the temperature adjustment index of the mobile phone in the corresponding time period. The specific acquisition process is set by the implementer based on the actual situation and will not be repeated in this embodiment.

[0088] It should be understood that the greater the heat dissipation effectiveness value and the smaller the temperature stability of the mobile phone, to a certain extent, it means that the regulating effect on the temperature of the mobile phone during the wireless charging process during this time period is stronger, and the greater the temperature regulation index of the mobile phone is.

[0089] A4, the distribution disorder of the mobile phone temperature adjustment index in all time periods is used as the temperature adjustment disorder degree of the mobile phone temperature sequence.

[0090] Generally speaking, the more inconsistent the changes in the temperature adjustment index of the mobile phone in different time periods are, that is, the stronger the chaotic characteristics of the temperature adjustment effect of the mobile phone during the entire time, the larger the smoothing coefficient should be selected when using the cubic exponential smoothing algorithm to predict the mobile phone temperature, so as to improve the response speed to the changes in the mobile phone temperature data, so as to improve the prediction effect of the mobile phone temperature during the wireless charging process.

[0091] Based on the above analysis, in this application, the distribution disorder of the mobile phone temperature adjustment index in all time periods is used as the temperature adjustment disorder degree of the mobile phone temperature sequence.

[0092] In this embodiment, the information entropy of the mobile phone temperature adjustment index in all time periods is used as the temperature adjustment disorder degree of the mobile phone temperature sequence.

[0093] In another embodiment of the present application, the variance of the mobile phone temperature adjustment index in all time periods is used as the temperature adjustment disorder of the mobile phone temperature sequence.

[0094] In other embodiments of the present application, the product of the mean square error of the mobile phone temperature adjustment index in all time periods and the information entropy can also be used as the temperature adjustment disorder degree of the mobile phone temperature sequence.

[0095] It should be understood that the greater the distribution chaos, the worse the consistency of the mobile phone temperature adjustment index during the entire time and the greater the discreteness, which to a certain extent reflects that the stronger the chaotic characteristics of the mobile phone temperature adjustment function, the greater the temperature adjustment chaos.

[0096] A5, combining the temperature regulation chaos and the change difference of the mobile phone temperature regulation index in all adjacent time periods, determines the smooth response coefficient.

[0097] Generally speaking, the greater the change between the temperature adjustment indexes of the mobile phone in adjacent time periods, the greater the degree of change of the mobile phone temperature, and the stronger the chaotic characteristics of the mobile phone temperature adjustment effect. At this time, a larger smoothing coefficient should be selected to improve the response speed to the change of the mobile phone temperature data;

[0098] Based on the above analysis, in this embodiment, the smooth response coefficient is determined by combining the temperature adjustment chaos degree and the change difference of the mobile phone temperature adjustment index in all adjacent time periods, which is specifically:

[0099] Calculate the difference between the temperature adjustment index of the mobile phone in each adjacent time period, and calculate the cumulative sum of the differences in all adjacent time periods; calculate the product of the cumulative sum and the temperature adjustment chaos as the adjustment factor; determine the smooth response coefficient based on the adjustment factor; wherein the adjustment factor is positively correlated with the smooth response coefficient.

[0100] In this embodiment, the absolute value of the difference between the temperature adjustment indexes of the mobile phone in each adjacent time period is used as the difference between the temperature adjustment indexes of the mobile phone in each adjacent time period.

[0101] In this embodiment, the opposite number of the adjustment factor is used as the exponent of an exponential function with the natural constant e as the base, and the difference between the number 1 and the calculation result of the exponential function is used as the smoothing response coefficient.

[0102] In another embodiment of the present application, the normalized value of the adjustment factor is used as the smoothing response coefficient.

[0103] In other embodiments of the present application, the product of the adjustment factor and the preset adjustment parameter factor can also be used as the smoothing response coefficient, wherein the value of the preset adjustment parameter factor is set by the implementer based on the specific actual situation, and is not elaborated in this embodiment.

[0104] It should be understood that the greater the temperature regulation chaos and the greater the difference in the change of the mobile phone temperature regulation index in all adjacent time periods, it means that the change of the mobile phone temperature may fluctuate more frequently in a short period of time when using the wireless charging adapter. The larger the smoothing response coefficient is, the higher the response speed to the change of the mobile phone temperature data when using the cubic exponential smoothing algorithm to predict the mobile phone temperature, and the better the prediction effect of the mobile phone temperature during the wireless charging process.

[0105] In one embodiment of the present application, a flow chart of a method for determining a smooth response coefficient is shown in the attached Figure 5 shown.

[0106] In the third step, the smoothed response coefficient is used as the smoothing coefficient of the cubic exponential smoothing algorithm to obtain the mobile phone temperature prediction result of the mobile phone temperature series.

[0107] The cell phone temperature is predicted using the cubic exponential smoothing algorithm. The cell phone temperature series is used as the input of the cubic exponential smoothing algorithm. The calculated smoothed response coefficient is used as the smoothing coefficient in the cubic exponential smoothing algorithm. The output of the cubic exponential smoothing algorithm is used as the cell phone temperature prediction result. The cubic exponential smoothing algorithm is a well-known technology and the specific process will not be repeated here.

[0108] In one embodiment of the present application, a schematic diagram of the mobile phone temperature prediction result is shown in the attached Figure 6 shown.

[0109] In the attached Figure 6 In the figure, the horizontal axis represents time in seconds, and the vertical axis represents temperature in degrees Celsius. That is, the temperature of the mobile phone changes to a certain extent over time. 1 is the temperature data of the mobile phone collected by the sensor, 2 is several mobile phone temperature data predicted by the cubic exponential smoothing algorithm.

[0110] The predicted temperature data of several mobile phones are used as the mobile phone temperature prediction result.

[0111] In this embodiment, the number of predicted mobile phone temperature data is 20, and the implementer can set the number of predicted values ​​according to actual conditions.

[0112] The fourth step is to adjust the output power of the wireless charging adapter based on the mobile phone temperature prediction result.

[0113] The mobile phone temperature prediction result is sent to the charging power regulation module.

[0114] In the charging power adjustment module, when the mobile phone temperature prediction result contains mobile phone temperature data higher than the preset rated temperature, the output power of the wireless charging adapter during wireless charging is appropriately reduced. In this embodiment, the preset rated temperature is 40°C. That is, when the mobile phone temperature prediction result contains mobile phone temperature data higher than 40°C, the output power of the wireless charging adapter is adjusted to reduce the output power of the wireless charging adapter at the current moment by the preset adjustment power value, thereby adjusting the output power of the wireless charging adapter. In this embodiment, the preset adjustment power value is set to 3W, which can be set by the implementer according to the actual situation.

[0115] Otherwise, the output power of the wireless charging adapter is not adjusted.

[0116] See also Figure 7 , Figure 7is a schematic diagram of the structure of a wireless charging adapter provided in an embodiment of the present application. In this embodiment, the wireless charging adapter includes modules for executing the steps in the embodiment corresponding to the wireless charging method. Figure 7 The wireless charging adapter 70 includes: a wireless charging temperature acquisition module 71, a wireless charging temperature processing module 72, a mobile phone temperature prediction module 73, and a charging power adjustment module 74.

[0117] The wireless charging temperature acquisition module 71 is used to collect the heat sink temperature data and the mobile phone temperature data during the operation of the wireless charging adapter through the temperature sensor to obtain the heat sink temperature sequence and the mobile phone temperature sequence;

[0118] The wireless charging temperature processing module 72 is used to determine the heat dissipation effectiveness value of each time period based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence; determine the temperature stability of the mobile phone in each time period based on the temperature fluctuation of the temperature data of each time period in the mobile phone temperature sequence; determine the temperature adjustment index of the mobile phone in each time period in combination with the heat dissipation effectiveness value and the temperature stability of the mobile phone; use the distribution disorder of the mobile phone temperature adjustment index of all time periods as the temperature adjustment disorder of the mobile phone temperature sequence; determine the smoothing response coefficient in combination with the temperature adjustment disorder and the change difference of the mobile phone temperature adjustment index of all adjacent time periods;

[0119] The mobile phone temperature prediction module 73 is used to use the smoothing response coefficient as the smoothing coefficient of the cubic exponential smoothing algorithm to obtain the mobile phone temperature prediction result of the mobile phone temperature sequence;

[0120] The charging power adjustment module 74 is used to adjust the output power of the wireless charging adapter based on the mobile phone temperature prediction result.

[0121] Based on the same concept as the method embodiment of the present application, a wireless charging device is proposed, which stores a computer program. When the computer program is executed by a processor, a wireless charging method as described in the first aspect is implemented. Its specific functions and technical effects can be found in the method embodiment part, which will not be repeated here.

[0122] Based on the same inventive concept as the above method, an embodiment of the present application also provides a wireless charging system, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned wireless charging methods are implemented.

[0123] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0124] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the sentence "including one..." does not exclude the existence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0125] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not invented by the present application.

[0126] It will be appreciated that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A wireless charging method, characterized in that: The method comprises the following steps: The temperature sensor is used to collect the heat sink temperature data and the mobile phone temperature data during the operation of the wireless charging adapter, and obtain the heat sink temperature sequence and the mobile phone temperature sequence; Based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence, the heat dissipation effectiveness value of each time period is determined; based on the temperature fluctuation of the temperature data of each time period in the mobile phone temperature sequence, the temperature stability of the mobile phone in each time period is determined; combining the heat dissipation effectiveness value and the temperature stability of the mobile phone, the temperature regulation index of the mobile phone in each time period is determined; The distribution disorder of the mobile phone temperature adjustment index in all time periods is used as the temperature adjustment disorder of the mobile phone temperature series; the smoothing response coefficient is determined by combining the temperature adjustment disorder and the change difference of the mobile phone temperature adjustment index in all adjacent time periods; The smoothed response coefficient is used as the smoothing coefficient of the cubic exponential smoothing algorithm to obtain the mobile phone temperature prediction result of the mobile phone temperature series; Adjust the output power of the wireless charging adapter based on the predicted result of the mobile phone temperature; The method for determining the heat dissipation effectiveness value in each time period includes: Differentiate the temperature data of each time period in the heat sink temperature series; Calculate the product of the number of negative elements in the difference value after difference in each time period and the absolute value of the cumulative sum of all negative elements as the numerator; calculate the product of the number of positive elements in the difference value after difference in each time period and the cumulative sum of all positive elements as the denominator; The ratio of the numerator to the denominator is used as the heat dissipation effectiveness value for each time period; The method for determining the temperature stability of the mobile phone in each time period includes: The extreme point detection algorithm is used to obtain the extreme points in the temperature data of each time period in the mobile phone temperature series; When the number of extreme value points in the temperature data of each time period is less than or equal to a preset value, the temperature stability of the mobile phone in each time period is set to 1; On the contrary, the fluctuation of the temperature data of all extreme points in each time period is calculated, the number of extreme points and the fluctuation are fused, and the inverse of the fusion result is used as the temperature stability of the mobile phone in each time period.

2. A wireless charging method as claimed in claim 1, characterized in that: The method for determining the mobile phone temperature adjustment index in each time period includes: The inverse number of the temperature stability of the mobile phone in each time period is used as the exponent of an exponential function with a natural constant as the base, and the product of the calculation result of the exponential function and the heat dissipation effectiveness value of the corresponding time period is used as the temperature adjustment index of the mobile phone in the corresponding time period.

3. A wireless charging method as claimed in claim 2, characterized in that: The temperature adjustment disorder of the mobile phone temperature sequence is the information entropy of the mobile phone temperature adjustment index in all time periods.

4. A wireless charging method as claimed in claim 3, characterized in that: The method for determining the smoothing response coefficient includes: Calculate the difference between the temperature adjustment index of the mobile phone in each adjacent time period, and calculate the cumulative sum of the differences in all adjacent time periods; Calculate the product of the cumulative sum and the temperature regulation disorder as the regulation factor; A smoothing response coefficient is determined based on the adjustment factor; wherein the adjustment factor is positively correlated with the smoothing response coefficient.

5. A wireless charging method as claimed in claim 4, characterized in that: The step of adjusting the output power of the wireless charging adapter based on the mobile phone temperature prediction result includes: When there is mobile phone temperature data higher than the preset rated temperature in the mobile phone temperature prediction result, the output power of the wireless charging adapter is reduced by a preset adjustment power value; otherwise, it is not adjusted.

6. A wireless charging adapter, implementing a wireless charging method as claimed in any one of claims 1 to 5, characterized in that: The wireless charging adapter comprises: The wireless charging temperature acquisition module is used to collect the heat sink temperature data and the mobile phone temperature data during the operation of the wireless charging adapter through the temperature sensor to obtain the heat sink temperature sequence and the mobile phone temperature sequence; The wireless charging temperature processing module is used to determine the heat dissipation effectiveness value of each time period based on the quantitative difference and numerical difference between the positive and negative values ​​in the differential value of the temperature data of each time period in the heat sink temperature sequence; determine the temperature stability of the mobile phone in each time period based on the temperature fluctuation of the temperature data of each time period in the mobile phone temperature sequence; determine the temperature adjustment index of the mobile phone in each time period in combination with the heat dissipation effectiveness value and the temperature stability of the mobile phone; use the distribution disorder of the mobile phone temperature adjustment index of all time periods as the temperature adjustment disorder of the mobile phone temperature sequence; determine the smoothing response coefficient in combination with the temperature adjustment disorder and the change difference of the mobile phone temperature adjustment index of all adjacent time periods; A mobile phone temperature prediction module is used to use the smoothing response coefficient as the smoothing coefficient of the cubic exponential smoothing algorithm to obtain the mobile phone temperature prediction result of the mobile phone temperature sequence; The charging power adjustment module is used to adjust the output power of the wireless charging adapter based on the mobile phone temperature prediction result.

7. A wireless charging device, wherein a computer program is stored in the wireless charging device, characterized in that: When the computer program is executed by a processor, the steps of a wireless charging method as described in any one of claims 1 to 5 are implemented.

8. A wireless charging system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the wireless charging method as described in any one of claims 1 to 5 are implemented.

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