WO2018152990A1

WO2018152990A1 - Method for determining component power consumption of electronic device, electronic device and storage media

Info

Publication number: WO2018152990A1
Application number: PCT/CN2017/089169
Authority: WO
Inventors: 杨俊�; 孔峥嵘; 周越海
Original assignee: 华为技术有限公司
Priority date: 2017-02-24
Filing date: 2017-06-20
Publication date: 2018-08-30
Also published as: CN108886548A; CN108886548B

Abstract

A method for determining the component power consumption of an electronic device and an electronic device, comprising: determining a power curve of an electronic device within a set time length, and determining m power models of N components in the electronic device, respectively; according to the power curve of the electronic device within the set time length and the m power models, determining the power consumption of each component within the set time length. The accuracy in determining the power consumption of a component may be improved.

Description

Method, electronic device and storage medium for determining device power consumption of electronic device

Technical field

The present application relates to the field of terminal technologies, and in particular, to a method, an electronic device, and a storage medium for determining power consumption of a device of an electronic device.

Background technique

With the development of technology in the field of terminals, more and more devices are integrated in electronic devices, and the heat generation problem of electronic devices has become an important factor affecting the user experience.

In order to alleviate the heating problem of electronic devices, it is first necessary to determine the power consumption of each device in the electronic device. The existing method for determining the power consumption of each device in the electronic device is that the controller in each device can estimate the current power consumption of the device according to the current clock frequency and the operation mode, and the electronic device can read the device through the software interface. Power consumption. However, this method is only applicable to some devices with controllers, and is not applicable to some devices with controllers (such as RF circuits, displays, etc.) and devices without controllers.

In summary, there is a need for a way to determine the power consumption of a device of an electronic device, thereby improving the accuracy of the results in determining the power consumption of each device in the electronic device.

Summary of the invention

Embodiments of the present application provide a method, an electronic device, and a storage medium for determining power consumption of a device of an electronic device, to accurately determine power consumption of each device in the electronic device.

In a first aspect, a method for determining power consumption of a device of an electronic device is provided, comprising: determining a power curve of the electronic device for a set duration, and determining N devices in the electronic device, respectively m power models, the m power models are used to indicate the frequency domain characteristics of the power of each of the N devices in the M _i use scenarios, N≥1, i=1～N,

And determining, according to the power curve of the electronic device within the set duration and the m power models, power consumption of each device within the set duration. Through the above method, since the m power models are used to indicate the frequency domain characteristics of the power of each of the N devices in the M _i use scenarios, according to the power curve of the terminal device within the set duration and m The power model determines the average power of each device in each usage scenario of the device to determine the power consumption of the device for a set period of time. When the above method is used to determine the power consumption of the device, there is no possibility that the prior art is not applicable to some devices. Since the above method can instantly collect and calculate the power curve within the set duration during the use of the terminal device, the power consumption of each device determined by the method can accurately reflect the current power consumption of the device, which is related to the prior art. Than, you can improve the accuracy of the results. After accurately determining the power consumption of each device, the user can be reminded to perform corresponding processing or automatically perform corresponding processing when a certain device consumes a large amount of power, thereby reducing the power consumption of the terminal device.

In an optional implementation manner, determining a power curve of the electronic device within a set duration includes: determining a first spectral feature of the power of the electronic device within the set duration and the electronic device a first average power within the set duration; determining m power models of the N devices in the electronic device, respectively, comprising: determining m second spectral features of the N devices and m first the average power of two, said m second frequency spectrum m second feature and the one-average power, wherein said m second frequency spectrum of the N devices in each device, respectively, using m _i th The spectral characteristics of the power in the scene, the m second average powers being an average of the powers of each of the N devices in the M _i use scenarios. Wherein the m second spectral features are in one-to-one correspondence with the m second average powers, and the m second spectral features are spectral features of the power of each of the N devices in the M _i use scenarios, m The second average power is the average of the power of each of the N devices in the M _i use scenarios.

That is, the power curve of the terminal device within the set duration may be characterized by the first spectral feature and the first average power; the m power models may be respectively composed of m second spectral features and one m second spectral features A corresponding m second average power is characterized.

The spectral characteristics can be determined by performing Fourier transform or wavelet transform on the time domain signal. For example, the first spectral feature can be obtained by performing Fourier transform or wavelet transform on the power of the terminal device within the set duration, and m second can be obtained by performing Fourier transform or wavelet transform on the m power models respectively. Spectrum characteristics.

In an optional implementation manner, determining, according to the power curve of the electronic device within the set duration and the m power models, determining power consumption of each device during the set duration, including: Determining, by the first spectral feature, the first average power, the m second spectral features, and the m second average powers, m power coefficients of the N devices, the m power coefficients Each of the power coefficients is used to indicate a ratio of an average power of the device in the usage scenario to a second average power over the set duration; according to the m power coefficients and the m second average powers Determining m average powers of the N devices; for each device: adding powers of the devices in the M _i usage scenarios of the m average powers respectively, to obtain the device in the setting Average power over time. By this method, since each of the m power coefficients is used to indicate the ratio of the average power of the device in the usage scenario to the second average power over a set duration, m power coefficients are respectively associated with m The second average power is multiplied to obtain m average powers. The average power of each of the obtained m average powers represents the average power of a certain device in a certain usage scenario. Then, the average power of a device in all its usage scenarios is added to obtain the device. The average power over the set length of time.

In an optional implementation manner, determining, according to the first spectral feature, the first average power, the m second spectral features, and the m second average powers, m of the N devices And determining, according to the first spectral feature and the m second spectral features, a proportion of each of the second spectral features in the first spectral feature; And determining, by the first average power and the m second average powers, a normalization coefficient; multiplying the ratio and the normalization coefficient to obtain the power coefficient.

In an optional implementation manner, the first spectral feature and the m second spectral features are represented by the same group of bases. By the above method, since the first spectral feature and the m second spectral features are expressed based on the same set of bases, each second spectral feature is determined in the first spectral feature according to the first spectral feature and the m second spectral features. It is easier to calculate and implement when it is accounted for.

In an optional implementation manner, the ratio is solved as follows:

Wherein F is the first spectral feature, F _i is the m second spectral features, and f _j is a base of the first spectral feature and the m second spectral features, b _j and a _ij respectively The coefficient of the first spectral feature and the m second spectral features under the substrate, x _i is the ratio.

In an optional implementation manner, the normalization coefficient is solved in the following manner:

Where P is the first average power, P _i is the m second average powers, and k is the normalization coefficient.

In a second aspect, an electronic device is provided, comprising: one or more processors; a memory; a plurality of applications; and one or more programs, wherein the one or more programs are stored in the memory, The one or more programs include instructions that, when executed by the electronic device, cause the electronic device to implement the various steps of the first aspect and the first aspect described above. For the implementation of the electronic device to solve the problem and the beneficial effects, refer to the first aspect and the possible implementation manners of the first aspect and the beneficial effects. Therefore, the implementation of the electronic device can refer to the first aspect and the foregoing The implementation of possible implementations on the one hand is not repeated here.

In a third aspect, a computer readable storage medium is provided, comprising instructions, wherein when the instructions are run on an electronic device, the electronic device is caused to perform any of the first aspect and the first aspect described above Methods. Based on the same inventive concept, the repetition will not be described again.

A fourth aspect provides an electronic device, including: a first determining unit, a second determining unit, and a third determining unit; the first determining unit, configured to determine power of the electronic device within a set duration a second determining unit, configured to respectively determine m power models of N devices in the electronic device, where the m power models are used to indicate that each of the N devices is respectively at M Frequency domain characteristics of power in _i use scenarios, N≥1, i=1～N,

The third determining unit is configured to determine, according to the power curve of the electronic device within the set duration and the m power models, power consumption of each device within the set duration. Based on the same inventive concept, the principles and benefits of the electronic device can be solved by referring to the first aspect and the possible implementation manners of the first aspect and the beneficial effects. Therefore, the implementation of the electronic device can be referred to the above. The implementation of the various possible implementations of the first aspect and the repetitive aspects will not be described again.

DRAWINGS

FIG. 1 is a schematic flowchart of a method for determining power consumption of a device of an electronic device according to an embodiment of the present disclosure;

2 is a block diagram showing a partial structure of a mobile phone 100 according to an embodiment of the present invention;

FIG. 3 is an electronic device according to an embodiment of the present application.

detailed description

As more and more devices are integrated in electronic devices, the power consumption and heat generation of electronic devices become an important factor affecting the user experience. Therefore, how to accurately determine the power consumption of each device in the electronic device and inform the user to become an urgent problem to be solved.

In the prior art, the method for determining the power consumption of each device in the electronic device is: for a device with a controller in the electronic device, the controller generally presets a power consumption model, and the controller can be based on the current clock frequency and the operation mode. Estimating the current power consumption of the device, the electronic device can read the power consumption of the device through a software interface; for the electronic device without a controller The device needs to be determined by the separation test method, that is, a device is separately powered and the power consumption data is sampled. In the above method, when determining the power consumption of the device with the controller, it is only applicable to some devices with controllers, and is not applicable to some devices with controllers; when determining the power consumption of devices without controllers, Since the separation test requires professional equipment, it cannot be completed by the user in the electronic device, which causes great inconvenience.

Therefore, embodiments of the present application provide a method, an electronic device, and a storage medium for determining power consumption of a device of an electronic device, to accurately determine power consumption of each device in the electronic device. The method and the electronic device are based on the same inventive concept. Since the principles of the method and the electronic device are similar, the implementation of the electronic device and the method can be referred to each other, and the repeated description is not repeated.

In the embodiment of the present application, the electronic device includes but is not limited to a smart phone, a smart watch, a tablet computer, a virtual reality (VR) device, an augmented reality (AR) device, a personal computer, a handheld computer, and a personal number. assistant Manager.

In order to make the objects, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the accompanying drawings.

It should be understood that in the description of the present application, the terms "first", "second" and the like are used to distinguish the purpose of the description, and are not to be construed as indicating or implying relative importance, nor as indicating or implying. order.

1 is a schematic flowchart of a method for determining power consumption of a device of an electronic device according to an embodiment of the present application. The method comprises the following steps:

S101: Determine a frequency domain characteristic of the power of the electronic device within a set duration, and determine m power models of the N devices in the electronic device, respectively.

Wherein, the m power models are used to indicate the frequency domain characteristics of the power of each of the N devices in the M _i use scenarios, N≥1, i=1～N,

In S101, the N devices in the electronic device include, but are not limited to, a display, a Global Positioning System (GPS), a radio frequency circuit, a camera, an audio circuit, and the like; the usage scenario may be a call scene, a webpage scene, or a screen scene. , game scenes, etc. In the embodiment of the present application, each of the N devices in the electronic device corresponds to a typical usage scenario of M _i (i=1～N), that is, device 1 in the N devices corresponds to M ₁ use scenarios. Device 2 in N devices corresponds to M ₂ usage scenarios, device 3 in N devices corresponds to M ₃ usage scenarios... and so on. Therefore, the m power models represent the power models of each device in at least one usage scenario of the device, and one of the m power models can be used to indicate the frequency domain characteristics of a certain device in a certain usage scenario. .

For example, N devices are two devices: display screen and GPS. The display screen corresponds to three usage scenarios of call, interest screen and game. GPS uses map navigation and unused map navigation. Then, the m power models are respectively the power model of the display screen in the call scene, the power model of the display screen in the interest screen scene, the power model of the display screen in the game scene, the power model of the GPS using the map navigation scene, and The five power models of the power model of GPS under the map navigation scene are not used.

It should be noted that the respective usage scenarios of the different devices in the electronic device may be completely different, may be identical, or may be partially the same, which is not limited in the embodiment of the present application. For example, for device 1 and device 2 in an electronic device, the respective usage scenarios can be as follows:

First case

Device 1 corresponds to three usage scenarios A, B, and C, and device 2 corresponds to four usage scenarios of D, E, F, and G.

Second case

Device 1 corresponds to three usage scenarios of A, B, and C, and device 2 corresponds to three usage scenarios of A, B, and C.

Third case

Device 1 corresponds to three usage scenarios of A, B, and C, and device 2 corresponds to two usage scenarios of C and D.

It should be noted that the number of the usage scenarios of the different devices in the electronic device may be the same or different, which is not limited in the embodiment of the present application. The device 1 and the device 2 are still taken as an example. When the number of usage scenarios of the device 1 is 2, the number of usage scenarios corresponding to the device 2 may be 2 or not 2.

In S101, the power curve of the electronic device during the set time period can be obtained by performing AD sampling on the power data of the electronic device within a set time period, that is, the power curve of the electronic device within the set time period and the collected power data. Time related. Assuming that the set duration is 5 minutes, the power curve of the electronic device during the period from 18:00 to 18:05 is different from the power curve of the electronic device during the period of 18:05 to 18:10. Accordingly, the power model is an inherent feature of the power of a device in a certain usage scenario, regardless of the time of AD sampling.

S102: Determine power consumption of each device for a set duration according to a power curve of the electronic device within a set duration and m power models.

In S102, according to the power curve of the electronic device in the set duration and the m power models, the average power corresponding to each power model can be determined, and the average power corresponding to each power model represents a device in a use scenario. Average power. Then, for a device in an electronic device, the average power of the device for a set period of time is equal to the sum of the average power of the device in each usage scenario of the device, and the power consumption of the device for a set period of time. Equal to the integration of the average power of the device over the set duration to the set duration.

In S101, it is necessary to determine a power curve of the electronic device within a set time period and the above m power models. The determining the power curve of the electronic device for a set period of time may be specifically implemented by: determining a first spectral feature of the power of the electronic device within a set duration and a first average power of the electronic device within a set duration; Determining the m power models may be implemented by: respectively determining m second spectral features of the N devices and m second average powers corresponding to the m second spectral features, m second spectral features The spectral characteristics of the power in the M _i use scenarios for each of the N devices, the m second average power being the average of the power of each of the N devices in the M _i use scenarios value.

That is, the power curve of the electronic device during the set duration may be characterized by the first spectral feature and the first average power; the m power models may be respectively composed of m second spectral features and one of the m second spectral features A corresponding m second average power is characterized.

The spectral features may indicate the frequency components that make up the signal and the size of each frequency component. The spectral characteristics can be determined by performing Fourier transform or wavelet transform on the time domain signal. For example, the first spectral feature can be obtained by performing Fourier transform or wavelet transform on the power of the electronic device within a set duration, and m second can be obtained by performing Fourier transform or wavelet transform on the m power models respectively. Spectrum characteristics.

Among them, the Fourier transform of the original signal can be used to fit the original signal with the sum of trigonometric functions of different frequencies, and the principle of wavelet transform is similar to the Fourier transform, except that the base of the wavelet transform is not a trigonometric function, but A set of wavelet bases. The wavelet base needs to satisfy the following two conditions: 1. The mean value of the wavelet base is 0; 2. The wavelet base has localized features in both the time domain and the frequency domain (ie, does not spread to the entire coordinate axis). The wavelet transform can be used to represent the original signal as a linear combination of a set of wavelet bases, allowing multi-scale analysis of the original signal.

When the power curve of the electronic device within the set duration and the m power models are determined in the above manner in S101, the power consumption of each device in the set duration may be further determined in S102 by: according to the first spectrum a feature, a first average power, m second spectral features, and m second average powers, determining m power coefficients of the N devices, each of the m power coefficients being used to indicate that within the set time period The ratio of the average power of the device in the usage scenario to the second average power; determining m average powers of the N devices based on the m power coefficients and the m second average powers; then, performing the following operations for each device: m in an average power in the average power of the device, respectively, under a usage scenarios m _i is added to obtain the average power of the device within the set duration.

It is assumed that N devices in the electronic device are device 1 and device 2, device 1 corresponds to three usage scenarios of A, B, and C, and device 2 corresponds to two usage scenarios of B and D. Then, the m power models are the power model of the device 1 under the use scenario A, the power model of the device 1 under the use scenario B, the power model of the device 1 under the use scenario C, and the power model of the device 2 under the use scenario B. And the power model of the device 2 in the use scenario D; the first spectrum feature is F, the first average power is P, the m second spectrum features are F1 to F5, and the m second average powers are respectively P1 to P5. Then, five power coefficients a1, a2, a3, a4, and a5 can be determined according to F, P, F1 to F5, and P1 to P5. Where a1 is used to indicate the ratio of the average power of the device 1 under the use scenario A to A1, a2 is used to indicate the ratio of the average power of the device 1 under the use scenario B to A2, and a3 is used to indicate that the device 1 is in use scenario C. The ratio of the average power to A3 below, a4 is used to indicate the ratio of the average power of device 2 under use scenario B to A4, and a5 is used to indicate the ratio of the average power of device 2 to scene A using scene D. Five average power values q1, q2, q3, q4, and q5 can be determined based on the above five power coefficients and A1 to A5. Where q1 is the average power of the device 1 under the use scenario A within the set duration, q2 is the average power of the device 1 under the use scenario B within the set duration, and q3 is the set duration of the device 1 under the use scenario C The average power, q4 is the average power of the device 2 under the use scenario B within the set duration, and q5 is the average power of the device 2 under the use scenario D for the set duration. By integrating the sum of q1, q2, and q3 with the set duration, the power consumption of the device 1 for the set duration can be obtained, and the sum of q4 and q5 can be integrated for the set duration to obtain the work of the device 2 for the set duration. Consumption.

According to the above scheme, since each of the m power coefficients is used to indicate the ratio of the average power of the device in the use scenario to the second average power within a set duration, the m power coefficients are respectively associated with m The second average power is multiplied to obtain m average powers. The average power of each of the obtained m average powers represents the average power of a certain device in a certain usage scenario. Then, the average power of a device in all its usage scenarios is added to obtain the device. The average power over the set length of time.

Further, a specific implementation manner of determining the m power coefficients may be: determining, according to the first spectral feature and the m second spectral features, a proportion of each second spectral feature in the first spectral feature; The m proportions, the first average power, and the m second average powers determine a normalization coefficient; and the m ratios are respectively multiplied by the normalization coefficients to obtain the m power coefficients.

Since each of the m second spectral features represents a spectral characteristic of the power of a certain device in a certain usage scenario, the duration of the device going through the usage scenario may be only a part of the set duration. The time period, therefore, the power consumption of the device for a set period of time cannot be directly integrated by the second average power for the set duration. Therefore, the proportion of each of the second second spectral features in the first spectral feature may be determined first, thereby determining the return according to the m ratio, the first average power, and the m second average powers. A coefficient of multiplication, multiplying the above m proportions and the normalization coefficient to obtain m power coefficients. The power factor of a device in a certain usage scenario indicates the ratio of the average power of the device in the usage scenario to the second average power over a set period of time.

Wherein, the normalization coefficient is a fixed value within the set duration. That is to say, the normalization coefficient changes when the power consumption of each device in the electronic device is determined to be determined in different time periods.

As mentioned before, both the first spectral feature and the second spectral feature can be obtained by Fourier transform or wavelet transform. When performing a Fourier transform or a wavelet transform, the first spectral feature and the m second spectral features may use the same set of base tables. Show. Thus, since the first spectral feature and the m second spectral features are expressed based on the same set of bases, it is easier to calculate and implement when determining the above ratio based on the first spectral feature and the m second spectral features.

Taking the same set of wavelet bases f ₁ , f ₂ . . . f _n as the first spectral feature and the m second spectral features, then each second spectral feature is in the first spectral feature. The ratio can be solved as follows:

Where F is the first spectral feature, F _i is m second spectral features, b _j and a _ij are coefficients of the first spectral feature and m second spectral features respectively under the base, and x _i is the ratio.

Further, the normalization coefficient can be solved as follows:

Where P is the first average power, P _i is m second average power, and k is a normalization coefficient.

Using the method for determining the power consumption of the device of the electronic device shown in FIG. 1, since the m power models are used to indicate the frequency domain characteristics of the power of each of the N devices in the M _i use scenarios, The power curve of the device over a set period of time and the m power models determine the average power of each device in each usage scenario of the device to determine the power consumption of the device for a set period of time. When the power consumption of the device is determined by the method shown in FIG. 1, there is no possibility that the prior art does not apply to some devices. Since the method shown in FIG. 1 can instantaneously collect and calculate the power curve within the set duration during the use of the electronic device, the power consumption of each device determined by the method can accurately reflect the current power consumption of the device, and Compared with technology, the accuracy of the results can be improved. After accurately determining the power consumption of each device, the user can be reminded to perform corresponding processing or automatically perform corresponding processing when the power consumption of a certain device is large, thereby reducing the power consumption of the electronic device.

In a specific implementation, the triggering conditions for performing the method shown in FIG. 1 include but are not limited to:

1. The electronic device is seriously heated: when the electronic device is hot, the user triggers or the electronic device automatically triggers the method shown in Figure 1 to detect the power consumption of each device in the electronic device, thereby alerting the user when the power consumption of a device is large. Perform corresponding processing or automatically perform corresponding processing (such as performing power reduction operation or shutdown operation), thereby reducing power consumption of electronic devices, reducing heat generation of electronic devices, and avoiding malfunction of electronic devices due to abnormal power consumption of a certain device. . For example, when the electronic device is hot, the power consumption of each device in the electronic device is determined by performing the method shown in FIG. 1 on a central processing unit (CPU) or a liquid crystal display (LCD). When the power consumption is large, the user may be prompted to perform a frequency reduction operation on the CPU or the LCD, or automatically turn off the GPS when the power consumption data of the GPS is abnormal, thereby avoiding the power consumption abnormality of the GPS and causing the electronic device to malfunction.

2. The usage scene of the electronic device changes: for example, the electronic device is switched from the standby scene to the call scene, and the game scene is switched to the camera scene. When the usage scenario of the electronic device changes, the power consumption of each device in the electronic device may also change. At this time, the power consumption of each device in the electronic device may be determined by performing the method shown in FIG. The power consumption of each device in the device changes, and the devices with abnormal power consumption are processed accordingly.

In addition, the method shown in FIG. 1 can also be applied to the development process of electronic devices, such as real-time analysis of the power consumption of each device during the development of electronic devices, thereby helping developers to optimize the energy consumption of electronic devices.

Based on the above embodiments, the present application also provides a method for determining power consumption of a device of an electronic device, which may be regarded as a specific example of the method shown in FIG. 1. The method comprises the following steps:

1. Select a set of wavelet bases f ₁ , f ₂ ... f _n .

Among them, the wavelet bases f ₁ , f ₂ ... f _n are a family of functions, and the mean of this family of functions is 0 and exhibits localized features in both the time domain and the frequency domain. There are many types of wavelet bases, which can be selected according to engineering scenarios and requirements. The type of the wavelet bases f ₁ , f ₂ . . . f _n is not limited in the embodiment of the present application, and may be, for example, a Haar Wavelet.

2, the sampling frequency curve of each device in electronic equipment in all usage scenarios of the device to obtain m frequency curve F ₁ ~ F _m, and F ₁ ~ F _m calculates an average power value P ₁ ~ P _m.

Wherein, F ₁ to F _m are specific examples of m second characteristic spectra in the method shown in FIG. 1, and P ₁ to P _m are specific examples of m second average powers in the method shown in FIG. 1 .

3. Wavelet analysis is performed on F ₁ to F _m respectively, that is, F ₁ to F _m are respectively decomposed into a combination of wavelet bases f ₁ , f ₂ ... f _n , respectively, and coefficients a _ij can be obtained respectively, where i= 1 to m, j = 1 to n.

4. When the power consumption of the electronic device exceeds a certain threshold, the power sampling is triggered, and the power curve F of the electronic device within the set duration is obtained, and the corresponding average power value P is calculated.

Wherein, F is a specific example of the first characteristic spectrum in the method shown in FIG. 1, and P is a specific example of the first average power in the method shown in FIG. 1.

5. Perform wavelet analysis on F, that is, F is also decomposed into a combination of wavelet bases f ₁ , f ₂ ... f _n , and coefficients b _j , j=1 to n can be obtained respectively.

6, due to

It is thus possible to determine the proportion x _{i of} each second spectral feature in the first spectral feature.

7, due to

Thus, the normalization coefficient k can be determined.

8. Multiplying the ratio x _{i by the} normalized k coefficient to obtain m power coefficients k*x _i .

9. Multiplying m power coefficients k*x _i and m second average powers respectively to obtain m average power values, and each of the m average power values represents a certain set time duration. The average power of the device under a certain usage scenario.

10. Add the average power of a device in all its usage scenarios to get the average power of the device for a set period of time. Then, integrate the average power of the device over the set duration for the set duration. You can get the power consumption of the device for a set period of time.

11. By performing step 10 on all devices in the electronic device, the power consumption of each device in the electronic device for a set period of time can be obtained.

The embodiment of the present invention further provides an electronic device. In some embodiments, the electronic device may be a portable electronic device such as a mobile phone, or may be a tablet, a PDA (Personal Digital Assistant), or a POS (Point of Sales, sales terminal, communication computer with headset interface, etc. For convenience of description, the embodiment of the present invention exemplifies a mobile phone as an example.

FIG. 2 is a block diagram of a partial structure of a mobile phone 100 according to an embodiment of the present invention. As shown in FIG. 2, the mobile phone 100 can include a display screen 140, a memory 120, a processor 180, an antenna 104, a radio frequency circuit 110, a positioning module 195, a sensor 150, other input devices 130, an I/O subsystem 170, and an audio circuit 160. , power supply 190, headphone interface 200 and other components. Field The skilled person can understand that the structure of the mobile phone shown in FIG. 2 does not constitute a limitation on the mobile phone, and may include more or less components than those illustrated, or combine some components, or split some components, or different. Assembly of parts.

The display screen 140 can be used to display information input by the user or information provided to the user as well as various menus of the mobile phone 100, and can also accept user input. The specific display screen 140 may include a display panel 141 and a touch panel 142. The display panel 141 can be configured by using an LCD (Liquid Crystal Display), an OLED (Organic Light-Emitting Diode), or the like. The touch panel 142, also referred to as a touch screen, a touch sensitive screen, etc., can collect contact or non-contact operations on or near the user (such as the user using any suitable object such as a finger, a stylus, or the like on or near the touch panel 142). Or the operation in the vicinity of the touch panel 142 may also include a somatosensory operation; the operation includes a single-point control operation, a multi-point control operation, and the like, and drives the corresponding connected electronic device according to a preset program. Optionally, the touch panel 142 can include two parts: a touch detection electronic device and a touch controller. Wherein, the touch detection electronic device detects the touch orientation and posture of the user, and detects a signal brought by the touch operation, and transmits a signal to the touch controller; the touch controller receives the touch information from the touch detection electronic device, and converts it into a processing. The information that the device can process is sent to the processor 180 and can receive commands from the processor 180 and execute them. In addition, the touch panel 142 can be implemented by using various types such as resistive, capacitive, infrared, and surface acoustic waves, and the touch panel 142 can be implemented by any technology developed in the future. Further, the touch panel 142 can cover the display panel 141, and the user can display the content according to the display panel 141 (the display content includes, but is not limited to, a soft keyboard, a virtual mouse, a virtual button, an icon, etc.) on the display panel 141. Operation is performed on or near the covered touch panel 142. After detecting the operation thereon or nearby, the touch panel 142 transmits to the processor 180 through the I/O subsystem 170 to determine user input, and then the processor 180 according to the user The input provides a corresponding visual output on display panel 141 via I/O subsystem 170. The touch panel 142 and the display panel 141 can function as two independent components to implement the input and input functions of the mobile phone 100. However, in some embodiments, the touch panel 142 can be integrated with the display panel 141 to implement the input of the mobile phone 100. And output function.

The handset 100 can also include a memory 120 for storing computer executable program code, the program code including instructions. The processor 180 executes various functional applications and data processing of the mobile phone 100 by executing instructions stored in the memory 120. The memory 120 may mainly include a storage program area and a storage data area. The storage program area can store an operating system, an application required for at least one function (such as a sound playing function, an image playing function, etc.). The storage data area can store data (such as audio data, phone book, etc.) created according to the use of the mobile phone 100. Moreover, memory 120 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The handset 100 can also include a processor 180. The processor 180 is a control center of the mobile phone 100. Connect the various parts of the entire phone with a variety of interfaces and lines. The various functions and processing data of the handset 100 are performed by running or executing software programs and/or modules stored in the memory 120, as well as recalling data stored in the memory 120, thereby providing overall monitoring of the handset. Alternatively, processor 180 may include one or more processing units. The processor 180 can integrate an application processor, a modem processor, a baseband module, a power management chip, a memory, a codec, and the like. Among them, the application processor mainly deals with operating systems, user interfaces, applications, and the like. The modem processor primarily handles wireless communications. It can be understood that the above modem processor may not be integrated into the processor 180. The Internet Protocol, Wireless Local Area Network Protocol (e.g., IEEE 702.11), 3G, 4G, 5G communication protocols, etc., can be implemented using the processor 180 and the memory 120.

The handset 100 can also include an antenna 104 for transmitting and receiving radio frequency signals. The antenna 104 can be located anywhere in the handset 100. The position of the antenna illustrated in the embodiment of the present invention is merely an exemplary illustration. Cell phone 100 can have one or more antennas. Each antenna in handset 100 can be used to cover a single or multiple communication bands.

The handset 100 also includes a radio frequency circuit 110. Used to receive and send signals during sending or receiving information or during a call. For example, after receiving the downlink information of the base station, it is sent to the processor 180 for processing. In addition, the uplink data is transmitted to the base station. Generally, the radio frequency circuit 110 includes at least one power amplifier 109, a transceiver 108, a coupler, an LNA (Low Noise Amplifier), a duplexer, and the like. In addition, the radio frequency circuit 110 can also communicate with the network and other devices through wireless communication. The wireless communication may use any communication standard or protocol, including but not limited to GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA (Code Division Multiple Access). , Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), e-mail, SMS (Short Messaging Service), and the like.

The handset 100 can also include a power amplifier 109 for amplifying the radio frequency signals to be transmitted by the handset 100. Power amplifier 109 can be implemented using one or more gain stages in one or more integrated circuits, as shown in FIG. It will be appreciated that there may be a plurality of power amplifiers 109, each associated with a communication band or a group of communication bands. To simplify the description, FIG. 2 is schematically illustrated by a single power amplifier 109 symbol.

Optionally, the mobile phone 100 may further include a positioning module 195. The positioning module is configured to detect the position, orientation, and the like of the mobile phone 100. Detection of the location or orientation of the handset 100 can be performed using various positioning services, such as Global Positioning System (GPS), Assisted GPS (A-GPS), cellular based on registered cellular telephones. Telephone base station triangulation or trilateration, Galileo positioning system, or other positioning or location services or technologies. Various hardware, software, and combinations thereof can be used to detect the location or orientation of the handset 100, such as GPS units, accelerometers, and other orientation and motion detection services or technologies in the handset 100.

The handset 100 can also include a sensor 150, which can include a proximity sensor, an ambient light sensor, an accelerometer sensor, and the like. Wherein, the ambient light sensor can adjust the brightness of the display panel 141 according to the brightness of the ambient light, and the proximity sensor can close the display panel 141 and/or the backlight when the mobile phone 100 moves to the ear.

Proximity sensors can include, for example, light emitting diodes (LEDs) and associated photodetectors, such as photodiodes. The light emitting diode may be an infrared light emitting diode that emits infrared light through the light emitting diode. Photodiodes are used to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object in the vicinity of the mobile phone 100. When insufficient reflected light is detected, it can be determined that there is no object near the mobile phone 100.

The ambient light sensor can be a photodiode or other light sensor capable of detecting incoming light. Ambient light sensors can operate in the visible and/or infrared spectrum. When the ambient light sensor is not obscured by the object, the ambient light sensor will typically receive more light 13 than when the ambient light sensor is blocked by the object, so ambient light sensors can be used to generate proximity data. This data can be used alone or in combination with proximity data from other sensors so that the handset 100 can more accurately determine if there are objects near the handset.

Accelerometer sensors detect the magnitude of acceleration in all directions (typically three axes). The magnitude and direction of gravity can be detected when the handset 100 is stationary. The accelerometer sensor can be used to identify the gesture of the phone (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tap). Can use plus The speedometer determines if the handset 100 is in motion (possibly held by the user), or if the handset 100 is being held by the user such that its left or right edge is facing down, or if the handset 100 is being placed horizontally on the desktop. If it is determined that the handset 100 is horizontal and stationary, it can be determined that the handset 100 is less likely to be held. This data can be combined with data from proximity sensors and other data to assist in determining whether the readings obtained from other sensors in the handset 100 are accurate.

The mobile phone 100 can process signals from a plurality of sensor devices (eg, proximity sensors, ambient light sensors, etc.) in parallel, determine whether there is an object in the vicinity of the mobile phone 100, and improve the accuracy of determining the distance between the mobile phone 100 and the object.

Other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, and the like that can be configured in the mobile phone 100 will not be described herein.

Other input devices 130 can be used to receive input numeric or character information, as well as generate key signal inputs related to user settings and function controls of the handset 100. Specifically, other input devices 130 may include, but are not limited to, a physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, and light mice (the light mouse is not sensitive to display visual output). One or more of a surface, or an extension of a touch sensitive surface formed by a touch screen. Other input devices 130 are coupled to other input device controllers 171 of I/O subsystem 170 for signal interaction with processor 180 under the control of other device input controllers 171.

The audio circuit 160, the speaker 161, and the microphone 162 can provide an audio interface between the user and the handset 100. The audio circuit 160 can transmit the converted audio data to the speaker 161 for conversion to the sound signal output by the speaker 161. On the other hand, the microphone 162 converts the collected sound signal into a signal, which is received by the audio circuit 160 and then converted into audio data, and then the audio data is output to the radio frequency circuit 110 for transmission to, for example, another mobile phone, or the audio data is output to the memory. 120 for further processing.

The user can insert the earphone into the earphone interface 200, and the pin of the earphone interface 200 is connected with the earphone, and the microphone of the earphone and the left and right channel earpieces can provide an audio interface between the user and the mobile phone 100. The audio circuit 160 can transmit the converted audio data signal to the left and right channel earpieces of the earphone for conversion to a sound signal output. On the other hand, the microphone of the earphone converts the collected sound signal into an electrical signal, and the electrical signal is transmitted to the audio circuit 160 through the headphone interface, and then converted into audio data for further processing.

The I/O subsystem 170 is used to control external devices for input and output, and may include other device input controllers 171, sensor controllers 172, and display controllers 173. Optionally, one or more other input control device controllers 171 receive signals from other input devices 130 and/or send signals to other input devices 130. Other input devices 130 may include physical buttons (press buttons, rocker buttons, etc.) , dial, slide switch, joystick, click wheel, light mouse (light mouse is a touch-sensitive surface that does not display visual output, or an extension of a touch-sensitive surface formed by a touch screen). It is worth noting that other input control device controllers 171 can be connected to any one or more of the above devices. Display controller 173 in I/O subsystem 170 receives signals from display 140 and/or transmits signals to display 140. After the display 140 detects the user input, the display controller 173 converts the detected user input into an interaction with the user interface object displayed on the display screen 140, ie, implements human-computer interaction. Sensor controller 172 can receive signals from one or more sensors 150 and/or send signals to one or more sensors 150.

The handset 100 also includes a power source 190 (such as a battery) that powers the various components. Preferably, the power source can be logically coupled to the processor 180 through the power management system to manage functions such as charging, discharging, and power consumption through the power management system.

Although not shown, the mobile phone 100 may further include a camera, a Bluetooth module, and the like, and details are not described herein.

An embodiment of the present invention further provides an electronic device, as shown in FIG. 3;

Figure 3 is an electronic device according to an embodiment of the present application, including a first determining unit 301, a second determining unit 302, and a third determining unit 303;

The first determining unit 301 is configured to determine a power curve of the electronic device within a set duration; based on the same inventive concept, the first determining unit determines an implementation manner of the power curve of the electronic device within a set duration: The relevant descriptions in the examples, repetitions, will not be described again.

The second determination unit 302 determines respectively for the m power model of the electronic apparatus of the N devices, the m indicating the power model for each of the N devices in each device usage scenarios M _i th Frequency domain characteristics of the power under, N≥1, i=1~N,

Based on the same inventive concept, the implementation of the m power models of the N devices in the electronic device may be referred to the related description in the method embodiments, and the details are not described again.

The third determining unit 303 is configured to determine, according to the power curve of the electronic device within the set duration and the m power models, power consumption of each device within the set duration. Based on the same inventive concept, the third determining unit determines the power consumption of each device in the set duration. For details, refer to the related description in the method embodiment, and the details are not repeated.

Those skilled in the art will appreciate that embodiments of the present application can be provided as a method, system, or computer program product. Thus, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment in combination of software and hardware. Moreover, the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the present application. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. An electronic device that implements the functions specified in one or more processes and/or block diagrams of one or more blocks of the flowchart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction electronics. The instruction electronics implements the functions specified in one or more blocks of the flow or in a flow or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

It is apparent that those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, it is intended that the present invention cover the modifications and variations of the embodiments of the present invention.

Claims

A method for determining power consumption of a device of an electronic device, comprising:

Determining a power curve of the electronic device for a set duration, and determining m power models of N devices in the electronic device, respectively, the m power models are used to indicate each of the N devices The frequency domain characteristics of the power of the device in the M i use scenarios, N≥1, i=1～N,

And determining, according to the power curve of the electronic device within the set duration and the m power models, power consumption of each device within the set duration.
The method of claim 1 wherein determining a power curve of the electronic device for a set length of time comprises:

Determining a first spectral characteristic of power of the electronic device within the set duration and a first average power of the electronic device within the set duration;

Determining m power models of the N devices in the electronic device, respectively, including:

Determining m second spectral features of the N devices and m second average powers, wherein the m second spectral features are in one-to-one correspondence with the m second average powers, the m second spectra wherein said N devices wherein each device in the power spectrum at m i are respectively a usage scenario, the second average power m of the N devices respectively, each device m i th The average of the power used in the scenario.
The method of claim 2, wherein determining the power consumption of each device during the set duration according to a power curve of the electronic device within the set duration and the m power models ,include:

Determining m power coefficients of the N devices according to the first spectral feature, the first average power, the m second spectral features, and the m second average powers, the m powers Each of the coefficients is used to indicate a ratio of an average power of the device to the second average power during the set time period;

Determining m average powers of the N devices according to the m power coefficients and the m second average powers;

For each device: summing the powers of the devices in the M i use scenarios in the m average powers to obtain an average power of the device within the set duration.
The method of claim 3, wherein the N is determined according to the first spectral feature, the first average power, the m second spectral features, and the m second average powers m power coefficients of each device, including:

Determining, by the first spectral feature and the m second spectral features, a proportion of each of the second spectral features in the first spectral feature;

Determining a normalization coefficient according to the ratio, the first average power, and the m second average powers;

Multiplying the ratio and the normalization coefficient to obtain the power coefficient.
The method according to any one of claims 2 to 4, wherein the first spectral feature and the m second spectral features are represented by the same set of bases.
The method according to claim 4 or 5, wherein the ratio is solved in the following manner:

Wherein F is the first spectral feature, F i is the m second spectral features, and f j is a base of the first spectral feature and the m second spectral features, b j and a ij respectively The coefficient of the first spectral feature and the m second spectral features under the substrate, x i is the ratio.
The method of claim 6 wherein said normalization coefficients are solved in the following manner:

Where P is the first average power, P i is the m second average powers, and k is the normalization coefficient.
An electronic device comprising:

One or more processors;

Memory

Multiple applications;

And one or more programs, wherein the one or more programs are stored in the memory, the one or more programs comprising instructions that, when executed by the electronic device, cause the electronic device The method of any of claims 1-7.
A computer readable storage medium comprising instructions, wherein when the instructions are run on an electronic device,

The electronic device is caused to perform the method of any of claims 1-7.
An electronic device includes: a first determining unit, a second determining unit, and a third determining unit;

The first determining unit is configured to determine a power curve of the electronic device within a set duration;

The second determining unit is configured to respectively determine m power models of the N devices in the electronic device, where the m power models are used to indicate that each of the N devices is respectively at M i The frequency domain characteristics of the power in the scenario, N≥1, i=1～N,

The third determining unit is configured to determine, according to the power curve of the electronic device within the set duration and the m power models, power consumption of each device within the set duration.
The electronic device of claim 10, wherein

The first determining unit is specifically configured to determine a first spectrum feature of the power of the electronic device within the set duration and a first average power of the electronic device within the set duration;

The second determining unit is specifically configured to respectively determine m second spectral features of the N devices and m second average powers, where the m second spectral features and the m second average powers are one correspondence, said m second frequency spectrum wherein said N devices wherein each device in the power spectrum are used at a scene number m i, the average of m second power device of the N The average of the power of each device in the M i use scenarios.
The electronic device according to claim 11, wherein the third determining unit is specifically configured to: according to the first spectral feature, the first average power, the m second spectral features, and the m second average powers, determining m power coefficients of the N devices, each of the m power coefficients being used to indicate an average of the device in the usage scenario during the set duration The ratio of power to the second average power;

Determining m average powers of the N devices according to the m power coefficients and the m second average powers;

For each device: summing the powers of the devices in the M i use scenarios in the m average powers to obtain an average power of the device within the set duration.
The electronic device according to claim 11, wherein the third determining unit is specifically configured to respectively determine each of the second spectral features according to the first spectral feature and the m second spectral features a percentage of the first spectral features;

Determining a normalization coefficient according to the ratio, the first average power, and the m second average powers;

Multiplying the ratio and the normalization coefficient to obtain the power coefficient.
The electronic device of claims 11-13, wherein the first spectral feature and the m second spectral features are each represented by a same set of bases.
The electronic device according to claim 13 or 14, wherein the third determining unit is configured to solve the proportion in the following manner:

Wherein F is the first spectral feature, F i is the m second spectral features, and f j is a base of the first spectral feature and the m second spectral features, b j and a ij respectively The coefficient of the first spectral feature and the m second spectral features under the substrate, x i is the ratio.
The electronic device according to claim 15, wherein said third determining unit is configured to solve said normalization coefficient in the following manner:

Where P is the first average power, P i is the m second average powers, and k is the normalization coefficient.