Embedded device power management method and system, electronic device and storage medium

Abstract

The invention discloses a power management method and system for embedded equipment, electronic equipment and a storage medium. The method comprises the following steps: acquiring power data information of the embedded equipment; analyzing the power supply data information based on a pre-trained power supply state prediction model to obtain a predicted power supply state value; determining a power state value of each task area of the embedded device according to the power data information; performing mean value calculation on the power state values of the task areas to obtain a power state mean value; and when the power supply state prediction change value is greater than the power supply state change threshold value, the power supply state mean value is set as a task process value, a management strategy of the task sub-region of the embedded device is generated, and the power supply state prediction change value is a difference value between the predicted power supply state value and the power supply state value. According to the technical scheme, the power management level of the embedded equipment can be improved, the power management strategy is optimized, and the energy efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and in particular to an embedded device power management method, system, electronic device and storage medium. Background Art

[0002] With the widespread application of embedded devices, issues such as battery life, power consumption and security are receiving more and more attention. Power management of embedded devices is a key link in device design and development. Especially in applications such as mobile, Internet of Things and portable electronic devices, the increasing complexity of device functions and the increasing demand for high performance make it an important issue to efficiently utilize limited power resources. Therefore, power management evaluation of embedded devices is particularly important.

[0003] In the prior art, traditional power management evaluation methods usually rely on offline testing or simple online monitoring. These methods cannot reflect the actual operating status of the device in real time, resulting in reduced energy efficiency and inability to monitor the power usage of the device in real time. Summary of the invention

[0004] The present invention provides an embedded device power management method, system, electronic device and storage medium to optimize power management strategy and improve energy efficiency.

[0005] According to one aspect of the present invention, a method for power management of an embedded device is provided, the method comprising:

[0006] Get power data information of embedded devices;

[0007] Analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value;

[0008] Determine the power status value of each task area of ​​the embedded device according to the power data information;

[0009] Calculate the average of the power status values ​​of each task area to obtain a power status average;

[0010] When the power state predicted change value is greater than the power state change threshold, the power state mean is set to the task process value, and a management policy for the task sub-area of ​​the embedded device is generated, wherein the power state predicted change value is the difference between the predicted power state value and the power state value.

[0011] Optionally, the acquiring power data information of the embedded device includes:

[0012] Setting a data collection terminal, wherein the data collection terminal is composed of a plurality of sub-data collection terminals, and the sub-data collection terminals are numbered;

[0013] Acquire a task area of ​​the embedded device, divide the task area into a plurality of task sub-areas, wherein the task sub-areas contain a power configuration component of the embedded device, and the power configuration component is assigned with a work task, and number the divided task sub-areas;

[0014] Associating the sub-data collection terminal and the task sub-area with the same label to obtain a corresponding device identifier; wherein the device identifier is composed of the label of the sub-data collection terminal and the label of the task sub-area;

[0015] The acquired device identifier is sent to the corresponding sub-data acquisition terminal, and the sub-data acquisition terminal collects power data information of the task sub-area with the corresponding label according to the received device identifier; wherein the power data information includes regional voltage, regional current, response time, regional battery power and image data of the task sub-area; the response time refers to the time required for the task status within the task sub-area to change, and the task status includes task in progress, task pause, task completion, task switching and task waiting, and the regional battery power refers to the remaining power within the task sub-area.

[0016] Optionally, the analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value includes:

[0017] According to the image data of the task sub-area collected by the sub-data collection terminal, the task sub-area is three-dimensionally modeled to obtain a physical model of the task sub-area, and the power data information of the task sub-area is marked to the corresponding position of the physical model of the task sub-area, and the device identifier between the sub-data collection terminal and the task sub-area is marked on the corresponding physical model of the task sub-area, and the physical models of the task sub-area are combined and spliced ​​according to the marked device identifier to obtain a task area state model; wherein the task area state model is used to reflect the task state of each power configuration component in the embedded device;

[0018] Setting a log recording library, monitoring the task status of the task area state model through the log recording library, and monitoring the response time, and obtaining the historical task start timestamp, historical task end timestamp, historical task completion amount and historical response time; wherein the task status refers to the running tasks of each power configuration component in the embedded device;

[0019] Calculate the difference between the start timestamp of the historical task and the end timestamp of the historical task to obtain the execution time of the historical task; calculate the ratio of the completion amount of the historical task to the execution time of the historical task to obtain the execution efficiency of the historical task;

[0020] Using several groups of historical task execution efficiency and historical response time as training sets and test sets, and inputting the training sets and test sets into a power state prediction model, training the power state prediction model, obtaining a trained power state prediction model, and outputting a corresponding power state prediction curve; obtaining a predicted power execution efficiency and a predicted response time according to the power state prediction curve;

[0021] A power state influence factor is set, and the power state influence factor, the predicted power execution efficiency and the predicted response time are multiplied to obtain a predicted power state value.

[0022] Optionally, determining the power status value of each task area of ​​the embedded device according to the power data information includes:

[0023] The task area state model is monitored in real time to obtain the area voltage, area current, response time, and area battery power, and the area voltage and area current are multiplied to obtain the area power consumption;

[0024] A ratio of the regional power consumption to the regional battery power is calculated, and a result of the ratio calculation is added to the response time to obtain a power state value.

[0025] Optionally, when the power state predicted change value is greater than the power state change threshold, setting the power state mean value as the task process value, and generating a management strategy for the task sub-area of ​​the embedded device, includes:

[0026] Calculate the difference between the power state value and the predicted power state value to obtain a predicted power state change value;

[0027] When the power state prediction change value is greater than the power state change threshold, it is predicted that the power state is abnormal, and the task sub-area in the embedded device is managed to generate an embedded management signal;

[0028] When the power state predicted change value is less than or equal to the power state change threshold, the power state change is predicted to be normal, and the task sub-area in the embedded device is not managed.

[0029] The task sub-area of ​​the embedded device is managed according to the embedded management signal.

[0030] Optionally, managing the task sub-area of ​​the embedded device according to the embedded management signal includes:

[0031] Calculate the average of the power state values ​​in the embedded device to obtain the power state average value, and set the power state average value as the task progress value, wherein the task progress value refers to the specified task completion time;

[0032] The power state values ​​are grouped according to the power state mean value, when the power state value is greater than the power state mean value, the power state value is recorded as a power state margin value, and when the power state value is less than or equal to the power state mean value, the power state value is recorded as a power state lean value;

[0033] Arrange the power state margin values ​​in order from large to small, and arrange the power state lean values ​​in order from small to large, and arrange the arranged power state lean values ​​at intervals within the arranged power state margin values ​​to obtain a task sequence, and sort the task sub-areas corresponding to the power state lean values ​​and the power state margin values ​​according to the task sequence, and execute the tasks in the task sub-area according to the task process value. If the power state value in the task sub-area is greater than the task process value, when the task execution time in the task sub-area reaches the task process value, the task state in the task sub-area is changed to task pause, and the task in the next task sub-area is executed; if the power state value in the task sub-area is less than the task process value, when the task execution in the task sub-area is completed, the task in the next task sub-area is executed; if the power state value in the task sub-area is equal to the task process value, the task in the task sub-area is executed, and a power management policy is generated.

[0034] Optionally, it is characterized in that after generating the power management strategy, it also includes:

[0035] By using the power management strategy, the regional current and regional voltage of each task sub-region are monitored in real time, and the regional current and regional voltage of each task sub-region are multiplied to obtain the task power consumption value;

[0036] During the task execution process of the task sub-area, performing difference calculation on the task power consumption values ​​of adjacent task sub-areas to obtain a task power consumption fluctuation value;

[0037] Setting a task power consumption fluctuation threshold, evaluating the power management strategy according to the task power consumption fluctuation threshold and the task power consumption fluctuation value, and when the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, the power management strategy does not need to be adjusted;

[0038] When the task power consumption fluctuation value is greater than the task power consumption fluctuation threshold, the power management strategy needs to be adjusted, and an adjustment value and an adjustment coefficient are set. The task progress value is adjusted according to the adjustment value and the adjustment coefficient. The adjustment value is multiplied by the adjustment coefficient, and the obtained product result is added to the task progress value to obtain the adjusted task progress value.

[0039] By adjusting the task progress value, the task execution time in the task sub-area is controlled until the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, and a power optimization management strategy is generated.

[0040] According to another aspect of the present invention, there is provided an embedded device power management system, comprising a management center, wherein the management center is communicatively connected to a power information acquisition module, a power information analysis module, a power information management module and a power information evaluation module;

[0041] The power information acquisition module is used to acquire power data information of embedded devices;

[0042] The power information analysis module is used to analyze the collected device power data information to obtain the predicted power state value and the power state value;

[0043] The power information management module is used to determine the power state of the embedded device by predicting the power state value and the power state value, and perform power management on the embedded device according to the power state of the embedded device to obtain a power management strategy;

[0044] The power information evaluation module is used to evaluate the power management strategy, obtain the evaluation result, and adjust the power management strategy according to the evaluation result to obtain the power optimization management strategy.

[0045] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0046] at least one processor; and

[0047] a memory communicatively connected to the at least one processor; wherein,

[0048] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the embedded device power management method described in any embodiment of the present invention.

[0049] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the embedded device power management evaluation method described in any embodiment of the present invention when executed.

[0050] The technical solution of the embodiment of the present invention obtains the power data information of the embedded device, analyzes the power data information based on the pre-trained power state prediction model, obtains the predicted power state value, and determines the power state value of each task area of ​​the embedded device according to the power data information. By monitoring the power state, the system performance of the embedded device can be analyzed, the power state value of each task area is averaged to obtain the power state average, and the power state predicted change value is obtained by predicting the power state value and the difference between the power state value, and when the power state predicted change value is greater than the power state change threshold, a management strategy for the task sub-area of ​​the embedded device is generated, and the power state average is used as a reference, corresponding to the task completion time. The power management system will adjust the execution of the task according to the power state average, thereby performing power management on the embedded device. The technical solution of the present invention can improve the power management level of the embedded device, optimize the power management strategy, and improve energy efficiency.

[0051] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0053] Figure 1 is a flow chart of a method for power management of an embedded device provided according to an embodiment of the present invention;

[0054] Figure 2 is a flow chart of another embedded device power management method provided according to an embodiment of the present invention;

[0055] Figure 3 is a flowchart of a method for obtaining a predicted power state value provided by an embodiment of the present invention;

[0056] Figure 4 is a flow chart of a method for determining power status values ​​of each task area of ​​an embedded device provided in an embodiment of the present invention;

[0057] Figure 5 is a flow chart of another embedded device power management method provided according to an embodiment of the present invention;

[0058] Figure 6 is a flow chart of another embedded device power management method provided in an embodiment of the present invention;

[0059] Figure 7 is a flow chart of a method for optimizing power management of an embedded device provided in an embodiment of the present invention;

[0060] Figure 8 is a schematic diagram of the structure of an embedded device power management system provided according to an embodiment of the present invention;

[0061] Fig. 9 It is a structural schematic diagram of an electronic device for implementing the embedded device power management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0063] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0064] Figure 1 A flowchart of an embedded device power management method is provided for an embodiment of the present invention. This embodiment is applicable to situations where power supply needs to be stable and reliable and system performance needs to be optimized. The method can be executed by an embedded device power management system, which can be implemented in the form of hardware and / or software. The system can be configured in mobile and portable devices, industrial automation equipment, and medical equipment. Figure 1 As shown, the method includes:

[0065] S101, obtaining power data information of an embedded device;

[0066] Among them, the embedded device refers to a computer system used to perform specific tasks, and the power data information may include voltage, current, response time, battery power, etc. The power data information can be obtained through the data acquisition terminal, and the data acquisition terminal can be divided into several sub-data acquisition terminals to collect power data information of several task sub-areas of the embedded device.

[0067] S102, analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value;

[0068] Among them, the power state prediction model is a physical model used to estimate the battery's state of charge, health state, and predict the remaining battery life. The predicted power state value refers to the value that estimates and predicts the current state and future state of the power supply. The power state prediction model can be obtained through three-dimensional modeling, and trained and tested based on historical task data to obtain a trained power state prediction model. The trained power state prediction model can be used to analyze the power data information of the embedded device to obtain the predicted power state value.

[0069] S103, determining the power status value of each task area of ​​the embedded device according to the power data information;

[0070] Among them, in the embedded system, the task area refers to the logical area where different tasks are managed and executed in the system, and the power state value refers to the indicator of the current state and performance of the power supply. The power data information can be obtained through the data acquisition terminal according to the power data information of several task sub-areas collected by several sub-data acquisition terminals. By performing three-dimensional modeling on the task sub-area and obtaining the task sub-area physical model, the power information data of the task sub-area can be matched one by one with the task sub-area physical model, and the sub-data acquisition terminal and the task sub-area can be matched one by one with the task sub-area physical model, and the task sub-area physical model can be combined and spliced ​​to obtain the task area state model. The task area state model is used to reflect the task state of each power configuration component in the embedded device. The state model of each task area is monitored in real time to obtain information such as voltage, current, response time, battery power, etc., and the power state value is determined according to the obtained power data information.

[0071] S104, calculating the average of the power status values ​​of each task area to obtain the power status average;

[0072] The power status mean value refers to a value obtained by averaging multiple power status values. The power status value of each task area can be obtained, and the power status value of each task area is averaged to obtain the power status mean value.

[0073] S105. When the power state predicted change value is greater than the power state change threshold, the power state mean is set to the task process value, and a management policy for the task sub-area of ​​the embedded device is generated, wherein the power state predicted change value is the difference between the predicted power state value and the power state value.

[0074] Among them, the power state change threshold is a preset value used to determine whether the power state has changed in the power system or battery management system. The power state predicted change value is a numerical value in the power system or battery management system that predicts the change of the power state parameter over time. The power state predicted change value can be obtained by performing a difference calculation between the power state value and the predicted power state value. The power state change threshold is set, and the power state predicted change value can be compared with the power state change threshold. When the power state predicted change value is greater than the power state change threshold, it can be considered that the predicted power state is abnormal, and the task sub-area in the embedded device needs to be managed, and an embedded management signal is generated. In this process, the power state mean can be set as the task process, and the task process refers to the specified task completion time. That is, the power state mean is used as a reference or benchmark, corresponding to the task completion time. The power management system will adjust the execution of the task according to the power state mean to ensure that the task can be completed within the specified time.

[0075] The technical solution of the embodiment of the present invention obtains the power data information of the embedded device, analyzes the power data information based on the pre-trained power state prediction model, obtains the predicted power state value, and determines the power state value of each task area of ​​the embedded device according to the power data information. By monitoring the power state, the system performance of the embedded device can be analyzed, the power state value of each task area is averaged to obtain the power state average, and the power state predicted change value is obtained by predicting the power state value and the difference between the power state value, and when the power state predicted change value is greater than the power state change threshold, a management strategy for the task sub-area of ​​the embedded device is generated, and the power state average is used as a reference, corresponding to the task completion time. The power management system will adjust the execution of the task according to the power state average, thereby performing power management on the embedded device. The technical solution of the present invention can improve the power management level of the embedded device, optimize the power management strategy, and improve energy efficiency.

[0076] Figure 2A flowchart of another method for power management of an embedded device is provided for an embodiment of the present invention. In some optional embodiments of the present invention, based on the above embodiments, reference is made to Figure 1 and Figure 2 After further refining S101, obtaining power data information of the embedded device, the method includes:

[0077] S201, setting a data collection terminal, which is composed of a plurality of sub-data collection terminals, and labeling the sub-data collection terminals;

[0078] Among them, the data acquisition terminal can obtain the power data information of the embedded device. The data acquisition terminal can include several sub-data acquisition terminals. The sub-data acquisition terminals can be distributed in different positions in the system. Each sub-data acquisition terminal is responsible for collecting the power data information of the corresponding area. The sub-data acquisition terminals can be labeled, and the labels can be numbers, letters, or any other identifiers. For example, it can be recorded as m, m = 1, 2, 3, ..., a, a is a positive integer.

[0079] S202, obtaining a task area of ​​the embedded device, dividing the task area into a plurality of task sub-areas, each task sub-area containing a power configuration component of the embedded device, and the power configuration component is assigned a work task, and numbering the divided task sub-areas;

[0080] Among them, the task area of ​​the embedded device can be obtained and divided into several task sub-areas. In each task sub-area, a power configuration component can be integrated, which is responsible for managing the power demand in the task sub-area, which can include power allocation, monitoring and optimization. The power configuration component not only manages the power, but also allocates work tasks, which can ensure the effectiveness of power management by monitoring the power status. The divided task sub-areas can be labeled, and the labels can be numbers, letters or any other identifiers. For example, it can be recorded as n, n = 1, 2, 3, ..., b, b is a positive integer.

[0081] S203, associating the sub-data collection terminals and task sub-areas with the same label to obtain a corresponding device identifier; wherein the device identifier is composed of the label of the sub-data collection terminal and the label of the task sub-area;

[0082] Among them, each sub-data collection terminal corresponds to a label, and each task sub-area corresponds to a label. The label of the sub-data collection terminal and the label of the task sub-area correspond to the same device identifier. It can ensure the pertinence of data collection and the effectiveness of task execution, and can ensure that the data collection terminal collects the required data for the corresponding task sub-area, improving the system performance and the accuracy of data processing. For example, if the label of the sub-data collection terminal is "3", then the task sub-area labeled "3" is obtained, and the sub-data collection terminal labeled "3" is associated with the task sub-area labeled "3", and the association identifier between the sub-data collection terminal labeled "3" and the task sub-area labeled "3" is "33"; if the label of the sub-data collection terminal is "7", then the task sub-area labeled "7" is obtained, and the sub-data collection terminal labeled "7" is associated with the task sub-area labeled "7", and the association identifier between the sub-data collection terminal labeled "7" and the task sub-area labeled "7" is "77".

[0083] S204. Send the acquired device identifier to the corresponding sub-data acquisition terminal, which collects power data information of the task sub-area with the corresponding label according to the received device identifier; wherein the power data information includes regional voltage, regional current, response time, regional battery power and image data of the task sub-area; response time refers to the time required for the task status in the task sub-area to change, and the task status includes task in progress, task paused, task completed, task switched and task waiting, and the regional battery power refers to the remaining power in the task sub-area.

[0084] Among them, the device identifier is composed of the label of the sub-data acquisition terminal and the label of the task sub-area. The device identifier is sent to the corresponding sub-data acquisition terminal through the management center, which can be achieved through wireless or wired communication. The sub-data acquisition terminal receives the device identifier sent from the management center, identifies and processes the received identifier, and identifies the task sub-area where data needs to be collected. Collect the power data information of the task sub-area with the corresponding label. The power data information may include regional voltage, regional current, response time, regional battery power and image data of the task sub-area; the response time refers to the time required for the task status to change in the task sub-area. The task status includes task in progress, task pause, task completion, task switching and task waiting. The regional battery power refers to the remaining power in the task sub-area.

[0085] S205, analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value;

[0086] S206, determining the power status value of each task area of ​​the embedded device according to the power data information;

[0087] S207, calculating the average of the power status values ​​of each task area to obtain a power status average;

[0088] S208. When the power state predicted change value is greater than the power state change threshold, the power state mean value is set as the task process value, and a management policy for the task sub-area of ​​the embedded device is generated, wherein the power state predicted change value is the difference between the predicted power state value and the power state value.

[0089] The technical solution of the embodiment of the present invention divides the task area of ​​the data acquisition terminal and the embedded device, and associates the divided sub-data acquisition terminal with the task sub-area to obtain the device identifier for the management of the device and the scheduling of tasks. It can ensure that the task area of ​​the embedded device is reasonably divided and managed, and each task sub-area can perform its assigned work tasks. The acquired device identifier is sent to the corresponding sub-data acquisition terminal, and the sub-data acquisition terminal collects the power data information of the task sub-area with the corresponding number according to the received device identifier. Effective communication between the sub-data acquisition terminal and the management center can be achieved, ensuring that the sub-data acquisition terminal can collect the power data information of the task sub-area with the corresponding number according to the received device identifier, thereby improving the accuracy and efficiency of data acquisition.

[0090] Figure 3 A flowchart of a method for obtaining a predicted power state value is provided for an embodiment of the present invention. In some optional embodiments of the present invention, reference is made to Figure 1 and Figure 3 S102: Analyzing the power data information based on the pre-trained power state prediction model to obtain a predicted power state value includes:

[0091] S301, based on the image data of the task sub-area collected by the sub-data collection terminal, three-dimensional modeling is performed on the task sub-area to obtain a physical model of the task sub-area, and the power data information of the task sub-area is marked, the corresponding position of the physical model of the task sub-area is marked, and the device identifier between the sub-data collection terminal and the task sub-area is marked on the corresponding physical model of the task sub-area, and the physical model of the task sub-area is combined and spliced ​​according to the marked device identifier to obtain a task area state model; wherein the task area state model is used to reflect the task state of each power configuration component in the embedded device;

[0092] Among them, the task area state model is used to reflect the task state of each power configuration component in the embedded device. The task state includes task progress, task pause, task completion, task switching and task waiting. The task sub-area is three-dimensionally modeled through the image data of the task sub-area collected by the sub-data acquisition terminal. The physical model of the task sub-area can be obtained by modeling through three-dimensional modeling software. The power data information of the task sub-area is marked at the corresponding position of the physical model, and the device identifier between the sub-data acquisition terminal and the task sub-area is marked on the corresponding task sub-area physical model. Each model can not only display the physical structure, but also identify the specific device of the data source. According to the marked device identifier, the physical models of each task sub-area are combined and spliced ​​to obtain a complete task area state model. This model not only contains the three-dimensional structure of the task area, but also includes power data information and device identifiers.

[0093] S302, setting a log recording library, monitoring the task status of the task area state model through the log recording library, and monitoring the response time, obtaining the historical task start timestamp, the historical task end timestamp, the historical task completion amount and the historical response time; wherein the task status refers to the running tasks of each power configuration component in the embedded device;

[0094] Among them, the logging library is used to record the information of events that occurred in the system. It can include timestamp, event type, event details and other information. The logging library can monitor the task execution and response time of the task area status model. Whenever a task starts or ends, it will be recorded in the logging library, including timestamp and task status. The logging library can save the start timestamp of historical tasks, the end timestamp of historical tasks, the completion amount of historical tasks and the historical response time. The response time refers to the time required for the task status to change in the task sub-area. The task status refers to the running tasks of each power configuration component in the embedded device.

[0095] S303, performing a difference calculation between the start timestamp of the historical task and the end timestamp of the historical task to obtain the execution time of the historical task; performing a ratio calculation between the completion amount of the historical task and the execution time of the historical task to obtain the execution efficiency of the historical task;

[0096] The historical task execution time can be obtained by calculating the difference between the historical task start timestamp and the historical task end timestamp, and then the historical task execution efficiency can be obtained by calculating the ratio of the historical task completion amount to the historical task execution time.

[0097] S304 uses several groups of historical task execution efficiency and historical response time as training sets and test sets, and inputs the training sets and test sets into the power state prediction model, trains the power state prediction model, obtains the trained power state prediction model, and outputs the corresponding power state prediction curve; obtains the predicted power execution efficiency and predicted response time according to the power state prediction curve;

[0098] Among them, according to the image data of several task sub-areas collected by several sub-data, three-dimensional modeling is performed on several task sub-areas to obtain several task sub-area physical models, thereby obtaining several task area state models; the task status and response time of several task area state models are monitored through the log record library to obtain several groups of historical task start timestamps, historical task end timestamps, historical task completion amounts and historical response times; thereby obtaining several groups of historical task execution efficiencies and historical response times. Several groups of historical task execution efficiencies and historical response times are used as training sets and test sets, and input into the power state prediction model to train the power state prediction model. After the training, the power state prediction model can capture the law of power state changes in historical data, and use the trained model to output the corresponding power state prediction curve according to the test set data. The power state prediction curve can be analyzed to obtain the predicted power execution efficiency and predicted response time; historical data can be effectively used to predict the power state, optimize power performance, and improve the reliability and efficiency of the system.

[0099] S305: Set a power state influence factor, calculate the product of the power state influence factor, the predicted power execution efficiency and the predicted response time, and obtain a predicted power state value.

[0100] The predicted power state value may be obtained by multiplying the power state influence factor, the predicted power execution efficiency, and the predicted response time.

[0101] Figure 4 The present invention provides a flowchart of a method for determining the power state value of each task area of ​​an embedded device. In some optional embodiments of the present invention, reference is made to Figure 1 and Figure 4 S103: The method for determining the power status value of each task area of ​​the embedded device according to the power data information includes:

[0102] S401, monitor the task area state model in real time, obtain the area voltage, area current, response time, and area battery power, calculate the product of the area voltage and the area current, and obtain the area power consumption;

[0103] Among them, the image data of the task sub-area collected by the sub-data acquisition terminal can be used to perform three-dimensional modeling of the task sub-area through three-dimensional modeling software to obtain a physical model of the task sub-area. The power supply data information of the task sub-area is marked at the corresponding position of the physical model, and the device identifier between the sub-data acquisition terminal and the task sub-area is marked on the corresponding task sub-area physical model. According to the marked device identifier, the physical models of each task sub-area are combined and spliced ​​to obtain a task area state model. The regional voltage, regional current, response time, and regional battery power can be obtained by real-time monitoring of the task area state model. The regional power consumption can be calculated by multiplying the regional voltage and the regional current.

[0104] S402: Calculate the ratio of the regional power consumption to the regional battery power, add the ratio calculation result to the response time, and obtain a power status value.

[0105] The power state value can be calculated by calculating the ratio of regional power consumption to regional battery power and then adding it to the response time. The power state predicted change value can be obtained according to the power state value and the predicted power state value, and the predicted power state can be determined according to the power state change value.

[0106] Figure 5 The present invention provides another flowchart of an embedded device power management method. In some optional embodiments of the present invention, based on the above embodiments, reference is made to Figure 1 and Figure 5 , after further refining S105, when the power state prediction change value is greater than the power state change threshold, setting the power state mean value to the task process value, and generating a management strategy for the task sub-area of ​​the embedded device, the method includes:

[0107] S501, obtaining power data information of an embedded device;

[0108] S502, analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value;

[0109] S503, determining the power status value of each task area of ​​the embedded device according to the power data information;

[0110] S504, calculating the average of the power status values ​​of each task area to obtain the power status average;

[0111] S505, performing a difference calculation between the power state value and the predicted power state value to obtain a predicted power state change value;

[0112] The power state predicted change value can be obtained by performing a difference calculation between the power state value and the predicted power state value, thereby determining the predicted power state according to the power state change value.

[0113] S506: When the power state prediction change value is greater than the power state change threshold, the power state is predicted to be abnormal, and the task sub-area in the embedded device is managed to generate an embedded management signal;

[0114] Among them, the power state can be monitored in real time, the power state value and the predicted power state value can be obtained, and the predicted power state change value can be calculated. The predicted power state is determined by comparing the power state predicted change value with the power state change threshold. When the power state predicted change value is greater than the power state change threshold, the predicted power state is abnormal. At this time, it is necessary to manage the task sub-area in the embedded device and generate an embedded management signal in the management center. The embedded device can better manage the power supply, improve the efficiency and responsiveness of the system, and ensure that timely measures can be taken when the actual change of the power state exceeds the preset threshold.

[0115] S507: When the power state predicted change value is less than or equal to the power state change threshold, the power state change is predicted to be normal, and the task sub-area in the embedded device is not managed.

[0116] Among them, if the power state predicted change value is less than or equal to the power state change threshold, it means that the power state predicted change value is within an acceptable range. At this time, the predicted power state change is normal, the system can operate normally, and there is no need to manage the task sub-area in the embedded device.

[0117] S508: Manage the task sub-area of ​​the embedded device according to the embedded management signal.

[0118] According to the comparison between the power state prediction change value and the power state change threshold, the task sub-area in the embedded device corresponding to the predicted power state abnormality is managed, which can be task progress, task pause, task completion, task switching and task waiting.

[0119] The technical solution of the present invention can effectively predict whether the power state is normal by comparing the power state predicted change value with the power state change threshold. If the predicted power state change is abnormal, the task sub-area within the embedded device can be managed to ensure the stability and efficiency of the power system.

[0120] Figure 6 A flowchart of another method for power management of an embedded device is provided for an embodiment of the present invention. In some optional embodiments of the present invention, reference is made to Figure 5 and Figure 6On the basis of the above embodiment, after S504 further refines the management of the task sub-area of ​​the embedded device according to the embedded management signal, the method includes:

[0121] S601, obtaining power data information of the embedded device;

[0122] S602, analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value;

[0123] S603: Determine the power status value of each task area of ​​the embedded device according to the power data information

[0124] S604, calculating the average of the power status values ​​of each task area to obtain the power status average;

[0125] S605, performing a difference calculation between the power state value and the predicted power state value to obtain a predicted power state change value;

[0126] S606: When the power state prediction change value is greater than the power state change threshold, the power state is predicted to be abnormal, and the task sub-area in the embedded device is managed to generate an embedded management signal;

[0127] S607: When the power state predicted change value is less than or equal to the power state change threshold, the power state change is predicted to be normal, and the task sub-area in the embedded device is not managed;

[0128] S608, calculating the average of the power state values ​​in the embedded device to obtain the power state average, and setting the power state average as the task progress value, wherein the task progress value refers to the specified task completion time;

[0129] The power state mean refers to the value obtained by averaging multiple power state values. The power state value of each task area can be obtained, and the power state value of each task area is averaged to obtain the power state mean. The power state mean is set as the task process value, allowing the embedded device to optimize the execution time and sequence of tasks according to the current power state to improve energy efficiency and performance. For the task sub-area that needs to be managed, the power state mean can be set as the task process, and the task process refers to the specified task completion time. In other words, the power state mean is used as a reference or benchmark, corresponding to the task completion time. The power management system will adjust the execution of the task according to the power state mean to ensure that the task can be completed within the specified time.

[0130] S609, grouping the power status values ​​according to the power status mean value, when the power status value is greater than the power status mean value, recording the power status value as a power status margin value, and when the power status value is less than or equal to the power status mean value, recording the power status value as a power status lean value;

[0131] The power state margin value refers to a power state value greater than the power state mean value, indicating that the performance or state of the power system is above the average level. The power state lean value refers to a power state value less than or equal to the power state mean value, indicating that the performance or state of the power system is at or below the average level. For each power state value, according to the comparison result with the power state mean value, it is marked as a power state margin value or a power state lean value.

[0132] S610, arrange each power state margin value in order from large to small, and arrange each power state lean value in order from small to large, and arrange the arranged power state lean values ​​in intervals within the arranged power state margin value, obtain a task sequence, and sort the task sub-areas corresponding to each power state lean value and power state margin value according to the task sequence, execute the tasks in the task sub-area according to the task progress value, if the power state value in the task sub-area is greater than the task progress value, then when the task execution time in the task sub-area reaches the task progress value, the task state in the task sub-area is changed to task pause, and the task in the next task sub-area is executed; if the power state value in the task sub-area is less than the task progress value, then when the task execution in the task sub-area is completed, the task in the next task sub-area is executed; if the power state value in the task sub-area is equal to the task progress value, then the task in the task sub-area is executed, and a power management policy is generated.

[0133] Among them, according to each power state margin value and each power state mean value obtained by comparison with the power state mean value, each power state margin value is arranged in order from large to small, and the value with the best power state can be placed at the front and the relatively poor value can be placed at the back. Each power state lean value is arranged from small to large, and the value with the worst power state can be placed at the front and the relatively good value can be placed at the back. The arranged power state lean values ​​are arranged at intervals between the arranged power state margin values, that is, a power state lean value is inserted between each power state margin value, so as to form a new sequence as a task sequence. The task sequence can be used for task scheduling or power management to ensure that the use of power can be balanced when executing tasks, and avoid affecting the execution efficiency of tasks or system stability due to extreme values ​​of power state. The task sub-areas corresponding to each power state lean value and power state margin value are sorted according to the task sequence, and the tasks in the task sub-areas are executed by the task process value, that is, the power state mean value.

[0134] Specifically, if the power state value in the task sub-region is greater than the task progress value, when the task execution time in the task sub-region reaches the task progress value, the current power state allows the task to be completed within the specified time. Therefore, the task will be allowed to execute until the time specified by the task progress value is reached. After reaching this time point, even if the task has not been completed, it will be paused so that the system can execute the task in the next task sub-region; if the power state value in the task sub-region is less than the task progress value, the power state cannot support the task to be completed within the specified time. In this case, the task will be allowed to continue to execute until it is completed, and the system will move to the next task sub-region and execute the task there; if the power state value in the task sub-region is equal to the task progress value, the power state just meets the requirement that the task be completed within the specified time. Task execution does not need to be paused until it is completed. At this time, the system can also generate a power management policy to ensure optimal power usage.

[0135] The technical solution of the present invention can more effectively monitor and manage the power state in the embedded device by grouping the power state value by the power state mean value, sorting each group of power state margin value and power state lean value and obtaining the task sequence, which can more effectively manage the power state in the embedded device and ensure that the execution of the task matches the power state, thereby improving the overall performance and stability of the system. Based on the power state value and the task process value, the task scheduling is performed and the power management method is generated, so that the embedded device can optimize the task execution while ensuring the stability of the system and the effective management of the power supply.

[0136] Figure 7 The present invention provides a flowchart of an embedded device power management optimization method. In some optional embodiments of the present invention, based on the above embodiments, Figure 7 As shown, after the power management strategy is generated, the embedded device power management optimization method includes:

[0137] S701, using a power management strategy, monitoring the regional current and regional voltage of each task sub-region in real time, and calculating the product of the regional current and regional voltage of each task sub-region to obtain a task power consumption value;

[0138] Among them, the power state parameters of each task sub-area are monitored in real time through the generated power management strategy. The regional current refers to the current flowing through the task sub-area, and the regional voltage refers to the power supply voltage of the sub-area. The task power consumption value can be calculated by multiplying the regional current and the regional voltage. By multiplying the regional current and the regional voltage of each task sub-area, the power consumption value of each task sub-area can be obtained.

[0139] S702, during the task execution process of the task sub-region, performing difference calculation on the task power consumption values ​​of adjacent task sub-regions to obtain a task power consumption fluctuation value;

[0140] The task power consumption fluctuation value refers to the difference in power consumption between adjacent task sub-regions. It can be used to evaluate the stability of power usage during task execution and the change in power demand between adjacent tasks. An adjacent task sub-region refers to the previous or next task sub-region next to the current task sub-region in the task execution sequence. Subtract the task power consumption values ​​of adjacent task sub-regions to obtain the power consumption difference between them.

[0141] S703, setting a task power consumption fluctuation threshold, and evaluating the power management strategy according to the task power consumption fluctuation threshold and the task power consumption fluctuation value. When the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, the power management strategy does not need to be adjusted.

[0142] The task power consumption fluctuation threshold is a pre-set value used to determine whether the task power consumption fluctuation is within an acceptable range. The power management strategy can be evaluated by comparing the task power consumption fluctuation value and the task power consumption fluctuation threshold. If the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, the power consumption change is within an acceptable range, and the current power management strategy can effectively support task execution without adjustment.

[0143] S704. When the task power consumption fluctuation value is greater than the task power consumption fluctuation threshold, the power management strategy needs to be adjusted, and the adjustment value and the adjustment coefficient are set. The task progress value is adjusted according to the adjustment value and the adjustment coefficient. The adjustment value is multiplied by the adjustment coefficient, and the obtained product result is added to the task progress value to obtain the adjusted task progress value.

[0144] The adjustment value refers to the increment or decrement value set to adjust the task progress value. The adjustment coefficient is used to adjust the size of the adjustment value. The adjustment amount is calculated by multiplying the adjustment value and the adjustment coefficient, and the adjustment amount indicates the size of the task progress value to be adjusted. The obtained adjustment amount is added to the task progress value to obtain the adjusted task progress value. The new task progress value reflects the adjustment of the task execution time, which may be advanced or delayed to adapt to the change of power status. Adjusting the task progress value can optimize power usage and ensure that the task can be completed within the range allowed by the power status.

[0145] S705 , control the task execution time in the task sub-area by adjusting the task progress value until the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, and generate a power optimization management strategy.

[0146] Among them, the task progress value refers to the specified task completion time. By adjusting the task progress value, the execution time of the task can be controlled to adapt it to the current power state. If the task power consumption fluctuation value exceeds the preset task power consumption fluctuation threshold, the impact of task execution on the power supply is large, and the power consumption fluctuation can be reduced by adjusting the task execution time. After adjusting the task progress value, continue to monitor the task power consumption fluctuation value to evaluate the effect of the adjustment. Continue to adjust the task progress value until the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold. At this point, the impact of task execution on the power supply has been controlled within an acceptable range. When the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, a power optimization management strategy is generated based on the current task progress value and power state.

[0147] The technical solution of the present invention can more effectively manage the power state in the embedded device by calculating the task power consumption value and the task power consumption fluctuation value, and determining whether the power management strategy needs to be adjusted according to the size relationship between the task power consumption fluctuation value and the task power consumption fluctuation threshold, so as to ensure that the execution of the task matches the power state, thereby improving the overall performance and stability of the system. When the task power consumption fluctuation value is greater than the task power consumption fluctuation threshold, the task process is adjusted by setting the mobilization value and the mobilization coefficient until the task power consumption fluctuation value is less than the task power consumption fluctuation threshold, and a power optimization management strategy is generated. It can ensure that the power use of the embedded device is kept in an optimized state when executing a task, reduce system instability caused by power supply fluctuations, improve power efficiency, and ensure that the task is completed on time.

[0148] Figure 8 The following is a schematic diagram of the structure of an embedded device power management system provided by an embodiment of the present invention. Figure 8 As shown, the system includes:

[0149] Management center 801, management center 801 is communicatively connected with power information acquisition module 802, power information analysis module 803, power information management module 804 and power information evaluation module 805;

[0150] The power information collection module 802 is used to collect power data information of embedded devices;

[0151] The power information analysis module 803 is used to analyze the collected device power data information to obtain the predicted power state value and the power state value;

[0152] The power information management module 804 is used to determine the power state of the embedded device by predicting the power state value and the power state value, and perform power management on the embedded device according to the power state of the embedded device to obtain a power management strategy;

[0153] The power information evaluation module 805 is used to evaluate the power management strategy, obtain the evaluation result, and adjust the power management strategy according to the evaluation result to obtain the power optimization management strategy.

[0154] The embedded device power management system provided by the embodiment of the present invention can execute the embedded device power management method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0155] Fig. 9 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0156] like Fig. 9 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0157] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0158] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as an embedded device power management method.

[0159] In some embodiments, the embedded device power management method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the embedded device power management method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the embedded device power management method in any other appropriate manner (e.g., by means of firmware).

[0160] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0161] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0162] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0163] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0164] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0165] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0166] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0167] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for power management of an embedded device, characterized in that: The method comprises: Get power data information of embedded devices; Analyzing the power data information based on a pre-trained power state prediction model to obtain a predicted power state value; Determine the power status value of each task area of ​​the embedded device according to the power data information; Calculate the average of the power status values ​​of each task area to obtain a power status average; When the power state predicted change value is greater than the power state change threshold, the power state mean is set to the task process value, and a management policy for the task sub-area of ​​the embedded device is generated, wherein the power state predicted change value is the difference between the predicted power state value and the power state value.

2. The method according to claim 1, characterized in that: The step of obtaining power data information of the embedded device includes: Setting a data collection terminal, wherein the data collection terminal is composed of a plurality of sub-data collection terminals, and the sub-data collection terminals are numbered; Acquire a task area of ​​the embedded device, divide the task area into a plurality of task sub-areas, wherein the task sub-areas contain a power configuration component of the embedded device, and the power configuration component is assigned with a work task, and number the divided task sub-areas; Associating the sub-data collection terminal and the task sub-area with the same label to obtain a corresponding device identifier; wherein the device identifier is composed of the label of the sub-data collection terminal and the label of the task sub-area; The acquired device identifier is sent to the corresponding sub-data acquisition terminal, and the sub-data acquisition terminal collects power data information of the task sub-area with the corresponding label according to the received device identifier; wherein the power data information includes regional voltage, regional current, response time, regional battery power and image data of the task sub-area; the response time refers to the time required for the task status within the task sub-area to change, and the task status includes task in progress, task pause, task completion, task switching and task waiting, and the regional battery power refers to the remaining power within the task sub-area.

3. The method according to claim 2, characterized in that The analyzing the power data information based on the pre-trained power state prediction model to obtain a predicted power state value includes: According to the image data of the task sub-area collected by the sub-data collection terminal, the task sub-area is three-dimensionally modeled to obtain a physical model of the task sub-area, and the power data information of the task sub-area is marked to the corresponding position of the physical model of the task sub-area, and the device identifier between the sub-data collection terminal and the task sub-area is marked on the corresponding physical model of the task sub-area, and the physical models of the task sub-area are combined and spliced ​​according to the marked device identifier to obtain a task area state model; wherein the task area state model is used to reflect the task state of each power configuration component in the embedded device; Setting a log recording library, monitoring the task status of the task area state model through the log recording library, and monitoring the response time, and obtaining the historical task start timestamp, historical task end timestamp, historical task completion amount and historical response time; wherein the task status refers to the running tasks of each power configuration component in the embedded device; Calculate the difference between the start timestamp of the historical task and the end timestamp of the historical task to obtain the execution time of the historical task; calculate the ratio of the completion amount of the historical task to the execution time of the historical task to obtain the execution efficiency of the historical task; Using several groups of historical task execution efficiency and historical response time as training sets and test sets, and inputting the training sets and test sets into a power state prediction model, training the power state prediction model, obtaining a trained power state prediction model, and outputting a corresponding power state prediction curve; obtaining a predicted power execution efficiency and a predicted response time according to the power state prediction curve; A power state influence factor is set, and the power state influence factor, the predicted power execution efficiency and the predicted response time are multiplied to obtain a predicted power state value.

4. The method according to claim 3, characterized in that The determining the power status value of each task area of ​​the embedded device according to the power data information includes: The task area state model is monitored in real time to obtain the area voltage, area current, response time, and area battery power, and the area voltage and area current are multiplied to obtain the area power consumption; A ratio of the regional power consumption to the regional battery power is calculated, and a result of the ratio calculation is added to the response time to obtain a power state value.

5. The method according to claim 1, characterized in that When the power state predicted change value is greater than the power state change threshold, the power state mean value is set as the task process value, and a management strategy for the task sub-area of ​​the embedded device is generated, including: Calculate the difference between the power state value and the predicted power state value to obtain a predicted power state change value; When the power state prediction change value is greater than the power state change threshold, it is predicted that the power state is abnormal, and the task sub-area in the embedded device is managed to generate an embedded management signal; When the power state predicted change value is less than or equal to the power state change threshold, the power state change is predicted to be normal, and the task sub-area in the embedded device is not managed; The task sub-area of ​​the embedded device is managed according to the embedded management signal.

6. The method according to claim 5, characterized in that: The managing the task sub-area of ​​the embedded device according to the embedded management signal includes: Calculate the average of the power state values ​​in the embedded device to obtain the power state average value, and set the power state average value as the task progress value, wherein the task progress value refers to the specified task completion time; The power state values ​​are grouped according to the power state mean value, when the power state value is greater than the power state mean value, the power state value is recorded as a power state margin value, and when the power state value is less than or equal to the power state mean value, the power state value is recorded as a power state lean value; Arrange the power state margin values ​​in order from large to small, and arrange the power state lean values ​​in order from small to large, and arrange the arranged power state lean values ​​at intervals within the arranged power state margin values ​​to obtain a task sequence, and sort the task sub-areas corresponding to the power state lean values ​​and the power state margin values ​​according to the task sequence, and execute the tasks in the task sub-area according to the task process value. If the power state value in the task sub-area is greater than the task process value, when the task execution time in the task sub-area reaches the task process value, the task state in the task sub-area is changed to task pause, and the task in the next task sub-area is executed; if the power state value in the task sub-area is less than the task process value, when the task execution in the task sub-area is completed, the task in the next task sub-area is executed; if the power state value in the task sub-area is equal to the task process value, the task in the task sub-area is executed, and a power management policy is generated.

7. The method according to claim 6, characterized in that After generating the power management strategy, the method further includes: By using the power management strategy, the regional current and regional voltage of each task sub-region are monitored in real time, and the regional current and regional voltage of each task sub-region are multiplied to obtain the task power consumption value; During the task execution process of the task sub-area, performing difference calculation on the task power consumption values ​​of adjacent task sub-areas to obtain a task power consumption fluctuation value; Setting a task power consumption fluctuation threshold, evaluating the power management strategy according to the task power consumption fluctuation threshold and the task power consumption fluctuation value, and when the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, the power management strategy does not need to be adjusted; When the task power consumption fluctuation value is greater than the task power consumption fluctuation threshold, the power management strategy needs to be adjusted, and an adjustment value and an adjustment coefficient are set. The task progress value is adjusted according to the adjustment value and the adjustment coefficient. The adjustment value is multiplied by the adjustment coefficient, and the obtained product result is added to the task progress value to obtain the adjusted task progress value. By adjusting the task progress value, the task execution time in the task sub-area is controlled until the task power consumption fluctuation value is less than or equal to the task power consumption fluctuation threshold, and a power optimization management strategy is generated.

8. An embedded device power management system, characterized in that: It includes a management center, which is communicatively connected to a power information acquisition module, a power information analysis module, a power information management module and a power information evaluation module; The power information acquisition module is used to acquire power data information of embedded devices; The power information analysis module is used to analyze the collected device power data information to obtain the predicted power state value and the power state value; The power information management module is used to determine the power state of the embedded device by predicting the power state value and the power state value, and perform power management on the embedded device according to the power state of the embedded device to obtain a power management strategy; The power information evaluation module is used to evaluate the power management strategy, obtain the evaluation result, and adjust the power management strategy according to the evaluation result to obtain the power optimization management strategy.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the embedded device power management method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the embedded device power management evaluation method according to any one of claims 1 to 7 when executed.

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