CN-122026625-A - Terminal energy consumption strategy adjustment method based on residual electric quantity prediction

CN122026625ACN 122026625 ACN122026625 ACN 122026625ACN-122026625-A

Abstract

The invention relates to the technical field of energy consumption management of terminals of the Internet of things and edge computing equipment, in particular to a terminal energy consumption strategy adjustment method based on residual electric quantity prediction, which comprises a data acquisition, phase space construction, state evaluation and control execution module, wherein the method constructs and updates a virtual energy phase space by acquiring electric signals, temperature and energy replenishment prediction data, and is characterized in that a friction damping parameter representing capacity contraction is calculated according to ambient temperature to compress a space reachable boundary, and an energy manifold residual error is calculated based on an actual and optimal discharge track, when the residual error is larger than a preset safety threshold, the method automatically reduces sampling frequency and closes a peripheral interface.

Inventors

Liu nanyu
CHEN YIN
ZHANG JUN
JIANG HAO

Assignees

贵州华泰智远大数据服务有限公司

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (9)

1. The method for regulating the terminal energy consumption strategy based on the residual electric quantity prediction is characterized by comprising the following steps: Acquiring real-time electric signal data, environment temperature data and environment energy supply prediction data of target equipment; constructing a virtual energy phase space comprising a state coordinate system based on a preset initial potential energy parameter and a preset energy attenuation model, wherein the energy attenuation model characterizes a capacity attenuation boundary of an energy supply module of the target equipment; Calculating a friction damping parameter characterizing an amount of available capacity contraction based on the ambient temperature data to compress an achievable boundary of the virtual energy phase space; Calculating current discharge power based on the real-time electrical signal data to update current position coordinates of the target device in the virtual energy phase space; Determining corresponding potential energy replenishment point coordinates in the virtual energy phase space based on the environmental energy replenishment prediction data; Calculating an optimal state track from the current position coordinate to the potential energy supplementing point coordinate; Calculating an energy manifold residual error representing track deviation based on the actual discharge track of the target equipment and the optimal state track; Generating a first control instruction to reduce the sampling frequency of the analog-to-digital converter in the target equipment and close a preset peripheral interface under the condition that the energy manifold residual error is larger than a preset safety threshold; And generating a second control instruction to maintain the current sampling frequency of the analog-to-digital converter and the current power supply state of the peripheral interface under the condition that the energy manifold residual error is smaller than or equal to the safety threshold.
2. The method for adjusting the terminal energy consumption strategy based on the residual capacity prediction according to claim 1, wherein the constructing a virtual energy phase space including a state coordinate system based on a preset initial potential energy parameter and a preset energy attenuation model includes: configuring the initial potential energy parameter as an initial state coordinate of the virtual energy phase space; extracting a first polarization factor representing the polarization degree of the battery and a second aging factor representing the aging degree of the battery from the energy attenuation model; mapping the first polarization factor and the second aging factor into virtual elasticity coefficients of the constraint state tracks in the virtual energy phase space; the virtual energy phase space is generated based on the initial state coordinates and the virtual elastic coefficients.
3. The method for adjusting a terminal energy consumption strategy based on residual capacity prediction according to claim 1, wherein calculating a friction damping parameter characterizing an amount of available capacity shrinkage based on the ambient temperature data to compress an achievable boundary of the virtual energy phase space comprises: converting the environmental temperature data into the friction damping parameters based on a preset mapping relation between temperature and capacity attenuation; Substituting the friction damping parameter into a boundary constraint condition of the virtual energy phase space; Calculating an upper limit of the available capacity of the target device based on the substituted friction damping parameters; the upper limit of available capacity is determined as the reachable boundary of the virtual energy phase space.
4. The method for adjusting a terminal energy consumption policy based on residual capacity prediction according to claim 1, wherein the real-time electrical signal data includes real-time voltage data and real-time current data, and the calculating the current discharge power based on the real-time electrical signal data to update the current position coordinates of the target device in the virtual energy phase space includes: Calculating the current discharge power based on a product of the real-time voltage data and the real-time current data; mapping the current discharge power to a current kinetic energy parameter of the target device; And calculating the current position coordinate of the target equipment in the virtual energy phase space based on the current kinetic energy parameter.
5. The method for adjusting a terminal energy consumption strategy based on residual capacity prediction according to claim 1, wherein the calculating an optimal state trajectory from the current position coordinate to the potential energy supplementing point coordinate comprises: Mapping the potential energy supplementing point coordinates to target potential energy coordinates on the virtual energy phase space time axis; Based on the principle of minimum action quantity, analyzing geometric projection on the energy topological manifold of the virtual energy phase space to solve the extreme value of the difference between kinetic energy and potential energy on time integration; Generating a Hamiltonian track from the current position coordinate to the target potential energy coordinate based on a projection result; and determining the Hamiltonian track as the optimal state track.
6. The method for adjusting a terminal energy consumption policy based on residual power prediction according to claim 1, wherein the calculating an energy manifold residual representing a track deviation based on an actual discharge track of the target device and the optimal state track includes: extracting a historical position coordinate sequence of the target equipment in a preset historical time window; Generating the actual discharge track based on the historical position coordinate sequence fitting; calculating coordinate deviation values of the actual discharge track and the optimal state track on a preset time node; and determining the coordinate deviation value as the energy manifold residual error.
7. The terminal power consumption policy adjustment method based on residual capacity prediction according to claim 1, wherein the method further comprises: After the first control instruction or the second control instruction is executed, the updated real-time electric signal data of the target equipment is acquired again; recalculating updated discharge power based on the updated real-time electrical signal data; And based on the updated discharge power, iteratively updating the current position coordinates in the virtual energy phase space.
8. The terminal power consumption policy adjustment method based on residual capacity prediction according to claim 1, wherein the method further comprises: after executing the first control instruction to reduce the sampling frequency of the analog-to-digital converter, extracting low-frequency stable discharge data; and updating model parameters of the energy attenuation model by using the low-frequency stable discharge data, and outputting a battery health evaluation result.
9. The method for adjusting the terminal energy consumption strategy based on the residual capacity prediction according to claim 1, wherein the target device comprises an internet of things node device without a special power management chip; the environmental energy supply prediction data comprise weather overcast and rainy probability data in a future preset period; The preset peripheral interfaces comprise camera pin interfaces.

Description

Terminal energy consumption strategy adjustment method based on residual electric quantity prediction Technical Field The invention relates to the technical field of energy consumption management of terminals of the Internet of things and edge computing equipment, in particular to a terminal energy consumption strategy adjustment method based on residual electricity prediction. Background In the current intelligent power grid and the operation and maintenance environment of the Internet of things, edge computing nodes deployed under complicated working conditions such as remote high and cold are often faced with irregular discharging scenes such as temperature dip and transient high-current discharging, and are limited by hardware resource allocation, and the terminal equipment is generally lack of a special power management chip; In order to manage and predict the energy consumption of the terminal equipment, the prior schemes generally adopt a fixed capacity table look-up method or construct a complex dynamic differential equation, and although the schemes have certain evaluation capability under the conventional steady discharge scene, the schemes are highly dependent on static experience parameters and have overhigh calculation power consumption, and are extremely easy to generate the phenomena of dynamic mismatch and energy manifold topology mismatch when the service aging of the battery and the complex climate change are faced; therefore, how to improve the accuracy of the residual electric quantity prediction of the terminal equipment and the reliability of the energy consumption self-adaptive adjustment in the complex working condition under the environment without a special power management chip and with limited calculation power becomes a technical problem to be solved. Disclosure of Invention In order to solve the technical problems, the invention provides a terminal energy consumption strategy adjustment method based on residual electric quantity prediction, and specifically, the technical scheme of the invention comprises the following steps: Acquiring real-time electric signal data, environment temperature data and environment energy supply prediction data of target equipment; constructing a virtual energy phase space comprising a state coordinate system based on a preset initial potential energy parameter and a preset energy attenuation model, wherein the energy attenuation model characterizes a capacity attenuation boundary of an energy supply module of the target equipment; Calculating a friction damping parameter characterizing an amount of available capacity contraction based on the ambient temperature data to compress an achievable boundary of the virtual energy phase space; Calculating current discharge power based on the real-time electrical signal data to update current position coordinates of the target device in the virtual energy phase space; Determining corresponding potential energy replenishment point coordinates in the virtual energy phase space based on the environmental energy replenishment prediction data; Calculating an optimal state track from the current position coordinate to the potential energy supplementing point coordinate; Calculating an energy manifold residual error representing track deviation based on the actual discharge track of the target equipment and the optimal state track; Generating a first control instruction to reduce the sampling frequency of the analog-to-digital converter in the target equipment and close a preset peripheral interface under the condition that the energy manifold residual error is larger than a preset safety threshold; And generating a second control instruction to maintain the current sampling frequency of the analog-to-digital converter and the current power supply state of the peripheral interface under the condition that the energy manifold residual error is smaller than or equal to the safety threshold. Further, the constructing a virtual energy phase space including a state coordinate system based on the preset initial potential energy parameter and the preset energy attenuation model includes: configuring the initial potential energy parameter as an initial state coordinate of the virtual energy phase space; extracting a first polarization factor representing the polarization degree of the battery and a second aging factor representing the aging degree of the battery from the energy attenuation model; mapping the first polarization factor and the second aging factor into virtual elasticity coefficients of the constraint state tracks in the virtual energy phase space; the virtual energy phase space is generated based on the initial state coordinates and the virtual elastic coefficients. Further, the calculating a friction damping parameter characterizing an amount of available capacity contraction based on the ambient temperature data to compress an achievable boundary of the virtual energy phase space comprises: converting the