Method and system for adjusting power consumption of RFID tag chip

Abstract

The invention discloses a power consumption adjustment method and system for an RFID tag chip, and the method comprises the steps: analyzing the heat effect interference distribution information of a target RFID tag chip and a corresponding power consumption distribution imbalance module; the chip power consumption constraint condition and the data interaction configuration scheme of each power consumption distribution imbalance module are considered when the energy distribution optimization is carried out on each power consumption distribution imbalance module, so that the power consumption distribution optimization can be accurately and effectively carried out on the power consumption distribution imbalance module when the heat effect interference condition exists; and meanwhile, smooth data interaction of each power consumption distribution imbalance module is ensured, so that the stability and the performance of the target RFID tag chip are ensured, and the requirement of coexistence of high performance and miniaturization of the RFID tag chip can be met.

Description

Technical Field

[0001] The present invention relates to the field of chip technology, and in particular to a method and system for adjusting power consumption of an RFID tag chip. Background Art

[0002] In the field of modern science and technology, the research of radio frequency identification tag chips based on artificial intelligence is of vital importance. They are widely used in scenarios such as logistics, medical treatment and intelligent manufacturing, and directly affect the advancement of informatization and intelligentization. However, in the existing technology, radio frequency identification tag chips often expose obvious deficiencies when facing complex application environments, especially in terms of functional integration and stability assurance in space-constrained scenarios. The existing technology is difficult to meet the needs of high performance and miniaturization of radio frequency identification tag chips. The main reason is that in space-constrained scenarios, the high integration of radio frequency identification tag chips will lead to the superposition of thermal effects between components, thereby generating non-negligible interference. This thermal effect interference will directly lead to power consumption imbalance between multiple functional modules within the radio frequency identification tag chip. The existing technology cannot effectively deal with the power consumption imbalance caused by thermal effect interference, which in turn seriously affects the stability and performance of the radio frequency identification tag chip. Summary of the Invention

[0003] The present invention provides a power consumption adjustment method and system for an RFID tag chip to solve the technical problem that the existing technology cannot effectively deal with the power consumption imbalance problem caused by thermal effect interference, thereby seriously affecting the stability and performance of the RFID tag chip.

[0004] In order to solve the above technical problems, a first aspect of an embodiment of the present invention provides a method for adjusting power consumption of an RFID tag chip, comprising: Determining thermal effect interference distribution information of the target RFID tag chip based on structural parameters and surface temperature distribution data of the target RFID tag chip; Determining a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and temperature detection data of each functional module in the target RFID tag chip; Determining a data interaction configuration scheme for each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters; According to the data interaction configuration scheme and the preset chip power consumption constraint conditions, energy allocation optimization is performed on each of the power consumption distribution imbalance modules to determine the target energy allocation ratio of each of the power consumption distribution imbalance modules; According to the target energy allocation ratio, the power consumption limit value of each of the power consumption distribution imbalance modules is determined, and the output power consumption of each of the power consumption distribution imbalance modules is adjusted according to the power consumption limit value.

[0005] As a preferred solution, determining the thermal effect interference distribution information of the target RFID tag chip based on the structural parameters and surface temperature distribution data of the target RFID tag chip specifically includes: Determining the assembly position, heating power, surface area, heat transfer distance, and thermal conductivity of each functional module in the target RFID tag chip based on the structural parameters; determining a heat influence radius of each of the functional modules according to the heat generation power, the surface area, the heat transfer distance, and the thermal conductivity; Determining the heat-affected area of ​​each functional module according to the assembly position and the heat-affected radius, and determining at least one heat-effect superposition area within the target RFID tag chip based on the overlapping area between the heat-affected areas; Determining, based on the surface temperature distribution data, a plurality of surface temperature collection points within the thermal effect superposition area and a surface temperature value corresponding to each of the surface temperature collection points; determining, based on the surface temperature value and a preset surface temperature threshold, whether each of the thermal effect superposition areas is a thermal effect interference area; When any thermal effect superposition region exists as the thermal effect interference region, the thermal effect interference distribution information is determined according to the position information of the thermal effect interference region and a plurality of target function modules corresponding to the thermal effect interference region.

[0006] As a preferred solution, the step of determining a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and the temperature detection data of each functional module in the target RFID tag chip specifically includes: Determining, according to the thermal effect interference distribution information, a number of the target functional modules corresponding to each of the thermal effect interference areas; Acquire a target temperature detection value sequence of each target functional module within a preset temperature detection period from the temperature detection data of each functional module; Inputting the target temperature detection value sequence into a preset autoregressive moving average model to obtain a power consumption value sequence corresponding to the target temperature detection value sequence of each target functional module; wherein the autoregressive moving average model is obtained by training based on historical temperature detection data and historical power consumption data of each functional module within a preset historical time period; determine whether output power distribution of a plurality of the target function modules corresponding to each of the thermal effect interference regions is unbalanced according to real-time total chip power at each time point in the power consumption value sequence, preset upper limit and lower limit of power consumption proportion of each of the target function modules, and the power consumption value sequence; when output power distribution of a plurality of the target function modules corresponding to any one of the thermal effect interference regions is unbalanced, determine the plurality of the target function modules corresponding to the any one of the thermal effect interference regions as the power consumption distribution imbalance module.

[0007] As a preferred solution, the data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters, and specifically includes: determine a data interaction priority coefficient of each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules; determine the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the data interaction priority coefficient and the chip configuration parameters.

[0008] As a preferred solution, the data interaction priority coefficient of each of the power consumption distribution imbalance modules is determined according to the power consumption data of each of the power consumption distribution imbalance modules, and specifically includes: determine actual output power and rated output power of each of the power consumption distribution imbalance modules according to the power consumption data; determine the data interaction priority coefficient of each of the power consumption distribution imbalance modules according to a ratio between the actual output power and the rated output power.

[0009] As a preferred solution, the data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the data interaction priority coefficient and the chip configuration parameters, and specifically includes: determine an interconnection bandwidth parameter, a to-be-processed task emergency coefficient and a data interaction coefficient between each of the power consumption distribution imbalance modules according to the chip configuration parameters; the to-be-processed task emergency coefficient is determined based on a difference between a preset processing deadline of a current to-be-processed task of the power consumption distribution imbalance module and a current time; the data interaction coefficient is used to represent a data interaction probability between each of the power consumption distribution imbalance modules, and the data interaction coefficient is determined based on historical data interaction records of the power consumption distribution imbalance module; determine a data interaction demand weight between each of the power consumption distribution imbalance modules according to the interconnection bandwidth parameter, the to-be-processed task emergency coefficient, the data interaction coefficient and the data interaction priority coefficient; Determining bandwidth configuration parameters of data interaction paths between the power consumption distribution imbalance modules according to the data interaction demand weights and the current remaining bandwidth resources; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the bandwidth configuration parameters of each of the data interaction paths.

[0010] As a preferred solution, the energy allocation optimization of each of the power consumption distribution imbalance modules is performed according to the data interaction configuration scheme and the preset chip power consumption constraint conditions, and the target energy allocation ratio of each of the power consumption distribution imbalance modules is determined, specifically including: Determining the bandwidth configuration parameters of the data interaction paths between the power consumption distribution imbalance modules according to the data interaction configuration scheme; Determining the energy consumption per unit time of each of the data interaction paths based on the bandwidth configuration parameters and a preset power consumption coefficient per unit bandwidth; Determining the current total chip power consumption of the target RFID tag chip according to the actual output power consumption of each of the functional modules and the energy consumption value per unit time; According to the actual output power consumption of each of the power consumption distribution imbalance modules, the current total power consumption of the chip and the chip power consumption constraint condition, a genetic algorithm is used to optimize the energy allocation of each of the power consumption distribution imbalance modules to determine the target energy allocation ratio of each of the power consumption distribution imbalance modules.

[0011] As a preferred solution, the method of optimizing energy allocation for each of the power distribution imbalance modules using a genetic algorithm based on the actual output power consumption of each of the power distribution imbalance modules, the current total chip power consumption, and the chip power consumption constraint condition, and determining the target energy allocation ratio of each of the power distribution imbalance modules specifically includes: determining an initial energy allocation ratio of each of the power consumption distribution imbalance modules according to a ratio between the actual output power consumption of each of the power consumption distribution imbalance modules and the current total power consumption of the chip; Determining the output power consumption upper limit of each functional module and the total power consumption upper limit of the chip according to the chip power consumption constraint condition; Determining a current energy allocation constraint based on the output power consumption upper limit and the chip total power consumption upper limit; Based on the initial energy allocation ratio, an initial population comprising a plurality of chromosomes is randomly generated within a preset initialization interval; wherein the chromosomes include a plurality of coding genes for representing the energy allocation ratio of each of the power consumption allocation imbalance modules and the energy allocation ratios of the remaining functional modules except the power consumption allocation imbalance module; Based on a fitness function, a fitness evaluation is performed on each chromosome in the initial population to obtain a fitness evaluation result; wherein the fitness function is the inverse of the sum of squares of differences between the energy allocation value of the functional module and its output power consumption upper limit; the energy allocation value is the product of the energy allocation ratio and the total power consumption upper limit of the chip; Based on the fitness evaluation result, a genetic algorithm is used to iteratively update the initial population until the fitness evaluation result meets a preset iteration termination condition, and the target energy allocation ratio of each power consumption distribution imbalance module is determined according to the chromosome with the highest current fitness value.

[0012] As a preferred solution, determining the power consumption limit value of each of the power consumption distribution imbalance modules according to the target energy allocation ratio specifically includes: The power consumption limit value of each of the power consumption allocation imbalance modules is determined according to the product of the chip total power consumption upper limit in the chip power consumption constraint condition and each of the target energy allocation ratios.

[0013] A second aspect of an embodiment of the present invention provides a power consumption adjustment system for an RFID tag chip, including: A thermal effect interference distribution analysis module is used to determine the thermal effect interference distribution information of the target RFID tag chip based on the structural parameters and surface temperature distribution data of the target RFID tag chip; a power consumption distribution imbalance module determination module, configured to determine a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and temperature detection data of each functional module in the target RFID tag chip; A data interaction configuration module, configured to determine a data interaction configuration scheme for each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters; an energy allocation optimization module, configured to optimize energy allocation for each of the power consumption distribution imbalance modules according to the data interaction configuration scheme and preset chip power consumption constraints, and determine a target energy allocation ratio for each of the power consumption distribution imbalance modules; The output power consumption adjustment module is configured to determine the power consumption limit value of each of the power consumption distribution imbalance modules according to the target energy distribution ratio, and adjust the output power consumption of each of the power consumption distribution imbalance modules according to the power consumption limit value.

[0014] Compared with the prior art, the embodiment of the present application has the beneficial effects that by analyzing the thermal effect interference distribution information of the target RFID tag chip and the corresponding power consumption allocation imbalance module, and considering the chip power consumption constraint condition and the data interaction configuration scheme of each power consumption allocation imbalance module when optimizing the energy allocation of each power consumption allocation imbalance module, the power consumption allocation imbalance module can be accurately and effectively optimized in the presence of thermal effect interference, while ensuring the smooth data interaction of each power consumption allocation imbalance module, thereby ensuring the stability and performance of the target RFID tag chip, and helping to meet the demand for coexistence of high performance and miniaturization of RFID tag chips. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a flow diagram of the power consumption adjustment method of the RFID tag chip in the embodiment of the present application; Figure 2 is a structural diagram of the power consumption adjustment system of the RFID tag chip in the embodiment of the present application. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0017] Please refer to Figure 1 The first aspect of the embodiment of the present application provides a power consumption adjustment method of an RFID tag chip, comprising the following steps S1 to S5: Step S1, determining the thermal effect interference distribution information of a target RFID tag chip according to the structure parameters and surface temperature distribution data of the target RFID tag chip; Step S2, determining a plurality of power consumption allocation imbalance modules based on the thermal effect interference distribution information and the temperature detection data of each functional module in the target RFID tag chip; Step S3, determining the data interaction configuration scheme of each power consumption allocation imbalance module according to the power consumption data of each power consumption allocation imbalance module and the preset chip configuration parameters; Step S4, optimizing the energy allocation of each power consumption allocation imbalance module according to the data interaction configuration scheme and the preset chip power consumption constraint condition, and determining the energy allocation ratio of each power consumption allocation imbalance module; Step S5: determining the power consumption limit value of each of the power consumption distribution imbalance modules according to the energy distribution ratio, and adjusting the output power consumption of each of the power consumption distribution imbalance modules according to the power consumption limit value.

[0018] Specifically, since thermal interference in RFID (Radio Frequency Identification) tag chips typically arises from the superposition of thermal effects between components in space-constrained scenarios, such as in some highly integrated or miniaturized RFID tag chips, this thermal interference not only leads to an imbalance in power consumption between multiple functional modules, but also affects the data transmission stability of the RFID tag chip. This is because temperature changes can cause changes in the dielectric constant of the material, which is sufficient to cause a significant shift in the originally stable signal propagation path. Therefore, it is necessary to optimize power consumption allocation for modules with unbalanced power consumption allocation under thermal interference. It is understandable that the assembly position of each functional module in the RFID tag chip determines the thermal effect superposition area between the functional modules. That is, for different RFID tag chips, the functional modules contained therein may be different, the assembly positions of the functional modules may also be different, and thus the thermal effect superposition area may also be different. In order to accurately identify the thermal effect interference information of the target RFID tag chip, this embodiment needs to first obtain the structural parameters and surface temperature distribution data of the target RFID tag chip to determine its thermal effect interference distribution information.

[0019] Furthermore, after the thermal effect interference distribution information is determined, it is possible to determine several current modules with unbalanced power consumption distribution based on the temperature detection data of each functional module corresponding to the thermal effect interference distribution area.

[0020] Furthermore, when optimizing the power distribution of imbalanced power distribution modules, it is necessary not only to ensure that the output power consumption of each imbalanced power distribution module after optimization is within an appropriate range, thereby achieving balanced power distribution, but also to ensure the high performance of the target RFID tag chip. To ensure the high performance of the target RFID tag chip, it is necessary to ensure that data interaction between each imbalanced power distribution module proceeds smoothly to avoid affecting the execution of pending tasks of each imbalanced power distribution module at each moment. Therefore, this embodiment determines the current data interaction configuration scheme for each imbalanced power distribution module based on the power consumption data and chip configuration parameters of each imbalanced power distribution module, providing an optimization basis for subsequent energy distribution optimization. It can be understood that the power consumption data of each imbalanced power distribution module can directly reflect the computing tasks undertaken by each imbalanced power distribution module, and the chip configuration parameters are real-time and accurate. They store parameters related to data interaction between each imbalanced power distribution module, such as interconnection bandwidth parameters and information about pending tasks, thereby providing a basis for determining the data interaction configuration scheme.

[0021] Furthermore, since the cooling systems of different RFID tag chips have different heat dissipation capabilities, different cooling systems have different power consumption constraints for the overall power consumption of the RFID tag chip and the power consumption of each functional module therein, to ensure that under the power consumption constraints, the cooling system of the current RFID tag chip can effectively dissipate heat and avoid the continuous superposition of thermal effects. Therefore, this embodiment optimizes the energy distribution of each power distribution imbalance module based on the above-mentioned data interaction configuration scheme and the preset chip power consumption constraints of the target RFID tag chip, thereby determining the target energy distribution ratio of each power distribution imbalance module. According to the target energy distribution ratio, it can be converted into the power consumption limit value of each power distribution imbalance module, and the power consumption configuration instructions containing the respective power consumption limit values ​​are sent to each power distribution imbalance module through the power consumption control interface inside the target RFID tag chip, thereby adjusting the output power consumption of each power distribution imbalance module to meet the allocated power consumption limit value.

[0022] The power consumption adjustment method for an RFID tag chip provided in an embodiment of the present invention analyzes the thermal effect interference distribution information of a target RFID tag chip and the corresponding power consumption distribution imbalance module, and considers the chip power consumption constraints and the data interaction configuration scheme of each power consumption distribution imbalance module when optimizing energy allocation for each power consumption distribution imbalance module. This method can accurately and effectively optimize the power consumption allocation of the power consumption distribution imbalance module when thermal effect interference exists, while ensuring smooth data interaction between each power consumption distribution imbalance module, thereby ensuring the stability and performance of the target RFID tag chip, and helping to meet the requirements of high performance and miniaturization of RFID tag chips.

[0023] As a preferred solution, determining the thermal effect interference distribution information of the target RFID tag chip based on the structural parameters and surface temperature distribution data of the target RFID tag chip specifically includes: Determining the assembly position, heating power, surface area, heat transfer distance, and thermal conductivity of each functional module in the target RFID tag chip based on the structural parameters; determining a heat influence radius of each of the functional modules according to the heat generation power, the surface area, the heat transfer distance, and the thermal conductivity; Determining the heat-affected area of ​​each functional module according to the assembly position and the heat-affected radius, and determining at least one heat-effect superposition area within the target RFID tag chip based on the overlapping area between the heat-affected areas; Determining, based on the surface temperature distribution data, a plurality of surface temperature collection points within the thermal effect superposition area and a surface temperature value corresponding to each of the surface temperature collection points; determining, based on the surface temperature value and a preset surface temperature threshold, whether each of the thermal effect superposition areas is a thermal effect interference area; When any thermal effect superposition region exists as the thermal effect interference region, the thermal effect interference distribution information is determined according to the position information of the thermal effect interference region and a plurality of target function modules corresponding to the thermal effect interference region.

[0024] Specifically, this embodiment uses the structural parameters of the target RFID tag chip to obtain the assembly position, heating power, surface area, heat transfer distance, and thermal conductivity of each functional module within it. Furthermore, the heat flux density can be obtained based on the ratio of the heating power of each functional module to its surface area. Then, by multiplying the heat flux density by the heat transfer distance and then calculating the ratio of the multiplied result to the thermal conductivity, the heat influence radius of each functional module can be obtained. It is understood that heating power refers to the amount of heat generated by a functional module per unit time, typically measured in watts (W), reflecting the rate at which the electrical energy consumed by the functional module during operation is converted into thermal energy. Thermal conductivity is a physical quantity that measures the thermal conductivity of a material, typically expressed in watts per meter·Kelvin (W / m·K). It reflects the amount of heat that passes through a unit area per unit time under a unit temperature gradient. A higher thermal conductivity indicates a higher thermal conductivity. The heat transfer distance refers to the path length along which heat is transferred from a heat source to the surrounding environment or a heat dissipation structure, typically measured in meters (m).

[0025] Furthermore, based on the assembly position and heat impact radius of each functional module, the heat impact area of ​​each functional module can be determined. When there is an overlapping area between the heat impact areas of at least two functional modules, the overlapping area is the thermal effect superposition area.

[0026] Furthermore, this embodiment collects surface temperature distribution data of the target RFID tag chip by pre-setting a number of temperature sensors on the surface of the target RFID tag chip. For example, this embodiment can divide the surface area of ​​the target RFID tag chip into a number of grids according to a preset grid side length, for example, into 10×10 grid areas, and then arrange a temperature sensor in each grid area, so that there are 100 temperature collection points on the surface of the target RFID tag chip, and each temperature sensor has a unique position coordinate, which can clearly define the surface area corresponding to each surface temperature value. For each thermal effect superposition area, the surface temperature collection points contained therein are counted and the surface temperature value corresponding to each surface temperature collection point is obtained. Then, based on a preset surface temperature threshold, such as 90°C, 92°C, 94°C, 95°C, etc., which is not specifically limited in this embodiment, the proportion of surface temperature collection points in the thermal effect superposition area that exceeds the surface temperature threshold is counted, and this proportion is used to determine whether each thermal effect superposition area is a thermal effect interference area. It can be understood that when the proportion of surface temperature collection points exceeding the surface temperature threshold in the thermal effect superposition area is greater than the preset proportion threshold, it indicates that there is excessive heat accumulation in the thermal effect superposition area, and it is determined to be a thermal effect interference area. Since each thermal effect superposition area is determined by the overlap of the heat influence areas of at least two functional modules, each thermal effect interference area has at least two corresponding functional modules. According to the position information of each thermal effect interference area and the corresponding target functional modules, the thermal effect interference distribution information can be determined.

[0027] As a preferred solution, the step of determining a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and the temperature detection data of each functional module in the target RFID tag chip specifically includes: Determining, according to the thermal effect interference distribution information, a number of the target functional modules corresponding to each of the thermal effect interference areas; Acquire a target temperature detection value sequence of each target functional module within a preset temperature detection period from the temperature detection data of each functional module; Inputting the target temperature detection value sequence into a preset autoregressive moving average model to obtain a power consumption value sequence corresponding to the target temperature detection value sequence of each target functional module; wherein the autoregressive moving average model is obtained by training based on historical temperature detection data and historical power consumption data of each functional module within a preset historical time period; Determine whether the output power consumption distribution of the target functional modules corresponding to each thermal effect interference area is unbalanced based on the real-time total chip power consumption at each moment in the power consumption value sequence, the preset upper limit of the power consumption ratio of each target functional module, the preset lower limit of the power consumption ratio, and the power consumption value sequence; When there is an output power consumption distribution imbalance among several target functional modules corresponding to any one thermal effect interference region, the several target functional modules corresponding to any one thermal effect interference region are determined as modules with unbalanced power consumption distribution.

[0028] Specifically, after determining the thermal effect interference distribution information, the several target functional modules corresponding to each thermal effect interference area can be clearly identified. Since there is a positive correlation between the operating temperature and output power consumption of each functional module, in order to determine whether the output power consumption distribution of the several target functional modules corresponding to each thermal effect interference area is unbalanced, this embodiment obtains the target temperature detection value sequence of each target functional module within a preset temperature detection period from the temperature detection data of each functional module.

[0029] Furthermore, this embodiment utilizes an autoregressive moving average model to derive a corresponding power consumption value sequence based on the target temperature detection value sequence of each target functional module. It is understandable that there is a nonlinear relationship between the operating temperature and output power consumption of a functional module. For example, for every 10°C increase in the operating temperature of a functional module, its output power consumption may increase by 15% to 20%. This embodiment has discovered that the autoregressive moving average model exhibits unique advantages in processing the corresponding relationship between temperature and power consumption. The autoregressive moving average model is trained using the historical temperature detection data and historical power consumption data of each functional module within a preset historical time period. It is worth noting that at each moment within this historical time period, the corresponding temperature detection value and power consumption value can be obtained from the historical temperature detection data and historical power consumption data. Therefore, training the autoregressive moving average model based on this historical temperature detection data and historical power consumption data can ensure that the autoregressive moving average model fits the nonlinear relationship between the operating temperature and output power consumption of the functional module, thereby achieving the conversion from a temperature series to a power consumption series.

[0030] Furthermore, by calculating the difference between the power consumption values ​​at adjacent moments in the power consumption value sequence and dividing it by the time interval, the instantaneous power consumption change rate of each target functional module at each moment can be obtained. When the instantaneous power consumption change rate is positive, it indicates that the power consumption has increased, and when the instantaneous power consumption change rate is negative, it indicates that the power consumption has decreased. In this embodiment, the proportional analysis method is used to determine the imbalance in power consumption distribution. Under normal circumstances, for the CPU (Central Processing Unit), GPU (Graphics Processing Unit), For the real-time chip total power consumption of the target functional modules (GPU, graphics processing unit) and other functional modules, the power consumption of the CPU accounts for approximately 40% of the total chip power consumption, the power consumption of the GPU accounts for approximately 30% of the total chip power consumption, and the power consumption of the remaining functional modules accounts for approximately 30% of the total chip power consumption. Based on the real-time chip total power consumption at each moment in the power consumption value sequence, the preset upper and lower limits of the power consumption ratio of each target functional module, and the power consumption value sequence, it is possible to determine whether the output power consumption distribution of the target functional modules corresponding to each thermal effect interference region is unbalanced. Specifically, the output power consumption distribution imbalance usually occurs in a specific spatial region and is caused by thermal effect interference. When it is detected that, among the target functional modules corresponding to the thermal effect interference region, the ratio between the power consumption value of at least one target functional module and the real-time chip total power consumption exceeds its preset upper limit of power consumption ratio and lasts for a preset time, while the ratio between the power consumption value of the remaining target functional modules and the real-time chip total power consumption is compressed to less than the preset lower limit of power consumption ratio and lasts for a preset time, it is determined that the target functional modules corresponding to the thermal effect interference region have a power consumption distribution imbalance.

[0031] As a preferred solution, determining the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and the preset chip configuration parameters specifically includes: determining, according to the power consumption data of each of the power consumption distribution imbalance modules, a data interaction priority coefficient of each of the power consumption distribution imbalance modules; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the data interaction priority coefficient and the chip configuration parameter.

[0032] Specifically, this embodiment can clarify the computing tasks undertaken by each power consumption distribution imbalance module based on the power consumption data of each power consumption distribution imbalance module. The heavier the computing tasks undertaken, the higher the urgency of resource allocation. Therefore, the data interaction priority coefficient of each power consumption distribution imbalance module is determined based on this.

[0033] Furthermore, in addition to considering the computing tasks undertaken by each power distribution imbalance module, it is also necessary to consider the chip configuration parameters to configure the data interaction of each power distribution imbalance module, so as to take into account the hardware capabilities, task requirements and the correlation between modules at the same time, achieve the dual goals of power consumption balance and performance optimization, and effectively alleviate the problem of local overheating.

[0034] As a preferred solution, determining the data interaction priority coefficient of each power consumption distribution imbalance module according to the power consumption data of each power consumption distribution imbalance module specifically includes: determining, based on the power consumption data, the actual output power consumption and the rated output power consumption of each of the power consumption distribution imbalance modules; The data interaction priority coefficient of each of the power consumption distribution imbalance modules is determined according to a ratio between the actual output power consumption and the rated output power consumption.

[0035] Specifically, each functional module will determine a rated output power consumption during design. The ratio between the actual output power consumption and the rated output power consumption of each power distribution imbalance module can intuitively reflect the load pressure of each power distribution imbalance module. Therefore, this embodiment uses this ratio as the data interaction priority coefficient of each power distribution imbalance module. For example, assuming that there are currently three power distribution imbalance modules, namely GPU, CPU and cache controller, after calculation, the ratio between the actual output power consumption and the rated output power consumption of the GPU is 1.5, the ratio between the actual output power consumption and the rated output power consumption of the CPU is 1.3, and the ratio between the actual output power consumption and the rated output power consumption of the cache controller is 1.1. Then, the data interaction priority coefficients of the GPU, CPU and cache controller are 1.5, 1.3 and 1.1 respectively. The size of the data interaction priority coefficient reflects the urgency of the current demand for data transmission resources by the power distribution imbalance module.

[0036] As a preferred solution, determining the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the data interaction priority coefficient and the chip configuration parameter specifically includes: Determining, based on the chip configuration parameters, an interconnection bandwidth parameter, an urgency coefficient of a pending task, and a data interaction coefficient between each of the power distribution imbalance modules; wherein the urgency coefficient of the pending task is determined based on a difference between a preset processing deadline of a current pending task of the power distribution imbalance module and a current time; and the data interaction coefficient is used to represent a probability of data interaction between each of the power distribution imbalance modules, and is determined based on historical data interaction records of the power distribution imbalance modules. Determining the data interaction demand weights between the power consumption distribution imbalance modules according to the interconnection bandwidth parameter, the urgency coefficient of the task to be processed, the data interaction coefficient, and the data interaction priority coefficient; Determining bandwidth configuration parameters of data interaction paths between the power consumption distribution imbalance modules according to the data interaction demand weights and the current remaining bandwidth resources; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the bandwidth configuration parameters of each of the data interaction paths.

[0037] Specifically, this embodiment first obtains the interconnection bandwidth parameters, the urgency coefficient of the pending tasks and the data interaction coefficient between each power distribution imbalance module from the chip configuration parameters. It can be understood that the interconnection bandwidth parameters are used to represent the maximum transmission capacity of the data transmission channel between each power distribution imbalance module, usually in GB / s; the urgency coefficient of the pending tasks is determined based on the difference between the preset processing deadline and the current time of the current pending tasks of the power distribution imbalance module. For example, this embodiment can set corresponding urgency coefficients of pending tasks for different difference intervals. The smaller the difference, the higher the urgency of the pending tasks, and the larger the corresponding urgency coefficient of the pending tasks; the data interaction coefficient is used to represent the probability of data interaction between each power distribution imbalance module, which can provide a basis for the subsequent allocation of data interaction resources, wherein the data interaction coefficient is based on It is determined based on the historical data interaction records of the power consumption allocation imbalance module. It can be understood that this embodiment can use the historical data interaction records to count the total data interaction times of the power consumption allocation imbalance module in a certain historical time period and the data interaction times between the power consumption allocation imbalance module and the remaining functional modules. Based on the ratio of the data interaction times between the power consumption allocation imbalance module and the remaining functional modules to the total data interaction times, the data interaction probability between the power consumption allocation imbalance module and the remaining functional modules can be determined. If the data interaction probability between the two power consumption allocation imbalance modules is greater, it means that the data interaction demand between the two power consumption allocation imbalance modules is greater, and more data interaction resources need to be allocated.

[0038] Furthermore, the product of the interconnection bandwidth parameter, the urgency coefficient of the task to be processed, the data interaction coefficient, and the data interaction priority coefficient is used as the data interaction demand coefficient of the data interaction path between each power distribution imbalance module, and then the data interaction demand coefficients of each data interaction path are summed to obtain the total data interaction demand coefficient of each current data interaction path, and then based on the ratio between the data interaction demand coefficients between each power distribution imbalance module and the total data interaction demand coefficient, the data interaction demand weight between each power distribution imbalance module is determined. It can be understood that when calculating the data interaction demand coefficient, the two power distribution imbalance modules involved in the data interaction path are represented by the first power distribution imbalance module and the second power distribution imbalance module respectively. If the data interaction path is used for the first power distribution imbalance module to transmit data to the second power distribution imbalance module, the data interaction priority coefficient used when calculating the data interaction demand coefficient is the data interaction priority coefficient of the first power distribution imbalance module.

[0039] Furthermore, a data interaction path with a larger data interaction demand weight indicates that the data transmission task on this data interaction path has a higher priority. Therefore, based on the product of each interaction demand weight and the current remaining bandwidth resources, the bandwidth configuration parameters of the data interaction path between each power consumption allocation imbalance module can be determined, which can ensure that the data interaction path with a larger data interaction demand weight can be allocated more bandwidth resources.

[0040] As a preferred solution, the energy allocation optimization of each of the power consumption distribution imbalance modules is performed according to the data interaction configuration scheme and the preset chip power consumption constraint conditions, and the target energy allocation ratio of each of the power consumption distribution imbalance modules is determined, specifically including: Determining the bandwidth configuration parameters of the data interaction paths between the power consumption distribution imbalance modules according to the data interaction configuration scheme; Determining the energy consumption per unit time of each of the data interaction paths based on the bandwidth configuration parameters and a preset power consumption coefficient per unit bandwidth; Determining the current total chip power consumption of the target RFID tag chip according to the actual output power consumption of each of the functional modules and the energy consumption value per unit time; According to the actual output power consumption of each of the power consumption distribution imbalance modules, the current total power consumption of the chip and the chip power consumption constraint condition, a genetic algorithm is used to optimize the energy allocation of each of the power consumption distribution imbalance modules to determine the target energy allocation ratio of each of the power consumption distribution imbalance modules.

[0041] Specifically, after obtaining the data interaction configuration scheme of each power consumption distribution imbalance module, this embodiment can clarify the bandwidth configuration parameters of the data interaction path between each power consumption distribution imbalance module. For example, the data interaction path for transmitting data from a higher priority GPU to a cache controller is allocated a bandwidth of 16 GB / s.

[0042] Furthermore, the bandwidth configuration parameters of each data interaction path are a guarantee for the smooth progress of data interaction tasks. The larger the allocated bandwidth, the higher the required power consumption. Therefore, this embodiment determines the unit time energy consumption value of each data interaction path based on the product of the bandwidth configuration parameters and the preset unit bandwidth power consumption coefficient, where the unit bandwidth power consumption coefficient is used to represent the power consumed per unit data transmission bandwidth. For example, assuming that a data interaction path is currently allocated a bandwidth of 16GB / s, and the unit bandwidth power consumption coefficient is: the power consumed per unit time for transmitting 1GB of data is 0.5W, then the unit time energy consumption value of this data interaction path is 8W. By calculating the actual output power consumption of each functional module and the unit time energy consumption value of the data interaction path between each power distribution imbalance module, the current total chip power consumption can be determined. The total chip power consumption is the power consumption value required for the normal operation of each functional module and the normal data interaction of each power distribution imbalance module.

[0043] Furthermore, based on the actual output power consumption of each power distribution imbalance module, the current total power consumption of the chip and the chip power consumption constraint conditions, a genetic algorithm is used to optimize the energy allocation of each power distribution imbalance module. This not only fully utilizes the capabilities of each power distribution imbalance module, but also ensures that the power consumption value of each power distribution imbalance module will not exceed its own power consumption constraint value. While solving the power distribution imbalance problem, it ensures that the data interaction of each power distribution imbalance module proceeds normally.

[0044] As a preferred solution, the method of optimizing energy allocation for each of the power distribution imbalance modules using a genetic algorithm based on the actual output power consumption of each of the power distribution imbalance modules, the current total chip power consumption, and the chip power consumption constraint condition, and determining the target energy allocation ratio of each of the power distribution imbalance modules specifically includes: determining an initial energy allocation ratio of each of the power consumption distribution imbalance modules according to a ratio between the actual output power consumption of each of the power consumption distribution imbalance modules and the current total power consumption of the chip; Determining the output power consumption upper limit of each functional module and the total power consumption upper limit of the chip according to the chip power consumption constraint condition; Determining a current energy allocation constraint based on the output power consumption upper limit and the chip total power consumption upper limit; Based on the initial energy allocation ratio, an initial population comprising a plurality of chromosomes is randomly generated within a preset initialization interval; wherein the chromosomes include a plurality of coding genes for representing the energy allocation ratio of each of the power consumption allocation imbalance modules and the energy allocation ratios of the remaining functional modules except the power consumption allocation imbalance module; Based on a fitness function, a fitness evaluation is performed on each chromosome in the initial population to obtain a fitness evaluation result; wherein the fitness function is the inverse of the sum of squares of differences between the energy allocation value of the functional module and its output power consumption upper limit; the energy allocation value is the product of the energy allocation ratio and the total power consumption upper limit of the chip; Based on the fitness evaluation result, a genetic algorithm is used to iteratively update the initial population until the fitness evaluation result meets a preset iteration termination condition, and the target energy allocation ratio of each power consumption distribution imbalance module is determined according to the chromosome with the highest current fitness value.

[0045] Specifically, this embodiment first determines the initial energy allocation ratio of each power distribution imbalance module based on the ratio between the actual output power consumption of each power distribution imbalance module and the current total power consumption of the chip. It can be understood that although the actual output power consumption of each power distribution imbalance module is currently unbalanced, under normal circumstances, the actual output power consumption of each power distribution imbalance module will not deviate too much from its rated output power consumption. In the process of executing the genetic algorithm, if the chromosomes in the initial population are simply randomly generated, there may be more chromosomes in which the energy allocation ratio represented by each gene code is unreasonable, resulting in more invalid solutions. Therefore, this embodiment randomly generates an initial population containing several chromosomes within a preset initialization interval based on the initial energy allocation ratio. The initialization interval can be set according to actual needs. For example, taking the initial energy allocation ratio as the base ratio, a ratio adjustment coefficient is introduced to define an initialization interval. The ratio between the absolute value of the difference between the ratio value in this initialization interval and the initial energy allocation ratio and the initial energy allocation ratio is less than or equal to the ratio adjustment coefficient. For example, assuming that the initial energy allocation ratio is [0.5, 0.3, 0.2], 0.5 and 0.3 represent the initial energy allocation ratios of the two power consumption allocation imbalance modules, respectively, and 0. .2 represents the initial energy allocation ratio of the remaining functional modules except the two power distribution imbalance modules. The current ratio adjustment coefficient is 10%. Then one of the initialized chromosomes can be encoded as [0.48, 0.32, 0.2], where 0.48 and 0.32 represent the energy allocation ratios of the two power distribution imbalance modules respectively, and 0.2 represents the energy allocation ratio of the remaining functional modules except the two power distribution imbalance modules. Compared with the initial energy allocation ratio, the change values ​​of these three energy allocation ratios all meet the current ratio adjustment coefficient, thereby narrowing the search range of the genetic algorithm, avoiding wasting iterations in invalid areas, and improving optimization efficiency.

[0046] Furthermore, the fitness function in this embodiment is the inverse of the sum of the squares of the differences between a functional module's energy allocation value and its output power consumption ceiling. When a functional module's energy allocation value approaches its output power consumption ceiling, its fitness value decreases, guiding the genetic algorithm to find a more balanced allocation solution. After evaluating the fitness of each chromosome in the initial population, the genetic algorithm is used to iteratively update the initial population based on the fitness evaluation results. This involves selection, crossover, and mutation operations. Specifically, the selection operation uses a roulette wheel method, selecting parent chromosomes based on their fitness values. Chromosomes with higher fitness values ​​have a higher probability of being selected. The specific steps are: calculating the fitness value of each chromosome; calculating the cumulative fitness value of each chromosome; generating a random number, and selecting a chromosome based on the cumulative fitness value. A crossover operation randomly selects two parent chromosomes and exchanges their coding genes according to a preset crossover probability (e.g., 80%) to produce a new allocation combination, namely, the offspring chromosome. Through a mutation operation, the chromosome to be mutated is selected according to a preset mutation probability (e.g., 5%). Random perturbations are then added to a coding gene on the selected chromosome to increase population diversity and avoid falling into a local optimum. This ensures that the adjusted value still meets the energy allocation ratio constraint, namely, that the sum of the values ​​of all coding gene bits is 1. The fitness value of each chromosome in the current new population is then calculated. Based on this fitness value, chromosomes with high fitness values ​​are selected to enter the next generation of the population until the fitness evaluation results meet a preset iteration termination condition. Exemplarily, this iteration termination condition is: the genetic algorithm is considered to have converged when the rate of change of the optimal fitness value for 10 consecutive generations is less than 0.01. After the iteration terminates, the target energy allocation ratio for each power distribution imbalance module is determined based on the values ​​of each coding gene bit in the chromosome with the highest current fitness value.

[0047] As a preferred solution, determining the power consumption limit value of each of the power consumption distribution imbalance modules according to the target energy allocation ratio specifically includes: The power consumption limit value of each of the power consumption allocation imbalance modules is determined according to the product of the chip total power consumption upper limit in the chip power consumption constraint condition and each of the target energy allocation ratios.

[0048] Specifically, assuming that the total power consumption limit of the chip in the chip power consumption constraint is 150W, there are currently three power consumption distribution imbalance modules, namely GPU, CPU and cache controller. The target energy allocation ratio corresponding to the GPU is 0.4, the target energy allocation ratio corresponding to the CPU is 0.3, and the target energy allocation ratio corresponding to the cache controller is 0.2. Then the power consumption limit value corresponding to the GPU is 60W, the power consumption limit value corresponding to the CPU is 45W, and the power consumption limit value corresponding to the cache controller is 30W.

[0049] It is worth noting that when adjusting the operating parameters of the power distribution imbalance module to comply with the power consumption limit value, this can be achieved by dynamically adjusting the operating frequency or voltage. For example, assuming that the power consumption limit value of the GPU is 60W, but its current actual operating power consumption is 70W, the operating frequency of the GPU can be reduced, such as from 1.5GHz to 1.2GHz, to reduce its power output. Such adjustments are usually completed by the power management unit within the chip, which monitors and dynamically adjusts the parameters of each module in real time to ensure that the power consumption is stable within the limit. For example, the current sensor and voltage sensor inside the chip can collect data multiple times per second to form a high-precision operating status data set. Assuming that the current value of the GPU is 5A and the voltage value is 12V, its real-time operating power consumption is 60W.

[0050] See Figure 2 A second aspect of an embodiment of the present invention provides a power consumption adjustment system for an RFID tag chip, comprising: The thermal effect interference distribution analysis module 11 is used to determine the thermal effect interference distribution information of the target RFID tag chip according to the structural parameters and surface temperature distribution data of the target RFID tag chip; a power consumption distribution imbalance module determining module 12, configured to determine a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and the temperature detection data of each functional module in the target RFID tag chip; A data interaction configuration module 13 is configured to determine a data interaction configuration scheme for each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters; An energy allocation optimization module 14 is configured to optimize energy allocation for each of the power consumption distribution imbalance modules according to the data interaction configuration scheme and the preset chip power consumption constraint conditions, and determine a target energy allocation ratio for each of the power consumption distribution imbalance modules; The output power consumption adjustment module 15 is configured to determine the power consumption limit value of each of the power consumption distribution imbalance modules according to the target energy allocation ratio, and adjust the output power consumption of each of the power consumption distribution imbalance modules according to the power consumption limit value.

[0051] As a preferred solution, the thermal effect interference distribution analysis module 11 is used to determine the thermal effect interference distribution information of the target RFID tag chip based on the structural parameters and surface temperature distribution data of the target RFID tag chip, specifically including: Determining the assembly position, heating power, surface area, heat transfer distance, and thermal conductivity of each functional module in the target RFID tag chip based on the structural parameters; determining a heat influence radius of each of the functional modules according to the heat generation power, the surface area, the heat transfer distance, and the thermal conductivity; Determining the heat-affected area of ​​each functional module according to the assembly position and the heat-affected radius, and determining at least one heat-effect superposition area within the target RFID tag chip based on the overlapping area between the heat-affected areas; Determining, based on the surface temperature distribution data, a plurality of surface temperature collection points within the thermal effect superposition area and a surface temperature value corresponding to each of the surface temperature collection points; determining, based on the surface temperature value and a preset surface temperature threshold, whether each of the thermal effect superposition areas is a thermal effect interference area; When any thermal effect superposition region exists as the thermal effect interference region, the thermal effect interference distribution information is determined according to the position information of the thermal effect interference region and a plurality of target function modules corresponding to the thermal effect interference region.

[0052] As a preferred solution, the power consumption distribution imbalance module determination module 12 is used to determine a number of power consumption distribution imbalance modules based on the thermal effect interference distribution information and the temperature detection data of each functional module in the target RFID tag chip, specifically including: Determining, according to the thermal effect interference distribution information, a number of the target functional modules corresponding to each of the thermal effect interference areas; Acquire a target temperature detection value sequence of each target functional module within a preset temperature detection period from the temperature detection data of each functional module; Inputting the target temperature detection value sequence into a preset autoregressive moving average model to obtain a power consumption value sequence corresponding to the target temperature detection value sequence of each target functional module; wherein the autoregressive moving average model is obtained by training based on historical temperature detection data and historical power consumption data of each functional module within a preset historical time period; Determine whether the output power consumption distribution of the target functional modules corresponding to each thermal effect interference area is unbalanced based on the real-time total chip power consumption at each moment in the power consumption value sequence, the preset upper limit of the power consumption ratio of each target functional module, the preset lower limit of the power consumption ratio, and the power consumption value sequence; When there is an output power consumption distribution imbalance among several target functional modules corresponding to any one thermal effect interference region, the several target functional modules corresponding to the any one thermal effect interference region are determined as modules with unbalanced power consumption distribution.

[0053] As a preferred solution, the data interaction configuration module 13 is used to determine the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and the preset chip configuration parameters, specifically including: determining, according to the power consumption data of each of the power consumption distribution imbalance modules, a data interaction priority coefficient of each of the power consumption distribution imbalance modules; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the data interaction priority coefficient and the chip configuration parameter.

[0054] As a preferred solution, the data interaction configuration module 13 is configured to determine the data interaction priority coefficient of each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules, specifically including: determining, based on the power consumption data, the actual output power consumption and the rated output power consumption of each of the power consumption distribution imbalance modules; The data interaction priority coefficient of each of the power consumption distribution imbalance modules is determined according to a ratio between the actual output power consumption and the rated output power consumption.

[0055] As a preferred solution, the data interaction configuration module 13 is used to determine the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the data interaction priority coefficient and the chip configuration parameters, specifically including: Determining, based on the chip configuration parameters, an interconnection bandwidth parameter, an urgency coefficient of a pending task, and a data interaction coefficient between each of the power distribution imbalance modules; wherein the urgency coefficient of the pending task is determined based on a difference between a preset processing deadline of a current pending task of the power distribution imbalance module and a current time; and the data interaction coefficient is used to represent a probability of data interaction between each of the power distribution imbalance modules, and is determined based on historical data interaction records of the power distribution imbalance modules. Determining the data interaction demand weights between the power consumption distribution imbalance modules according to the interconnection bandwidth parameter, the urgency coefficient of the task to be processed, the data interaction coefficient, and the data interaction priority coefficient; Determining bandwidth configuration parameters of data interaction paths between the power consumption distribution imbalance modules according to the data interaction demand weights and the current remaining bandwidth resources; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the bandwidth configuration parameters of each of the data interaction paths.

[0056] As a preferred solution, the energy allocation optimization module 14 is used to optimize the energy allocation of each of the power consumption distribution imbalance modules according to the data interaction configuration scheme and the preset chip power consumption constraint conditions, and determine the target energy allocation ratio of each of the power consumption distribution imbalance modules, specifically including: Determining the bandwidth configuration parameters of the data interaction paths between the power consumption distribution imbalance modules according to the data interaction configuration scheme; Determining the energy consumption per unit time of each of the data interaction paths based on the bandwidth configuration parameters and a preset power consumption coefficient per unit bandwidth; Determining the current total chip power consumption of the target RFID tag chip according to the actual output power consumption of each of the functional modules and the energy consumption value per unit time; According to the actual output power consumption of each of the power consumption distribution imbalance modules, the current total power consumption of the chip and the chip power consumption constraint condition, a genetic algorithm is used to optimize the energy allocation of each of the power consumption distribution imbalance modules to determine the target energy allocation ratio of each of the power consumption distribution imbalance modules.

[0057] As a preferred solution, the energy allocation optimization module 14 is configured to optimize the energy allocation of each of the power distribution imbalance modules using a genetic algorithm based on the actual output power consumption of each of the power distribution imbalance modules, the current total chip power consumption, and the chip power consumption constraint, and determine the target energy allocation ratio of each of the power distribution imbalance modules. Specifically, the method includes: determining an initial energy allocation ratio of each of the power consumption distribution imbalance modules according to a ratio between the actual output power consumption of each of the power consumption distribution imbalance modules and the current total power consumption of the chip; Determining the output power consumption upper limit of each functional module and the total power consumption upper limit of the chip according to the chip power consumption constraint condition; Determining a current energy allocation constraint based on the output power consumption upper limit and the chip total power consumption upper limit; Based on the initial energy allocation ratio, an initial population comprising a plurality of chromosomes is randomly generated within a preset initialization interval; wherein the chromosomes include a plurality of coding genes for representing the energy allocation ratio of each of the power consumption allocation imbalance modules and the energy allocation ratios of the remaining functional modules except the power consumption allocation imbalance module; Based on a fitness function, a fitness evaluation is performed on each chromosome in the initial population to obtain a fitness evaluation result; wherein the fitness function is the inverse of the sum of squares of differences between the energy allocation value of the functional module and its output power consumption upper limit; the energy allocation value is the product of the energy allocation ratio and the total power consumption upper limit of the chip; Based on the fitness evaluation result, a genetic algorithm is used to iteratively update the initial population until the fitness evaluation result meets a preset iteration termination condition, and the target energy allocation ratio of each power consumption distribution imbalance module is determined according to the chromosome with the highest current fitness value.

[0058] As a preferred solution, the output power consumption adjustment module 15 is used to determine the power consumption limit value of each of the power consumption distribution imbalance modules according to the target energy distribution ratio, specifically including: The power consumption limit value of each of the power consumption allocation imbalance modules is determined according to the product of the chip total power consumption upper limit in the chip power consumption constraint condition and each of the target energy allocation ratios.

[0059] The power consumption adjustment system for an RFID tag chip provided by an embodiment of the present invention analyzes the thermal effect interference distribution information of a target RFID tag chip and the corresponding power consumption distribution imbalance module, and considers the chip power consumption constraints and the data interaction configuration scheme of each power consumption distribution imbalance module when optimizing energy allocation for each power consumption distribution imbalance module. Thus, when thermal effect interference exists, the power consumption allocation of the power consumption distribution imbalance module can be accurately and effectively optimized, while ensuring smooth data interaction between the power consumption distribution imbalance modules, thereby ensuring the stability and performance of the target RFID tag chip, and helping to meet the requirements of high performance and miniaturization of RFID tag chips.

[0060] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for adjusting power consumption of an RFID tag chip, characterized in that: include: Determining thermal effect interference distribution information of the target RFID tag chip based on structural parameters and surface temperature distribution data of the target RFID tag chip; Determining a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and temperature detection data of each functional module in the target RFID tag chip; Determining a data interaction configuration scheme for each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters; According to the data interaction configuration scheme and the preset chip power consumption constraint conditions, energy allocation optimization is performed on each of the power consumption distribution imbalance modules to determine the target energy allocation ratio of each of the power consumption distribution imbalance modules; According to the target energy allocation ratio, the power consumption limit value of each of the power consumption distribution imbalance modules is determined, and the output power consumption of each of the power consumption distribution imbalance modules is adjusted according to the power consumption limit value.

2. The method for adjusting power consumption of an RFID tag chip according to claim 1, wherein: Determining the thermal effect interference distribution information of the target RFID tag chip based on the structural parameters and surface temperature distribution data of the target RFID tag chip specifically includes: Determining the assembly position, heating power, surface area, heat transfer distance, and thermal conductivity of each functional module in the target RFID tag chip based on the structural parameters; determining a heat influence radius of each of the functional modules according to the heat generation power, the surface area, the heat transfer distance, and the thermal conductivity; Determining the heat-affected area of ​​each functional module according to the assembly position and the heat-affected radius, and determining at least one heat-effect superposition area within the target RFID tag chip based on the overlapping area between the heat-affected areas; Determining, based on the surface temperature distribution data, a plurality of surface temperature collection points within the thermal effect superposition area and a surface temperature value corresponding to each of the surface temperature collection points; determining, based on the surface temperature value and a preset surface temperature threshold, whether each of the thermal effect superposition areas is a thermal effect interference area; When any thermal effect superposition region exists as the thermal effect interference region, the thermal effect interference distribution information is determined according to the position information of the thermal effect interference region and a plurality of target function modules corresponding to the thermal effect interference region.

3. The method for adjusting power consumption of an RFID tag chip according to claim 2, wherein: The determining of a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and the temperature detection data of each functional module in the target RFID tag chip specifically includes: Determining, according to the thermal effect interference distribution information, a number of the target functional modules corresponding to each of the thermal effect interference areas; Acquire a target temperature detection value sequence of each target functional module within a preset temperature detection period from the temperature detection data of each functional module; Inputting the target temperature detection value sequence into a preset autoregressive moving average model to obtain a power consumption value sequence corresponding to the target temperature detection value sequence of each target functional module; wherein the autoregressive moving average model is obtained by training based on historical temperature detection data and historical power consumption data of each functional module within a preset historical time period; Determine whether the output power consumption distribution of the target functional modules corresponding to each thermal effect interference area is unbalanced based on the real-time total chip power consumption at each moment in the power consumption value sequence, the preset upper limit of the power consumption ratio of each target functional module, the preset lower limit of the power consumption ratio, and the power consumption value sequence; When there is an output power consumption distribution imbalance among several target functional modules corresponding to any one thermal effect interference region, the several target functional modules corresponding to any one thermal effect interference region are determined as modules with unbalanced power consumption distribution.

4. The method for adjusting power consumption of an RFID tag chip according to claim 1, wherein: Determining the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters specifically includes: determining a data interaction priority coefficient of each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the data interaction priority coefficient and the chip configuration parameter.

5. The method for adjusting power consumption of an RFID tag chip according to claim 4, wherein: The determining, according to the power consumption data of each of the power consumption distribution imbalance modules, a data interaction priority coefficient of each of the power consumption distribution imbalance modules specifically includes: Determining the actual output power consumption and rated output power consumption of each of the power consumption distribution imbalance modules according to the power consumption data; The data interaction priority coefficient of each of the power consumption distribution imbalance modules is determined according to a ratio between the actual output power consumption and the rated output power consumption.

6. The method for adjusting power consumption of an RFID tag chip according to claim 4, wherein: Determining the data interaction configuration scheme of each of the power consumption distribution imbalance modules according to the data interaction priority coefficient and the chip configuration parameter specifically includes: Determining, based on the chip configuration parameters, an interconnection bandwidth parameter, an urgency coefficient of a pending task, and a data interaction coefficient between each of the power distribution imbalance modules; wherein the urgency coefficient of the pending task is determined based on a difference between a preset processing deadline of a current pending task of the power distribution imbalance module and a current time; and the data interaction coefficient is used to represent a probability of data interaction between each of the power distribution imbalance modules, and is determined based on historical data interaction records of the power distribution imbalance modules. Determining the data interaction demand weights between the power consumption distribution imbalance modules according to the interconnection bandwidth parameter, the urgency coefficient of the task to be processed, the data interaction coefficient, and the data interaction priority coefficient; Determining bandwidth configuration parameters of data interaction paths between the power consumption distribution imbalance modules according to the data interaction demand weights and the current remaining bandwidth resources; The data interaction configuration scheme of each of the power consumption distribution imbalance modules is determined according to the bandwidth configuration parameters of each of the data interaction paths.

7. The method for adjusting power consumption of an RFID tag chip according to claim 6, wherein: The step of optimizing energy allocation for each of the power consumption distribution imbalance modules according to the data interaction configuration scheme and the preset chip power consumption constraint conditions, and determining a target energy allocation ratio for each of the power consumption distribution imbalance modules, specifically includes: Determining the bandwidth configuration parameters of the data interaction paths between the power consumption distribution imbalance modules according to the data interaction configuration scheme; Determining the energy consumption per unit time of each of the data interaction paths based on the bandwidth configuration parameters and a preset power consumption coefficient per unit bandwidth; Determining the current total chip power consumption of the target RFID tag chip according to the actual output power consumption of each of the functional modules and the energy consumption value per unit time; According to the actual output power consumption of each of the power consumption distribution imbalance modules, the current total power consumption of the chip and the chip power consumption constraint condition, a genetic algorithm is used to optimize the energy allocation of each of the power consumption distribution imbalance modules to determine the target energy allocation ratio of each of the power consumption distribution imbalance modules.

8. The method for adjusting power consumption of an RFID tag chip according to claim 7, wherein: The step of optimizing energy allocation for each of the power consumption distribution imbalance modules using a genetic algorithm based on the actual output power consumption of each of the power consumption distribution imbalance modules, the current total power consumption of the chip, and the chip power consumption constraint condition, and determining the target energy allocation ratio of each of the power consumption distribution imbalance modules specifically includes: determining an initial energy allocation ratio of each of the power consumption distribution imbalance modules according to a ratio between the actual output power consumption of each of the power consumption distribution imbalance modules and the current total power consumption of the chip; Determining the output power consumption upper limit of each functional module and the total power consumption upper limit of the chip according to the chip power consumption constraint condition; Determining a current energy allocation constraint based on the output power consumption upper limit and the chip total power consumption upper limit; Based on the initial energy allocation ratio, an initial population comprising a plurality of chromosomes is randomly generated within a preset initialization interval; wherein the chromosomes include a plurality of coding genes for representing the energy allocation ratio of each of the power consumption allocation imbalance modules and the energy allocation ratios of the remaining functional modules except the power consumption allocation imbalance module; Based on a fitness function, a fitness evaluation is performed on each chromosome in the initial population to obtain a fitness evaluation result; wherein the fitness function is the inverse of the sum of squares of differences between the energy allocation value of the functional module and its output power consumption upper limit; the energy allocation value is the product of the energy allocation ratio and the total power consumption upper limit of the chip; Based on the fitness evaluation result, a genetic algorithm is used to iteratively update the initial population until the fitness evaluation result meets a preset iteration termination condition, and the target energy allocation ratio of each power consumption distribution imbalance module is determined according to the chromosome with the highest current fitness value.

9. The method for adjusting power consumption of an RFID tag chip according to claim 1, wherein: The determining, according to the target energy allocation ratio, the power consumption limit value of each of the power consumption distribution imbalance modules specifically includes: The power consumption limit value of each of the power consumption allocation imbalance modules is determined according to the product of the chip total power consumption upper limit in the chip power consumption constraint condition and each of the target energy allocation ratios.

10. A power consumption adjustment system for an RFID tag chip, characterized in that: include: A thermal effect interference distribution analysis module is used to determine the thermal effect interference distribution information of the target RFID tag chip based on the structural parameters and surface temperature distribution data of the target RFID tag chip; a power consumption distribution imbalance module determination module, configured to determine a plurality of power consumption distribution imbalance modules based on the thermal effect interference distribution information and temperature detection data of each functional module in the target RFID tag chip; A data interaction configuration module, configured to determine a data interaction configuration scheme for each of the power consumption distribution imbalance modules according to the power consumption data of each of the power consumption distribution imbalance modules and preset chip configuration parameters; an energy allocation optimization module, configured to optimize energy allocation for each of the power consumption distribution imbalance modules according to the data interaction configuration scheme and preset chip power consumption constraints, and determine a target energy allocation ratio for each of the power consumption distribution imbalance modules; The output power consumption adjustment module is configured to determine the power consumption limit value of each of the power consumption distribution imbalance modules according to the target energy distribution ratio, and adjust the output power consumption of each of the power consumption distribution imbalance modules according to the power consumption limit value.

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