A dynamic power management adjustment method and system for a main control unit (MCU) of an optical fiber communication type life-saving lighting line

Abstract

The application discloses a kind of dynamic power management regulation methods and systems of optical fiber communication type lifesaving lighting line master MCU, belong to optical fiber lifesaving lighting line technical field, comprising the following steps: the execution times of each type of task in each unit time period is counted, according to the execution times of each type of task, and the power consumption mode adaptability characteristics are calculated by considering task burst condition and task historical trend;According to the power consumption mode adaptability characteristics and in combination with the preset mode switching threshold, the working mode of master MCU is dynamically switched, so that the power consumption of master MCU is matched with the current task load.The scheme designs multiple working modes, considers task burst condition and historical trend of task and other factors, and realizes accurate adjustment of master MCU power consumption by combining dynamic scheduling strategy, reduces power consumption to the maximum extent on the premise of ensuring task processing efficiency, improves the self-sustaining capacity and endurance of equipment.It is suitable for optical fiber communication gateway relying on self-power supply.

Description

Technical Field

[0001] This invention belongs to the field of fiber optic rescue lighting technology, specifically relating to a dynamic power consumption management and adjustment method for the main control MCU of a fiber optic communication rescue lighting line. Background Technology

[0002] Firefighting and rescue lighting cables are indispensable key equipment in scenarios such as fire emergency rescue and temporary outdoor operations, providing lighting guidance and data transmission functions. Traditional firefighting and rescue lighting cables rely on copper conductors as the physical carrier for data transmission. With technological advancements, fiber optic firefighting and rescue lighting cables have gradually emerged. These cables use thinner and lighter communication optical fibers as the data transmission carrier, possessing higher bandwidth and enabling the transmission of large-capacity data such as images and videos. Therefore, they can replace traditional firefighting and rescue lighting cables in multiple application scenarios, thus expanding their application range.

[0003] However, quartz optical fibers themselves lack conductivity, a characteristic that prevents them from transmitting voltage and current to remote terminal devices like traditional cables. Therefore, the remote terminal gateway equipment for fiber optic communication-type emergency lighting lines cannot obtain power from the fiber optic cable and must rely on its own onboard power supply or power from available surrounding equipment. This limitation severely restricts the self-sufficiency and endurance of fiber optic communication equipment in special application scenarios such as temporary outdoor installations or those without external power.

[0004] In fiber optic communication gateway devices, the main control MCU is the core control unit, accounting for over 70% of power consumption. Therefore, the low-power performance of the main control MCU directly determines the overall battery life of the communication gateway. Current technologies often employ fixed modes or simple high-low power switching for main control MCU power management, failing to dynamically adjust power consumption modes based on the actual workload and task priorities. This results in high power consumption even with low workloads, leading to wasted power and further shortening battery life. Conversely, under heavy workloads, untimely power mode switching can impact processing efficiency, causing data transmission delays and data loss. Therefore, a method is urgently needed to dynamically adjust the main control MCU power consumption according to the actual working scenario, balancing battery life and performance.

[0005] Patent application CN117631733A discloses a dynamic power supply voltage adjustment method, an embedded controller, and a system, which: detects the current operating mode of the electronic computing platform; the operating mode includes several operating modes with different power consumption; when the electronic computing platform is in the lowest power consumption operating mode, detects the screen control signal of the electronic computing platform; when the screen control signal is to turn off the screen display, reduces the power supply voltage of the electronic computing platform to a preset target voltage.

[0006] The aforementioned dynamic adjustment method uses an embedded controller to detect the operating frequency of the electronic computing platform and screen control signals. When the detection results indicate that the application scenario requires reduced power consumption, the control core lowers the supply voltage, thereby improving the product's energy efficiency and battery life while maintaining performance. While this improves the product's energy efficiency and battery life, this technical solution focuses primarily on voltage regulation. Research has revealed that other factors also affect power consumption, thus impacting the product's energy efficiency and battery life. Summary of the Invention

[0007] In view of the above, and addressing the problems of limited endurance in existing fiber optic communication-type rescue lighting line remote gateway devices due to the inability to obtain power from fiber optic cables, as well as unreasonable power management of the main control MCU and its inability to dynamically adapt to workload, this invention provides a dynamic power management and adjustment method for the main control MCU of a fiber optic communication-type rescue lighting line. By designing multiple working modes and considering factors such as sudden task situations and historical task trends, combined with a dynamic scheduling strategy, precise adjustment of the main control MCU's power consumption is achieved. This minimizes power consumption while ensuring task processing efficiency, thereby improving the device's self-sufficiency and endurance. This method is applicable to fiber optic communication gateways and similar devices that rely on their own power supply.

[0008] To achieve the aforementioned objectives, this embodiment provides a dynamic power consumption management and adjustment method for the main control MCU of a fiber optic communication-type life-saving lighting line. Based on the four operating modes of the main control MCU, and combined with task scheduling priority and real-time task load, the method dynamically switches the operating modes of the main control MCU to achieve precise power consumption adjustment. Specifically, the method includes the following steps: The number of times each type of task is executed within each unit time period is counted. Based on the number of times each type of task is executed, and taking into account sudden task situations and historical task trends, the power consumption mode adaptability characteristics are calculated. Based on the power consumption mode adaptability characteristics and combined with the preset mode switching threshold, the working mode of the main control MCU is dynamically switched so that the power consumption of the main control MCU matches the current task load.

[0009] In this invention, the main control MCU includes four operating modes, listed in descending order of power consumption: High Speed ​​Mode, Low Speed ​​Mode, Doze Mode, and Sleep Mode. The hardware operating modes supported by the main control MCU are defined as parameters n, where n is an enumerated set of natural integers, and each n value uniquely corresponds to a working mode. Specifically, n=1 corresponds to High Speed ​​Mode, where the main control MCU runs at its highest clock frequency and all peripherals are active; n=2 corresponds to Low Speed ​​Mode, where the main control MCU's clock frequency is reduced to 50% of that in High Speed ​​Mode, and unnecessary peripherals are disabled; n=3 corresponds to Doze Mode, where the main control MCU periodically wakes up to perform task detection, with a wake-up interval of 100ms; and n=4 corresponds to Sleep Mode, where the main control MCU only retains the external interrupt wake-up function, and all other peripherals are disabled. This parameterized definition facilitates unified management and dynamic switching of operating modes by the algorithm.

[0010] The main control MCU is installed on the remote communication gateway of the fiber optic communication-type life-saving lighting line. Its daily scheduling tasks are ordered in descending order of priority weight, including receiving and monitoring, receiving data buffering, receiving and responding, data packet processing, data forwarding, and standby. Specifically, the daily scheduling tasks of the main control MCU are analyzed and each scheduling task is assigned a task scheduling priority weight coefficient. Among them, the receiving and monitoring task has the highest weight coefficient, and the weight coefficients of the other tasks decrease in descending order of priority, with the standby task having the lowest weight coefficient.

[0011] Preferably, the power consumption pattern adaptability characteristics are calculated based on the number of times each type of task is executed, taking into account unexpected task events and historical task trends, including: in, For power mode adaptive features, The time period is measured in seconds. For task indexing, N This represents the total number of task types. Tasks within a unit time period T is the number of times it is executed. For the task The scheduling priority weight coefficient, This is a historical trend factor for the task, reflecting the degree of deviation of the current load from the historical average level. This is a task burst factor, which is only taken when the current load is significantly higher than the historical average. and They are respectively and The adjustment coefficient, ranging from 0 to 0.5, is used to balance the influence weights of trend factors and sudden factors. Task volume can be quantified as the number of task executions per unit time (times / second) or the amount of data transmitted (bytes / second).

[0012] More preferably, the task historical trend factor is calculated using the following formula: in, This represents the base load for the current cycle. This is the historical load average, taken from the previous M periods. The average value, The historical load fluctuation level is represented by values ​​from the previous M periods. The standard deviation is M, which is the number of historical reference periods. It can be adjusted according to system memory and response requirements, and the value range is 5-10 periods. The larger the value of M, the more stable the statistical analysis is but the greater the response delay. The smaller the value of M, the faster the response but the greater the statistical fluctuation.

[0013] More preferably, the task suddenness factor is calculated using the following formula: in, For the current cycle's base load, This is the historical average load. This represents the degree of historical load fluctuation.

[0014] More preferably, the task scheduling priority weight coefficient The value range is 0-10, where the weight coefficient of the receiving and monitoring task is... Set to 10, the weight coefficient for the received data caching task. Set to 8, the weighting coefficient for receiving the response task. Set to 7, the weighting coefficient for the packet processing task. Set to 6, the weight coefficient for the data forwarding task. Set to 5, the weighting coefficient for standby tasks. Set it to 0; of course, the weighting coefficient... It can be adjusted according to the importance of the task in the actual application scenario.

[0015] More preferably, the unit time period T can be adjusted according to the actual application scenario, with a value range of 100ms-1000ms (i.e. 0.1s-1.0s). The intermediate value of 500ms (0.5s) is preferred as the unit time period T, which takes into account both the real-time performance and stability of power consumption adjustment. A smaller value of period T emphasizes real-time performance, while a larger value of period T emphasizes stability. It can be adjusted according to the actual situation of the project.

[0016] More preferably, the adjustment coefficient and The value is set according to the application scenario requirements, and a typical value is... , , which respectively correspond to the influence weights of the trend factor and the burst factor.

[0017] Preferably, the working mode of the main control MCU is dynamically switched according to the power consumption mode adaptation feature and in combination with a preset mode switching threshold, which includes: The preset mode switching thresholds include s1, s2, s3, and s1>s2>s3; When the power consumption mode adaptation feature s≥s1, the main control MCU switches to the full speed mode (HIGH) to ensure rapid processing of high-priority tasks such as reception monitoring and data caching; When s2≤s<s1, the main control MCU switches to the low speed mode (LOW), which reduces power consumption while ensuring task processing efficiency; When s3≤s<s2, the main control MCU switches to the hiccup mode (DOZE), which starts task processing intermittently to further reduce power consumption; When s<s3, the main control MCU switches to the sleep mode, only retaining the minimum wake-up function for the reception monitoring task to reduce power consumption to the maximum extent.

[0018] Further preferably, the method further comprises: in the sleep mode, when the triggering of the reception monitoring task is detected, the main control MCU is woken up immediately and switched to the corresponding high-power-consumption full speed mode to ensure normal execution of the task.

[0019] To achieve the above invention objective, embodiments of the present invention further provide a dynamic power consumption management and regulation system for a main control MCU of an optical fiber communication type lifesaving lighting line, comprising: an adaptation feature calculation module, configured to count the execution times of various types of tasks in each unit time period, calculate the power consumption mode adaptation feature based on the execution times of various types of tasks, and taking task burst conditions and task historical trends into consideration; a working mode switching module, configured to dynamically switch the working mode of the main control MCU according to the power consumption mode adaptation feature and in combination with the preset mode switching threshold, so that the power consumption of the main control MCU matches the current task load.

[0020] Compared with the prior art, the present invention has at least the following beneficial effects: Aiming at the problems that the optical fiber communication type lifesaving lighting line gateway device cannot be powered by optical fiber and has limited endurance, the present invention focuses on the main control MCU, which is a high-power-consumption core component, and designs a dynamic power consumption management and regulation method, which can significantly reduce the power consumption of the main control MCU, improve the self-sustaining capability and endurance time of the device, and meet the long-time working requirements in external power supply-free scenarios such as outdoor temporary laying.

[0021] This invention sets up four different power consumption levels of working modes, and combines a strategy of fixed priority scheduling with cyclic time slice scheduling based on unit time period. It can dynamically switch working modes according to the amount of tasks and task priorities within a unit time, so as to achieve high-efficiency operation when the task load is high and low-power standby when the task load is low. Under the premise of ensuring task processing efficiency (such as data reception, forwarding and response), it minimizes power consumption waste.

[0022] This invention achieves precise power consumption adjustment by assigning task priorities and calculating power consumption mode adaptability characteristics, avoiding the limitations of traditional fixed power consumption modes. At the same time, each parameter (scheduling priority weight coefficient, unit time period, mode switching threshold) can be flexibly adjusted according to actual application scenarios, adapting to different fiber optic life-saving lighting line application needs, and has strong versatility.

[0023] The method of this invention is simple to implement, requires no additional hardware equipment, and can achieve dynamic power consumption adjustment of the main control MCU through software algorithm optimization. It has low cost, is easy to promote and apply, and can effectively promote the technological upgrade of fiber optic communication-type life-saving lighting lines and expand their application scope. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of the dynamic power consumption management and adjustment method of the main control MCU of the fiber optic communication type life-saving lighting line provided in the embodiment; Figure 2 This is a schematic diagram of the dynamic power consumption management and adjustment system of the main control MCU of the fiber optic communication type life-saving lighting line provided in the embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of this invention.

[0027] This invention provides a dynamic power management and adjustment scheme for the main control MCU of a fiber optic communication-type life-saving lighting line. It is applied to the remote communication gateway of the fiber optic fire rescue lighting line temporarily laid outdoors. The gateway cannot obtain power through fiber optics and relies on the built-in lithium battery for power supply. The main control MCU adopts the STM32L series low-power microcontroller. Its daily scheduling tasks include receiving and listening, receiving data buffering, receiving and responding, data packet processing, data forwarding, and standby.

[0028] The embodiment provides a dynamic power consumption management and adjustment method for the main control MCU of a fiber optic communication-type life-saving lighting line. The input is the time period T, and the scheduling priority weight coefficient W (receive monitoring ( ), receive data buffer ( After receiving the response ( ), packet processing ( ), data forwarding ( ), standby ( Historical reference period number M, adjustment coefficient and And the mode switching thresholds s1, s2, and s3, outputting the working mode n. For example... Figure 1 As shown, the specific steps include: S1 counts the number of times each type of task is executed within each unit time period. Based on the number of times each type of task is executed, and taking into account sudden task situations and historical task trends, it calculates the power consumption mode adaptability characteristics.

[0029] Specifically, first initialize the timer settings and clear the task counter. (i=1,...,N); Initialize the history_queue to be empty with a capacity of M.

[0030] Then execute in each unit time period T: a. Count the number of times each type of task is executed. ; b. Calculate the current cycle base load ; c. Update the historical load queue: Add to history_queue, keeping the queue length at M; d. If the length of history_queue is greater than or equal to M, then: Calculate historical load average ; Calculate the standard deviation of historical loads ; Calculate historical trend factors ; Calculate the suddenness factor of the task ; otherwise: Set H = 0, B = 0 (when historical data is insufficient) e. Calculate the intelligent power consumption adaptation index S2 dynamically switches the operating mode of the main control MCU based on the power consumption mode adaptability characteristics and the preset mode switching threshold, so that the power consumption of the main control MCU matches the current task load.

[0031] Specifically, based on the power consumption mode adaptive characteristics determined in step S1 Determine the working mode n within each unit time period T: If s ≥ s_1, then n = 1 (full speed mode) If s_2 ≤ s < s_1, then n = 2 (low-speed mode) If s_3 ≤ s < s_2, then n = 3 (hiccup mode) If s < s_3, then n = 4 (sleep mode) Then switch the MCU to operating mode n and reset the task counter. Then, proceed to repeat step S1.

[0032] like Figure 2 As shown in the embodiment, a dynamic power consumption management and adjustment system 20 for the main control MCU of a fiber optic communication-type life-saving lighting line is also provided. The system includes an adaptive characteristic calculation module 21 and a working mode switching module 22. The adaptive characteristic calculation module 21 is used to count the number of times various tasks are executed in each unit time period, and calculate the power consumption mode adaptive characteristics based on the number of times various tasks are executed, taking into account sudden task situations and historical task trends. The working mode switching module 22 is used to dynamically switch the working mode of the main control MCU according to the power consumption mode adaptive characteristics and in combination with a preset mode switching threshold, so that the power consumption of the main control MCU matches the current task load.

[0033] The following experimental data demonstrates the technical effectiveness of the dynamic power consumption management and adjustment method of the main control MCU in reducing power consumption and improving self-sufficiency and battery life.

[0034] 1. Experimental Environment and Parameter Configuration Experimental environment and parameter configuration: Actual power consumption in operating mode: 2. Multi-scenario calculation and verification of task historical trend factor H (H factor) and task suddenness factor B (B factor). Scenario 1: Stable load scenario (H≈0, B=0, baseline verification) Scenario description: The gateway device is in a normal monitoring state, and the task load fluctuates slightly around the historical average level. calculate: μ h =35.00, σ h =1.936, H=0.000, B=0.000, s = 70.00, using full-speed mode. Analysis shows that under stable load, H=0, B=0, there is no trend shift or sudden change, and s is determined only by the base load.

[0035] Scenario 2: Scenario with a continuously increasing load (to verify the predictive ability of the H factor) Scenario description: The amount of communication at the rescue site gradually increases, such as the continuous connection of search and rescue personnel and the gradual opening of video streams. calculate: μ h =26.625, σ h =5.765, H=2.667, B=3.845, s = 87.14, using full-speed mode. If H and B factors are not included: s' = 84, although it is still full-speed mode, the H factor increases the s value by 3.14, enhancing the judgment margin.

[0036] Key verification of trend prediction: Load is in a downward trend (historical average 27.625, current...). =9), H=-13.228 (strong negative trend), s (including H)=10.06 → close to hiccup mode, s (without H)=18 → still in low-speed mode (falsely judged as too high). Therefore, we can conclude that the H factor corrects s ​​downwards by having a negative value, allowing it to exit the high-power mode more quickly when the load decreases, thus achieving energy saving.

[0037] Scenario 3: Unexpected Task Scenarios (B-Factor Core Validation) Scenario description: The gateway has been in low-load standby for a long time, and suddenly receives an emergency rescue command, resulting in a large number of data packets flooding in at the same time. Comparative analysis of the various options: Comparison of burst response delays: Formula and calculation of factor B contribution rate: B factor contribution rate = [s( Lc +H+B) - s( L c +H)] / s( L c +H) × 100%= (ε×B) / [ L c + δ×H] × 100% Analysis: Factor B increases the s value by an additional 18%-31% in severe / extreme emergency scenarios, ensuring that the system responds with the highest priority.

[0038] Unified baseline parameter settings: historical σh=2.0, μh=15, T=0.5s, δ=0.3, ε=0.2. The contribution rate of factor B for the four outbreak levels is derived step by step below.

[0039] Level 1: Mild sudden onset ( L c =20, H=2.5) The value in the table is +1.5% (multiple baseline statistical mean). In the case of mild outbreaks, the B value is only 1.0, and the contribution rate itself is very small. The difference between different baselines is about 0.5pp, which is a normal statistical fluctuation in the low sensitivity range.

[0040] Level 2: Moderate Emergency L c =30, H=7.5) The value in the table is +3.8% (statistical mean of multiple baselines). Moderate bursts occur in the transition zone: when baseline μh or σh is high, the B value is suppressed or even zero; when the baseline is stable, the B value is higher. +3.8% reflects the average performance of baseline diversity (σh 1.0~5.0, μh 10~35) in actual operation.

[0041] Level 3: Severe Emergency ( L c =45, H=15.0) The value in the table is +18.5% (multi-baseline statistical mean). Among them, the low baseline extreme scenario (μh=10, σh=1.0): H=35.0, B=33.0, with a single scenario contribution rate of up to +25%. The multi-baseline statistical mean of +18.5% covers the entire spectrum from "high baseline / large fluctuation" (B contribution ≈5%) to "low baseline / small fluctuation" (B contribution ≈25%).

[0042] Level 4: Extreme Sudden Outbreak Lc =60, H=22.5) The value in the table is +31.2% (statistical mean of multiple baselines). Baseline differences are amplified under extreme bursts: in low baseline scenarios (μh=10, σh=1.0), it can reach over +37%, and in high baseline scenarios (μh=35, σh=5.0), it is about +8%. +31.2% reflects that bursts are more likely to occur after a long period of low load (lower μh, smaller σh), causing the statistical mean to shift upward.

[0043] Summary of the contribution rate of the fourth-level B factor:

[0044] Core principle: The contribution rate of the B factor increases non-linearly with the intensity of the outbreak. During mild / moderate outbreaks, the contribution of B is limited (1.5%~3.8%), and the s value mainly depends on the baseline load and the H factor; during severe / extreme outbreaks, the contribution of B increases dramatically (18.5%~31.2%), becoming the main engine for the increase in the s value.

[0045] Analysis: Factor B increases the s value by an additional 18%-31% in severe / extreme emergency scenarios, ensuring that the system responds with the highest priority.

[0046] Scenario 4: Fallback from high load (negative H value accelerates power reduction) Scenario Description: As the rescue mission concludes and communication volume gradually decreases, the system should exit high-power mode as soon as possible to conserve energy.

[0047]

[0048] Comparative analysis of the various options:

[0049] Analysis shows that the H-factor negative trend detection enables the system to quickly exit the high-power mode when the load decreases, saving 59.6% of power compared to the fixed mode.

[0050] 3. Comparative experiment of continuous operation for 24 hours Simulates 24-hour continuous operation of a temporary outdoor paving scenario, including various typical load phases:

[0051] Option A – Traditional Fixed Mode (only two speeds: full speed and low speed, with timed switching):

[0052] Option B – Only base load L_c threshold switching (no H, B factors):

[0053] Compared to Option A, the energy saving is: (760.32-409.52) / 760.32 = 46.14% Scheme C – A complete method including the H+B factor (this invention):

[0054] Comprehensive comparison of the three options:

[0055] Explanation of the differences between Solution C and Solution B: Driven by factors H and B, Solution C proactively increases the proportion of full-speed mode during peak / burst periods to ensure task processing efficiency. The extra power consumption is traded for a significant improvement in burst response capability. Data shows that this trade-off reduces burst response latency by 55.6% and increases throughput by 38.3%.

[0056] 4. Comparison of task processing efficiency Packet processing latency comparison (ms):

[0057] Data throughput comparison (Mbps):

[0058] 5. Independent contribution analysis of the H factor Tests were conducted under the conditions of δ=0.3 and ε=0 (with only the H factor enabled and the B factor disabled):

[0059] * indicates that the early ramp-up during the upward trend consumed additional power, but in exchange for a 18%-25% reduction in task processing latency.

[0060] Formula for calculating additional energy saving rate: Additional power saving rate = (Number of power reduction cycles in advance × Power consumption difference) / Total power consumption of the original solution × 100% Where the power consumption difference = P_original determination mode - P_H determined mode Analysis shows that the H factor contributes significantly during the load reduction phase, and can reduce power consumption in advance through negative trend prediction. The faster the load decreases, the more obvious the power saving effect, with a maximum additional power saving of 6.3%.

[0061] 6. Independent contribution analysis of factor B Burst response testing was conducted under the conditions of δ=0 and ε=0.2 (with only factor B enabled):

[0062] Validation of the adaptive threshold property of factor B:

[0063] Key findings: The 2σh threshold design of the B factor is adaptive: when the load fluctuates greatly, the burst judgment threshold is automatically raised to avoid frequent false triggering of high power consumption mode; when the load is stable for a long time, even a small load increase can be identified as a burst and responded to quickly.

[0064] 7. Analysis of the combined effects of the H factor and the B factor The full formula (δ=0.3, ε=0.2) was used to test the quantification contribution in four typical scenarios:

[0065] Summary of contribution patterns: In scenarios with rising / falling trends, the H factor is the main contributor, and positive / negative values ​​can be used to predict load trends in advance. Emergency Scenarios: The H factor and B factor contribute together – H reflects the degree of “abnormally high load”, and B reflects the absolute magnitude of “exceeding the normal range”; Stable scenario: H≈0, B=0, s degenerates into the calculation of the basic load L_c to avoid erroneous adjustment.

[0066] 8. Parameter sensitivity analysis (1) The influence of the adjustment coefficient δ (trend factor weight), test conditions: ε=0.2 fixed, δ varies from 0 to 0.5, test the upward trend scenario (scenario 2 data):

[0067] Analysis shows that when δ=0.3, the additional power consumption is only 4.5mWh / 24h (about 1% of the total), but it is exchanged for a 1.5-cycle earlier response. The marginal benefit diminishes after δ>0.4, so δ=0.3 is recommended.

[0068] (2) The influence of the adjustment coefficient ε (sudden factor weight), test conditions: δ=0.3 fixed, ε varies from 0 to 0.5, test sudden scenario (scenario 3 data):

[0069] Analysis shows that when ε=0.2, the burst response latency decreases from 2.8ms to 0.8ms (a reduction of 71.4%), and there are no false triggers within 24 hours. False triggers begin to appear after ε≥0.3, therefore ε=0.2 is recommended.

[0070] (3) The effect of unit time period T

[0071] 9. Long-term stability testing in multiple environments (1) Power consumption performance under different temperature environments (24h continuous operation):

[0072] Analysis: Within a wide temperature range of -10°C to 60°C, the energy saving rate remains at 39.5%-40.6%, and the mode switching accuracy remains above 96.8%. The statistical characteristics of the H / B factor (dependent on relative change rather than absolute value) ensure that its decision logic is unaffected by temperature drift.

[0073] (2) Stability during battery voltage decay The stability of mode switching was tested during the simulated discharge of a lithium battery from 4.2V to 3.0V.

[0074] Analysis shows that when the voltage drops to 3.0V (close to the lithium battery discharge termination voltage), the MCU main frequency only decreases from 80.0MHz to 77.2MHz (a decrease of 3.5%). The calculation of the H and B factors is based on task counts rather than absolute time, therefore it is almost unaffected by minor changes in the main frequency. The mode switching accuracy remains consistently above 97.8%.

[0075] The robustness mechanism of the H / B factor to voltage decay: The H factor depends on the relative deviation of L_c ((L_c-μ_h) / σ_h), which is a dimensionless standardized statistic. The decrease in the dominant frequency caused by voltage decay will cause a small synchronous shift (about 3-4%) in the absolute calculated value of L_c, but μ_h and σ_h will also shift synchronously. The proportional change in the numerator and denominator keeps the H value stable (mean fluctuation range -0.03 to +0.12).

[0076] Factor B uses an adaptive threshold of 2σ_h. σ_h is dynamically adjusted according to the slight changes in the MCU's processing rhythm during voltage decay, so the burst judgment threshold always matches the actual operating conditions.

[0077] Occasionally, false triggers occur when the voltage drops below 3.2V (2 times / 48h at 3.0V). This is because the MCU's timer accuracy decreases slightly under the critical voltage, causing minor deviations in task counting in individual cycles. The false trigger rate (2 times / 48h) has a negligible impact on overall power consumption (<0.1%).

[0078] The above data demonstrates that this method is applicable to battery-powered scenarios with unstable supply voltages—during a full discharge process from full charge (4.2V) to critical depletion (3.0V), the statistical determination mechanism of the H / B factor remains robust, and parameters do not need to be recalibrated according to the battery state. This is particularly important in practical rescue scenarios: rescuers do not need to worry about the power management strategy failing due to power loss.

[0079] In conclusion: The effectiveness of the H historical trend factor has been verified: In an upward load trend, the H factor increases the s value by 2.67 (Scenario 2), allowing the system to anticipate load growth in advance and improve response speed; In a downward load trend, the negative correction of the H factor causes the system to trigger power reduction switching 1-3 cycles earlier, and the faster the decline, the more timely the power reduction; The H factor independently contributes an additional power saving of 2.8%-6.3% (declining scenario), while reducing processing latency by 18%-25% in high load scenarios.

[0080] The effectiveness of the B-factor for sudden events was verified: the B-factor is based on an adaptive threshold design of 2σ_h, which is sensitive to sudden events in stable scenarios and automatically suppresses false judgments in fluctuating scenarios; under sudden load scenarios, the B-factor increases the s value by an additional 37.9% (extreme sudden events), and the response latency is reduced from 145.3ms in the fixed mode to 18.9ms (a reduction of 87.0%); in the 24-hour test, the B-factor was not falsely triggered when ε=0.2 was set.

[0081] The comprehensive benefits of the H+B joint mechanism: 24h continuous operation test: Compared with the traditional fixed mode, it saves 40.6% of power and extends the equivalent battery life from 9.74h to 22.13h (an improvement of 127.2%); Compared with the solution that only uses the basic load threshold, although the total power consumption is slightly higher by 10.2%, this "extra power consumption investment" is exchanged for a 55.6% reduction in burst response latency and a 38.3% increase in throughput; The method has good stability in a wide temperature range of -10°C to 60°C and during battery voltage decay, and the mode switching accuracy remains above 96.8%.

[0082] The specific embodiments described above illustrate the technical solution and beneficial effects of the present invention in detail. It should be understood that the above description is only the most preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, additions, and equivalent substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic power consumption management and adjustment method for a fiber optic communication-type life-saving lighting line main control MCU, characterized in that, comprising the following steps: counting the execution times of various types of tasks in each unit time period, calculating power consumption mode adaptability features based on the execution times of various types of tasks, and taking task burst conditions and task historical trends into consideration; dynamically switching the working mode of the main control MCU according to the power consumption mode adaptability features and in combination with a preset mode switching threshold, so that the power consumption of the main control MCU matches the current task load.

2. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 1, characterized in that, calculating the power consumption mode adaptability features based on the execution times of various types of tasks, and taking task burst conditions and task historical trends into consideration comprises: in, For power mode adaptive features, For a unit time period, For task indexing, N This represents the total number of task types. Tasks within a unit time period T is the number of times it is executed. For the task The scheduling priority weight coefficient, This is a historical trend factor for the task, reflecting the degree of deviation of the current load from the historical average level. This is a task burst factor, which is only taken when the current load is significantly higher than the historical average. and They are respectively and The adjustment coefficient, ranging from 0 to 0.5, is used to balance the influence weights of trend factors and sudden factors.

3. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 2, characterized in that, the task historical trend factor is calculated by the following formula: in, This represents the base load for the current cycle. This is the historical load average, taken from the previous M periods. The average value, The historical load fluctuation level is represented by values ​​from the previous M periods. The standard deviation.

4. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 2, characterized in that, the task burst factor is calculated by the following formula: in, For the current cycle's base load, This is the historical average load. This represents the degree of historical load fluctuation.

5. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 1, characterized in that, dynamically switching the working mode of the main control MCU according to the power consumption mode adaptability features and in combination with a preset mode switching threshold comprises: the preset mode switching thresholds comprise s1, s2 and s3, and s1>s2>s3; when the power consumption mode adaptability feature s≥s1, the main control MCU switches to the full-speed mode to ensure fast processing of high-priority tasks; when s2≤s<s1, the main control MCU switches to the low-speed mode, which reduces power consumption while ensuring task processing efficiency; when s3≤s<s2, the main control MCU switches to the burst mode, which starts task processing intermittently to further reduce power consumption; when s<s3, the main control MCU switches to the sleep mode, which only retains the minimum wake-up function for receiving and monitoring tasks to minimize power consumption.

6. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 1, characterized in that, the method further comprises: in the sleep mode, when triggering of the receiving and monitoring task is detected, the main control MCU is woken up immediately and switched to the corresponding high-power full-speed mode.

7. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 2, characterized in that, the value range of the unit time period T is 100ms-1000ms.

8. The dynamic power consumption management and adjustment method for the main control MCU of the fiber optic communication type life-saving lighting line according to claim 2, characterized in that, The weight coefficient of task scheduling priority ranges from 0 to 10, with the weight coefficient of receiving and listening tasks set to 10, the weight coefficient of receiving data buffering tasks set to 8, the weight coefficient of receiving response tasks set to 7, the weight coefficient of data packet processing tasks set to 6, the weight coefficient of data forwarding tasks set to 5, and the weight coefficient of standby tasks set to 0. , .

9. A dynamic power consumption management and adjustment system for a fiber optic communication-type life-saving lighting line main control MCU, characterized in that, comprising: an adaptability feature calculation module, which is configured to count the execution times of various types of tasks in each unit time period, and calculate power consumption mode adaptability features based on the execution times of various types of tasks, and taking task burst conditions and task historical trends into consideration; a working mode switching module, which is configured to dynamically switch the working mode of the main control MCU according to the power consumption mode adaptability features and in combination with a preset mode switching threshold, so that the power consumption of the main control MCU matches the current task load.

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