A solar energy lithium electric street lamp dynamic light attenuation self-adaptive energy-saving regulation method, device and equipment

Abstract

The application discloses a solar lithium electric street lamp dynamic light decay self-adaptive energy-saving regulation method, device and equipment. The application belongs to the technical field of street lamp intelligent control. The method comprises the following steps: collecting multi-source time sequence data such as photovoltaic panel output, lithium battery SOC, internal resistance, voltage, temperature, ambient light intensity and road surface illuminance; calculating a theoretical output voltage drop, calculating apparent illuminance loss caused by the battery voltage drop, obtaining real illuminance loss caused by LED chip aging; taking the photovoltaic effective power generation as an energy hard constraint, solving the maximum light decay compensation amount and the target road surface illuminance reference value; calculating the pre-compensation theoretical illuminance and the preliminary PWM duty cycle; collecting real-time road surface illuminance calculation error and correcting the duty cycle; iteratively updating the lithium battery aging index and storing it for next night regulation. The application can accurately distinguish the apparent light decay caused by LED self-decay and lithium battery voltage drop, maintain the target road surface illuminance, prevent the battery from over-discharging, and prolong the service life of the system.

Description

Technical Field

[0001] This application belongs to the field of intelligent street light control technology, specifically relating to a method, device, and equipment for dynamic light decay adaptive energy-saving regulation of solar lithium circuit lights. Background Technology

[0002] Solar-powered lithium-ion streetlights are widely used in municipal roads, rural roads, and park lighting due to their advantages such as zero wiring and low carbon emissions. However, LED light sources experience nonlinear light decay under long-term high temperature and humidity environments, while lithium batteries experience increased internal resistance and reduced effective capacity after hundreds of cycles, leading to a significant decrease in actual road surface illuminance over the years. Existing control schemes often use fixed PWM duty cycles or simple on / off control based on ambient light intensity, failing to detect the true aging state of the light source and battery, often resulting in problems such as "new lights being too bright and wasting energy, while old lights are too dim and do not meet standards." Some improved schemes attempt to introduce photosensors for feedback dimming or linearly adjust brightness based on the lithium battery's SOC, but these still confuse LED light decay with the illuminance reduction caused by battery voltage drop. The voltage drop caused by increased battery internal resistance also leads to reduced road surface illuminance. If these are indiscriminately attributed to LED aging and the drive current is blindly increased to compensate, not only will the target illuminance not be restored, but the deep discharge of the lithium battery will be accelerated, shortening the system's lifespan. Furthermore, existing solutions generally lack energy budget constraints and periodic self-calibration mechanisms, failing to dynamically balance the trade-off between maintaining illuminance and ensuring battery life during long-term operation. This leads to frequent battery over-discharge protection and even system shutdowns during cloudy or rainy weather. Therefore, there is an urgent need for an adaptive control method that can decouple light source aging from battery voltage drop interference and balance illuminance compensation with energy safety. Summary of the Invention

[0003] This application provides a method, device, and equipment for dynamic light decay adaptive energy-saving control of solar lithium circuit lights, aiming to solve the technical problems of existing solar street lights that cannot distinguish between the light decay of the LED itself and the apparent light decay caused by the voltage drop of the lithium battery, blind compensation leading to battery over-discharge, and illuminance not meeting the standards.

[0004] In a first aspect, embodiments of this application provide a method for dynamic light decay adaptive energy-saving control of a solar lithium circuit lamp, the method comprising: S1 collects multi-source time-series sensing data of solar lithium circuit lights, including: photovoltaic panel output voltage and current data, lithium battery SOC, output terminal voltage, internal resistance, battery temperature, ambient light intensity, actual road surface illuminance, and timestamp. S2, calculate the theoretical output voltage drop based on the current SOC, internal resistance and discharge current of the lithium battery, and estimate the road surface apparent illuminance loss corresponding to the lithium battery voltage drop based on the theoretical output voltage drop; subtract the apparent illuminance loss from the measured road surface illuminance loss to obtain the real illuminance loss caused only by the aging of the LED chip itself, and obtain the LED real dynamic light decay index Φ_decay after normalization. S3, calculates the effective photovoltaic power generation on the day, and calculates the lithium battery aging index Ω_aging based on the lithium battery internal resistance change rate, historical cycle number and voltage drop characteristics under low temperature conditions. S4 uses the effective photovoltaic power generation of the day as the upper limit of the energy hard constraint, and combines the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay to calculate the maximum allowable light decay compensation Δ_max and the target road surface illuminance benchmark value E_target. S5, perform light decay pre-compensation on the target road surface illuminance reference value E_target based on the LED real dynamic light decay index Φ_decay to obtain the pre-compensated theoretical illuminance E_theo, and output the corresponding preliminary LED drive PWM duty cycle D_pre; S6, collect the real-time actual road surface illuminance E_actual, calculate the illuminance error, and correct the PWM duty cycle based on the illuminance error to obtain D_fb; S7, after the current day and night charging and discharging cycle ends, uses the road surface illuminance, lithium battery parameters and photovoltaic power generation data collected throughout the cycle to iteratively update Φ_decay, removes abnormal samples of lithium battery voltage drop, adopts a gradient weighted sliding update method, stores the updated Φ_decay for the next day and night regulation, and outputs D_fb to the LED constant current drive module.

[0005] Furthermore, after step S6, the method further includes: Identify the current street light operating conditions, including normal nighttime operating conditions, late-night low-pedestrian-flow operating conditions, and rainy / rainy low-power-output operating conditions; For different operating conditions, the corresponding illuminance correction coefficient is applied to E_target to obtain the corrected target value E_target'. Based on E_target', the feedback closed-loop correction of S6 is re-executed to obtain the final duty cycle D_final and output to the LED constant current drive module. Among them, the illuminance correction coefficient is less than 1.0 under the operating conditions of low traffic at night and low power generation in rainy weather, and the target illuminance is lowered to reduce the compensation power consumption.

[0006] Furthermore, the operating condition identification method is as follows: If the ambient light intensity is lower than the light-on threshold and the current time is not within the preset late-night time range, it is identified as a normal nighttime working condition. If the preset late-night time threshold is reached, it will be identified as a late-night low-traffic situation. If the effective photovoltaic power generation on a given day is lower than the preset power generation threshold, it will be identified as a low power generation condition due to cloudy or rainy weather. Among them, the illuminance correction factor for low-population conditions at night is 0.7-0.9, and the illuminance correction factor for low-power conditions during cloudy and rainy weather is 0.6-0.8. In addition, the upper limit of the maximum light attenuation compensation Δ_max is prohibited from being called under the conditions of low-power conditions during cloudy and rainy weather.

[0007] Furthermore, step S2 includes: The ohmic voltage drop is calculated using the following formula based on the equivalent internal resistance R_int of the lithium battery and the real-time discharge current I_dis: ; By looking up the table based on the current SOC, the corresponding open-circuit voltage OCV for this SOC range is obtained, and the theoretical terminal voltage is calculated using the following formula: ; The apparent illuminance loss ratio caused by the lithium battery voltage drop is obtained by mapping the theoretical terminal voltage V_term with the volt-ampere characteristics of the LED driver. The ratio of the measured road surface illuminance to the baseline illuminance without pressure drop is taken as the total illuminance loss ratio. After subtracting the apparent illuminance loss ratio, the true illuminance loss ratio caused only by the aging of the LED chip itself is obtained, and then normalized to obtain Φ_decay.

[0008] Furthermore, the formula for calculating the lithium battery aging index Ω_aging in step S3 is as follows: ; Where R_int0 is the factory reference internal resistance, N_cycle is the cumulative number of cycles, N_rated is the rated cycle life, ΔV_cold is the voltage drop increment coefficient under low temperature conditions relative to normal temperature, and α, β, and γ are preset weighting coefficients, all of which are greater than 0.

[0009] Furthermore, the calculation of the maximum allowable optical attenuation compensation amount Δ_max in step S4 satisfies the following constraints: The compensation power consumption P_comp corresponding to Δ_max satisfies: ; Where T_night is the duration of nighttime lighting, E_pv_valid is the effective photovoltaic power generation on the day, η_batt is the overall discharge efficiency of the lithium battery, and E_reserve(Ω_aging) is the minimum reserve capacity that increases with Ω_aging. When Ω_aging exceeds the preset aging threshold, an attenuation factor k(Ω_aging)∈(0,1] is applied to Δ_max, and the larger Ω_aging is, the smaller the attenuation factor is.

[0010] Furthermore, step S6 includes: Real-time monitoring of lithium battery SOC; When the SOC of the lithium battery drops below the safe discharge depth threshold corresponding to the current Ω_aging, D_fb is forcibly clamped to the maximum allowable duty cycle under the lithium battery SOC, and the light decay pre-compensation operation is stopped. The basic lighting is maintained by using the low power consumption duty cycle of the remaining nighttime to amortize the current SOC.

[0011] Furthermore, step S7 includes: For each cycle, the candidate light decay index Φ_candidate is calculated. If the lithium battery voltage drop is abnormal in the current cycle, the data for that cycle is discarded; otherwise, it is updated as follows: ; Wherein, λ_n is the learning rate weight of the nth cycle, and the sum of λ_n in recent cycles is greater than the sum of λ_n in early cycles, so that Φ_decay tracks the nonlinear aging trend of LED without being disturbed by a single abnormal sampling jump. When Φ_decay_new is lower than the preset severe light decay threshold, a light source fault warning signal is generated, light decay compensation is stopped, and the system switches to a low-power fixed duty cycle mode.

[0012] Secondly, embodiments of this application provide a dynamic light decay adaptive energy-saving control device for solar lithium circuit lamps, comprising: The multi-source data acquisition module is used to collect multi-source time-series sensing data of solar lithium circuit lights, including: photovoltaic panel output voltage and current data, lithium battery SOC, output terminal voltage, internal resistance, battery temperature, ambient light intensity, actual road surface illuminance, and timestamp. The apparent light decay decoupling module is used to calculate the theoretical output voltage drop based on the current SOC, internal resistance and discharge current of the lithium battery, and to estimate the road surface apparent illuminance loss corresponding to the lithium battery voltage drop based on the theoretical output voltage drop; the measured road surface illuminance loss is subtracted from the apparent illuminance loss to obtain the real illuminance loss caused only by the aging of the LED chip itself, and after normalization, the real dynamic light decay index Φ_decay of the LED is obtained. The aging assessment module is used to count the effective photovoltaic power generation on the day, and to calculate the lithium battery aging index Ω_aging based on the lithium battery internal resistance change rate, historical cycle number and voltage drop characteristics under low temperature conditions. The joint budget module is used to calculate the maximum allowable light decay compensation Δ_max and the target road illuminance benchmark value E_target, by taking the effective photovoltaic power generation of the day as the upper limit of the energy hard constraint, and combining the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay. The feedforward pre-compensation module is used to perform light decay pre-compensation on the target road surface illuminance reference value E_target based on the LED real dynamic light decay index Φ_decay, to obtain the pre-compensated theoretical illuminance E_theo, and output the corresponding preliminary LED drive PWM duty cycle D_pre; The feedback correction module is used to collect the real-time actual road surface illuminance E_actual, calculate the illuminance error, and correct the PWM duty cycle based on the illuminance error to obtain D_fb; The periodic self-calibration module is used to iteratively update Φ_decay after the current day-night charge-discharge cycle ends, using the road surface illuminance, lithium battery parameters and photovoltaic power generation data collected throughout the cycle. Abnormal samples of lithium battery voltage drop are removed. The updated Φ_decay is stored for the next day-night regulation using a gradient weighted sliding update method, and D_fb is output to the LED constant current drive module.

[0013] Thirdly, this application provides a dynamic light decay adaptive energy-saving control device for solar lithium circuit lamps, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps as described above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0015] The technical solution provided in this application decouples the apparent light decay caused by lithium battery voltage drop from the light decay of the LED itself due to aging, thereby achieving precise compensation of road illuminance. By combining the hard constraint of photovoltaic energy with the dynamic limit of battery aging level to limit the maximum compensation amount, the system can maintain the target illuminance while preventing over-discharge of the battery. The light decay index is updated iteratively by periodic self-calibration, so that the control parameters track the nonlinear aging trend of the device in the long term, taking into account both lighting quality and system life. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of the solar lithium circuit lamp dynamic light decay adaptive energy-saving control device provided in the embodiments of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0018] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0019] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0020] The following description, in conjunction with the accompanying drawings, details the method, apparatus, equipment, and medium for dynamic light decay adaptive energy-saving control of solar lithium circuit lamps provided in this application, through specific embodiments and application scenarios.

[0021] Example 1 Figure 1 This is a schematic flowchart of the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps provided in Embodiment 1 of this application. Figure 1 As shown, the specific steps include the following: S1 collects multi-source time-series sensing data of solar lithium circuit lights, including: photovoltaic panel output voltage and current data, lithium battery SOC, output terminal voltage, internal resistance, battery temperature, ambient light intensity, actual road surface illuminance, and timestamp. Solar lithium circuit lights refer to off-grid road lighting equipment that is equipped with photovoltaic panels, lithium battery energy storage modules, and LED lighting heads.

[0022] Multi-source time-series sensing data refers to a dataset collected from multiple different sensors with added time stamps.

[0023] Photovoltaic panel output voltage and current data refer to the measured values ​​of output voltage and output current when the photovoltaic panel is generating electricity.

[0024] SOC (State of Charge) refers to the parameter that characterizes the percentage of the remaining usable capacity of a lithium battery relative to its rated total capacity.

[0025] Output voltage refers to the voltage value detected at the output port of the lithium battery for external power supply.

[0026] Internal resistance refers to the measured value of the equivalent internal resistance of the lithium battery cell.

[0027] Battery temperature refers to the temperature sampling data collected inside the lithium battery module.

[0028] Ambient light intensity refers to the intensity of natural light illuminating the location where the street light is installed.

[0029] Actual road surface illuminance refers to illuminance data collected by road surface illuminance sensors, reflecting the true lighting level at the illuminated locations on the road.

[0030] A timestamp is a time-series marker that marks the exact moment each set of collected data occurs.

[0031] Specifically, various physical parameters can be read through external physical sensors and a lithium battery BMS (Battery Management System), and a timestamp can be added to each set of read parameters to complete the acquisition of multi-source time-series sensing data.

[0032] S2, calculate the theoretical output voltage drop based on the current SOC, internal resistance and discharge current of the lithium battery, and estimate the road surface apparent illuminance loss corresponding to the lithium battery voltage drop based on the theoretical output voltage drop; subtract the apparent illuminance loss from the measured road surface illuminance loss to obtain the real illuminance loss caused only by the aging of the LED chip itself, and obtain the LED real dynamic light decay index Φ_decay after normalization. Theoretical output voltage drop refers to the theoretically calculated value of the voltage decrease caused by the consumption of internal resistance of the battery cell during the discharge process of a lithium battery.

[0033] The apparent illuminance loss on the road surface refers to the decrease in road surface illuminance caused solely by the voltage drop of the lithium battery or insufficient power supply output. This decrease in illuminance is not caused by the aging of LED devices.

[0034] The measured road surface illuminance loss refers to the total illuminance loss collected from the current road surface compared to the standard illuminance calibrated by the LED manufacturer.

[0035] LED chip aging refers to the aging phenomenon of LED chips, where the performance of internal light-emitting materials deteriorates and luminous efficiency decreases after prolonged operation.

[0036] True illuminance loss refers to the illuminance loss that is entirely due to the aging of the LED chip itself, after eliminating interference caused by the voltage drop of the lithium battery.

[0037] Φ_decay refers to the true dynamic light decay index of an LED, which is a dimensionless normalized parameter. The larger the value, the more severe the light decay of the LED chip.

[0038] Specifically, the system can read and obtain parameters such as SOC, internal resistance, and discharge current, calculate the theoretical output voltage drop of the lithium battery, and combine the mapping relationship of the LED driver's volt-ampere characteristics to calculate the apparent illuminance loss of the road surface. By subtracting the apparent illuminance loss from the measured road surface illuminance loss, the system can obtain the true illuminance loss corresponding to the aging of the LED chip itself. Then, it can perform a normalization operation to output the true dynamic light decay index Φ_decay of the LED.

[0039] S3, calculates the effective photovoltaic power generation on the day, and calculates the lithium battery aging index Ω_aging based on the lithium battery internal resistance change rate, historical cycle number and voltage drop characteristics under low temperature conditions. The effective photovoltaic power generation on a given day refers to the available electrical energy that can be used for LED lighting after deducting the standby power consumption of the controller and sensors from the total electrical energy generated by the photovoltaic panels during the period from sunrise to sunset.

[0040] The rate of change of internal resistance refers to the proportion of change in the current internal resistance of a lithium battery relative to its factory-set reference internal resistance.

[0041] Historical cycle count refers to the total number of complete charge-discharge cycles of a lithium battery.

[0042] Low-temperature voltage drop characteristics refer to the characteristic parameters of the voltage drop amplitude of lithium battery terminals under low-temperature discharge conditions.

[0043] Ω_aging refers to the lithium battery aging index, a dimensionless parameter. The larger the value, the higher the degree of aging and deterioration of the lithium battery.

[0044] The effective photovoltaic power generation of the day can be obtained by reading photovoltaic voltage and current data within the time series and performing integration statistics. The internal resistance, cycle record, and low temperature voltage drop characteristics of lithium batteries can be collected, and the weighted calculation can be completed by configuring preset weight coefficients to output the lithium battery aging index Ω_aging.

[0045] S4 uses the effective photovoltaic power generation of the day as the upper limit of the energy hard constraint, and combines the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay to calculate the maximum allowable light decay compensation Δ_max and the target road surface illuminance benchmark value E_target. The energy hard constraint upper limit refers to the value that the total electricity consumption of streetlights at night cannot exceed, in order to prevent nighttime electricity consumption from exceeding the available electricity collected by photovoltaics during the day.

[0046] The maximum allowable light decay compensation amount Δ_max refers to the maximum increase in illuminance that the system is allowed to use to compensate for LED light decay, which is limited by both photovoltaic power generation and battery aging.

[0047] The target road surface illuminance reference value E_target refers to the basic target illuminance of the road surface that meets the road lighting specifications and is not subject to light attenuation compensation.

[0048] This scheme can use the effective photovoltaic power generation of the day as the boundary condition, substitute it with the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay for calculation, and calculate and solve to obtain the maximum allowable light decay compensation Δ_max and the target road surface illuminance benchmark value E_target.

[0049] S5, perform light decay pre-compensation on the target road surface illuminance reference value E_target based on the LED real dynamic light decay index Φ_decay to obtain the pre-compensated theoretical illuminance E_theo, and output the corresponding preliminary LED drive PWM duty cycle D_pre; Light decay pre-compensation refers to feedforward processing logic that pre-increases the target illuminance based on the degree of LED light decay, in order to offset the decrease in brightness caused by LED chip aging.

[0050] The pre-compensated theoretical illuminance E_theo refers to the theoretical road surface illuminance that the system expects to achieve after completing the light attenuation pre-compensation.

[0051] PWM (Pulse Width Modulation) is a driving control method that adjusts the output brightness of an LED by relying on the duty cycle of a pulse signal.

[0052] The initial LED driver PWM duty cycle D_pre refers to the duty cycle value output by the feedforward pre-compensation stage, which has not yet been corrected by feedback from the actual road surface illuminance.

[0053] Specifically, it can read Φ_decay to perform light decay pre-compensation operation on E_target, calculate the pre-compensation theoretical illuminance E_theo, and then convert it according to the LED driving characteristic mapping relationship to output the preliminary LED driving PWM duty cycle D_pre.

[0054] S6, collect the real-time actual road surface illuminance E_actual, calculate the illuminance error, and correct the PWM duty cycle based on the illuminance error to obtain D_fb; Real-time road surface illuminance E_actual refers to the actual road surface illuminance collected in real time by sensors during the lighting operation phase.

[0055] Illuminance error refers to the difference between the pre-compensated theoretical illuminance E_theo and the real-time actual illuminance E_actual on the road surface.

[0056] D_fb refers to the PWM duty cycle after feedback correction based on the actual road surface illuminance.

[0057] Continuously read data from the road surface illuminance sensor to obtain E_actual, compare it with E_theo to solve for the illuminance error, use the illuminance error to perform closed-loop correction on D_pre, and obtain the duty cycle D_fb after feedback correction.

[0058] S7, after the current day and night charging and discharging cycle ends, uses the road surface illuminance, lithium battery parameters and photovoltaic power generation data collected throughout the cycle to iteratively update Φ_decay, removes abnormal samples of lithium battery voltage drop, adopts a gradient weighted sliding update method, stores the updated Φ_decay for the next day and night regulation, and outputs D_fb to the LED constant current drive module.

[0059] The day-night charge-discharge cycle refers to a complete operating cycle from the daytime photovoltaic charging to the nighttime LED discharge.

[0060] Lithium battery voltage drop anomaly samples refer to the samples collected during the cycle that correspond to abnormal discharge conditions such as overvoltage, undervoltage, and sudden changes in internal resistance of the lithium battery.

[0061] Gradient-weighted sliding update refers to a sliding iteration algorithm where, when periodic data participates in the iteration, periods closer to the current time are assigned higher weights, while earlier historical periods are assigned lower weights.

[0062] An LED constant current drive module is a hardware unit that receives PWM control signals and provides a constant drive current to the LED lamp head.

[0063] In this scheme, after a full day and night charge and discharge cycle is completed, the entire dataset collected in this cycle can be read, samples with abnormal lithium battery voltage drop can be screened out, Φ_decay can be iteratively updated using a gradient weighted sliding update algorithm, the updated exponent can be saved to local storage, and then the D_fb output obtained by feedback correction can be sent to the LED constant current drive module.

[0064] The technical solution provided in this embodiment acquires multiple raw data from photovoltaic, lithium battery, and lighting sources through multi-source time-series sensing. It decouples the apparent light decay caused by the discharge voltage drop of the lithium battery from the actual light decay of the LED chip itself, obtaining the true dynamic light decay index of the LED. Combining the hard constraint of photovoltaic power generation and the aging state of the lithium battery, it solves the upper limit of light decay compensation. It adopts a dual closed-loop control of feedforward light decay pre-compensation plus road illuminance feedback closed loop. At the same time, it iteratively updates the light decay index every day and night cycle. It can compensate for the brightness decay caused by LED aging to ensure road lighting, while not ignoring the aging of the lithium battery and the total power generation of the day. It avoids deep discharge and excessive loss of the lithium battery to compensate for light decay, and realizes the dynamic adaptive energy-saving control of off-grid solar lithium circuit lights.

[0065] In one embodiment, optionally, after step S6, the method further includes: Identify the current street light operating conditions, including normal nighttime operating conditions, late-night low-pedestrian-flow operating conditions, and rainy / rainy low-power-output operating conditions; For different operating conditions, the corresponding illuminance correction coefficient is applied to E_target to obtain the corrected target value E_target'. Based on E_target', the feedback closed-loop correction of S6 is re-executed to obtain the final duty cycle D_final and output to the LED constant current drive module. Among them, the illuminance correction coefficient is less than 1.0 under the operating conditions of low traffic at night and low power generation in rainy weather, and the target illuminance is lowered to reduce the compensation power consumption.

[0066] Street light operating conditions refer to the operating scenarios of street lights, which are determined by combining time, ambient light, and total power generation.

[0067] Normal nighttime operating conditions refer to working scenarios where there is normal traffic and pedestrian flow at night and a complete level of road lighting is required.

[0068] Low-traffic conditions at night refer to work scenarios where there is a significant reduction in pedestrians and vehicles on the road during late-night hours.

[0069] Low power generation during cloudy and rainy weather refers to a working scenario where there is insufficient sunlight during the day and the photovoltaic panels generate insufficient power.

[0070] The illuminance correction factor is a dimensionless coefficient that scales the target road surface illuminance reference value.

[0071] The corrected target value E_target' refers to the road surface illuminance target updated after applying the illuminance correction coefficient.

[0072] The final duty cycle D_final refers to the PWM duty cycle that is finally sent to the driver module after operating condition adaptation.

[0073] Specifically, the current operating condition of the street light can be identified based on the collected environmental, time, and power generation parameters. E_target is multiplied by the illuminance correction coefficient corresponding to the operating condition to obtain E_target'. With E_target' as the new target, the feedback closed-loop correction process of S6 is executed again to calculate D_final and output D_final to the LED constant current drive module.

[0074] This technical solution can differentiate between different road operation scenarios and actively reduce the target illuminance at night or on rainy days to reduce the power consumption caused by light decay compensation. While taking into account basic lighting needs, it saves lithium battery power. For example, in rainy weather when power generation is insufficient, the target illuminance is reduced by a correction coefficient of less than 1 to prevent the lithium battery from being quickly depleted.

[0075] In one embodiment, optionally, the working condition identification method is: If the ambient light intensity is lower than the light-on threshold and the current time is not within the preset late-night time range, it is identified as a normal nighttime working condition. If the preset late-night time threshold is reached, it will be identified as a late-night low-traffic situation. If the effective photovoltaic power generation on a given day is lower than the preset power generation threshold, it will be identified as a low power generation condition due to cloudy or rainy weather. Among them, the illuminance correction factor for low-population conditions at night is 0.7-0.9, and the illuminance correction factor for low-power conditions during cloudy and rainy weather is 0.6-0.8. In addition, the upper limit of the maximum light attenuation compensation Δ_max is prohibited from being called under the conditions of low-power conditions during cloudy and rainy weather.

[0076] The light-on threshold refers to the critical value of ambient light intensity required to turn on streetlights.

[0077] The preset late-night time range refers to a pre-configured time range that represents the time when there are few pedestrians on the road, such as 11 p.m. to 5 a.m.

[0078] The preset late-night time threshold refers to the critical time point at which the judgment of late-night working conditions is triggered.

[0079] The preset power generation threshold refers to the critical value of effective photovoltaic power generation on a given day that distinguishes between normal sunshine and low power generation due to cloudy or rainy weather.

[0080] This solution can read ambient light intensity, system time, and daily photovoltaic power generation, compare various thresholds to determine the operating condition, and match the illuminance correction coefficient for different operating conditions. When the operating condition is determined to be a cloudy or rainy low power generation condition, the controller restricts the program from using the upper limit of the maximum allowable light decay compensation amount Δ_max.

[0081] This technical solution clarifies the feasible operating condition judgment logic, provides a range of directly usable correction coefficient values, and directly locks the compensation upper limit under cloudy and rainy conditions, further protecting limited energy storage and preventing excessive battery consumption due to light decay compensation on nights with poor power generation.

[0082] In one embodiment, optionally, step S2 includes: The ohmic voltage drop is calculated using the following formula based on the equivalent internal resistance R_int of the lithium battery and the real-time discharge current I_dis: ; By looking up the table based on the current SOC, the corresponding open-circuit voltage OCV for this SOC range is obtained, and the theoretical terminal voltage is calculated using the following formula: ; The apparent illuminance loss ratio caused by the lithium battery voltage drop is obtained by mapping the theoretical terminal voltage V_term with the volt-ampere characteristics of the LED driver. The ratio of the measured road surface illuminance to the baseline illuminance without pressure drop is taken as the total illuminance loss ratio. After subtracting the apparent illuminance loss ratio, the true illuminance loss ratio caused only by the aging of the LED chip itself is obtained, and then normalized to obtain Φ_decay.

[0083] Among them, the equivalent internal resistance R_int of the lithium battery refers to the sampled value of the equivalent internal resistance of the lithium battery under operating conditions.

[0084] Real-time discharge current I_dis refers to the real-time discharge current output by the lithium battery.

[0085] Ohmic voltage drop refers to the voltage drop caused by current flowing through the equivalent internal resistance of a lithium battery.

[0086] OCV (Open) Circuit Voltage (open circuit voltage) refers to the open circuit voltage of a lithium battery under no-load discharge conditions.

[0087] The theoretical terminal voltage V_term refers to the theoretical output voltage of a lithium battery after deducting the ohmic voltage drop.

[0088] The current-voltage characteristic mapping of an LED driver refers to a pre-calibrated and stored mapping table that describes the correspondence between input voltage and LED output illuminance.

[0089] Apparent illuminance loss ratio refers to the percentage decrease in illuminance caused by lithium battery voltage drop relative to the baseline illuminance.

[0090] The voltage drop-free reference illuminance refers to the standard illuminance that an LED should output when the lithium battery is under ideal voltage drop conditions.

[0091] The total illuminance loss ratio refers to the percentage of total loss between the current measured illuminance and the baseline illuminance without pressure drop.

[0092] Specifically, R_int and I_dis can be substituted to calculate the ohmic voltage drop of the lithium battery, the current SOC can be read, the open-circuit voltage OCV can be obtained by retrieving the pre-stored lookup table data, the theoretical terminal voltage V_term can be calculated, the apparent illuminance loss ratio can be obtained by querying the driver volt-ampere characteristic mapping table, the total illuminance loss ratio can be calculated, the apparent illuminance loss ratio can be subtracted to obtain the real illuminance loss ratio caused by the aging of the LED itself, and the normalized calculation outputs Φ_decay.

[0093] This technical solution provides a specific implementation path for the calculation. Relying on Ohm's law, open-circuit voltage lookup table, and driver volt-ampere mapping, it realizes the quantitative calculation of apparent light decay caused by lithium battery voltage drop, ensuring the accuracy of the calculation of the true dynamic light decay index of LED.

[0094] In one embodiment, optionally, the formula for calculating the lithium battery aging index Ω_aging in step S3 is: ; Where R_int0 is the factory reference internal resistance, N_cycle is the cumulative number of cycles, N_rated is the rated cycle life, ΔV_cold is the voltage drop increment coefficient under low temperature conditions relative to normal temperature, and α, β, and γ are preset weighting coefficients, all of which are greater than 0.

[0095] This solution can read the internal resistance, cycle count, and low-temperature voltage drop increment of the lithium battery, substitute them into the formula to complete the weighted calculation, and output the lithium battery aging index Ω_aging.

[0096] This technical solution provides a formula for calculating the lithium battery aging index that can be directly applied, while taking into account multiple dimensions such as internal resistance growth, cumulative loss due to cycle count, and low-temperature discharge degradation, so that the lithium battery aging level assessment results are more in line with the actual degradation state of the battery.

[0097] In one embodiment, optionally, the calculation of the maximum allowable optical attenuation compensation amount Δ_max in step S4 satisfies the following constraint relationship: The compensation power consumption P_comp corresponding to Δ_max satisfies: ; Where T_night is the duration of nighttime lighting, E_pv_valid is the effective photovoltaic power generation on the day, η_batt is the overall discharge efficiency of the lithium battery, and E_reserve(Ω_aging) is the minimum reserve capacity that increases with Ω_aging. When Ω_aging exceeds the preset moderate aging threshold, an attenuation factor k(Ω_aging)∈(0,1] is applied to Δ_max, and the larger Ω_aging is, the smaller the attenuation factor becomes.

[0098] Compensation power consumption P_comp refers to the additional LED power required to complete all light decay compensation for Δ_max.

[0099] η_batt refers to the overall discharge efficiency of a lithium battery, which is a comprehensive efficiency parameter that includes cell loss and line loss.

[0100] E_reserve(Ω_aging) refers to the minimum reserve capacity that increases synchronously with the aging index of the lithium battery. The older the battery, the more reserve capacity it has.

[0101] The preset moderate aging threshold refers to the critical value of Ω_aging for determining whether a lithium battery has entered a moderate aging state.

[0102] The aging factor k (Ω_aging) is a coefficient used to reduce the maximum light decay compensation. Its value ranges from greater than 0 to less than or equal to 1. The larger the lithium battery aging index, the smaller the value of this factor.

[0103] Specifically, by inputting nighttime duration, power generation, discharge efficiency, and minimum retained power, the upper limit of compensation power consumption can be calculated to obtain the initial Δ_max. If the lithium battery aging index exceeds the medium aging threshold, the attenuation factor will be applied to Δ_max to further compress the maximum compensation amplitude.

[0104] This technical solution sets dual constraints on the maximum light decay compensation amount. On the one hand, it is constrained by the actual total photovoltaic power generation during the day. On the other hand, the older the lithium battery is, the lower the allowable light decay compensation range becomes, thus preventing deep discharge of the aging battery and extending the overall service life of the lithium battery.

[0105] In one embodiment, optionally, step S6 includes: Real-time monitoring of lithium battery SOC; When the SOC of the lithium battery drops below the safe discharge depth threshold corresponding to the current Ω_aging, D_fb is forcibly clamped to the maximum allowable duty cycle under the lithium battery SOC, and the light decay pre-compensation operation is stopped. The basic lighting is maintained by using the low power consumption duty cycle of the remaining nighttime to amortize the current SOC.

[0106] The safe depth of discharge threshold refers to the minimum state of charge (SOC) value that a lithium battery is allowed to discharge for different lithium battery aging indices. The more severe the battery aging, the higher this threshold.

[0107] Clamping refers to the operational logic that forcibly restricts variables to a range of allowed values.

[0108] The maximum permissible duty cycle refers to the upper limit of the LED driver duty cycle that the lithium battery can safely support under the current SOC conditions.

[0109] Stopping the light decay pre-compensation operation means that the controller no longer executes the illuminance boost feedforward logic driven by Φ_decay.

[0110] The low-power duty cycle that evenly distributes the remaining nighttime lighting time refers to the duty cycle obtained by distributing the remaining lithium battery power evenly to the remaining nighttime lighting time, maintaining only the minimum basic lighting.

[0111] Among them, the SOC of the lithium battery can be continuously read and compared with the safe discharge depth threshold corresponding to Ω_aging. Once the SOC is lower than the threshold, D_fb is forcibly limited to the maximum allowable duty cycle, the light decay pre-compensation is turned off, the remaining power is evenly distributed to the remaining nighttime, and a low power consumption duty cycle is output to ensure basic lighting.

[0112] This technical solution sets up dynamic battery protection logic, which directly terminates light decay compensation when the lithium battery level is close to the safe lower limit, maintaining only the minimum illumination, avoiding the risk of over-discharge damaging the lithium battery, and improving the system's operational safety.

[0113] In one embodiment, optionally, step S7 includes: For each cycle, the candidate light decay index Φ_candidate is calculated. If the lithium battery voltage drop is abnormal in the current cycle, the data for that cycle is discarded; otherwise, it is updated as follows: ; Wherein, λ_n is the learning rate weight of the nth cycle, and the sum of λ_n in recent cycles is greater than the sum of λ_n in early cycles, so that Φ_decay tracks the nonlinear aging trend of LED without being disturbed by a single abnormal sampling jump. When Φ_decay_new is lower than the preset severe light decay threshold, a light source fault warning signal is generated, light decay compensation is stopped, and the system switches to a low-power fixed duty cycle mode.

[0114] The candidate light decay index Φ_candidate refers to the temporary light decay index calculated using the current day-night cycle data and waiting to participate in the iterative update.

[0115] Low-power fixed duty cycle mode refers to a fail-safe operating mode that no longer performs any adaptive compensation and maintains lighting with a fixed low duty cycle.

[0116] Specifically, the candidate light decay index Φ_candidate can be calculated in each complete day-night cycle. If the lithium battery voltage drop is abnormal in this cycle, the sample for that cycle is directly discarded. If there is no abnormality, the sample is obtained by weighted iteration according to the assigned learning rate weights. When the new light decay index reaches the severe light decay threshold, a fault warning is output, all light decay compensation is turned off, and the system switches to a low-power fixed duty cycle mode.

[0117] This technical solution employs weighted iterative updates to avoid drastic jumps in the light decay index caused by single sampling anomalies, adapting to the nonlinear aging pattern of LEDs. It also includes fallback logic for severe light decay faults, triggering an alarm and stopping compensation after excessive aging of the LED, preventing excessive energy consumption to compensate for damaged LEDs, and facilitating timely maintenance and replacement of the lamp holder.

[0118] To enable those skilled in the art to better understand this solution, this application also provides a preferred embodiment.

[0119] This solution operates on an embedded controller at the end of a solar lithium-ion lamp, and its core hardware includes: The STM32L4 series low-power MCU is used as the main controller to execute all control algorithms; Photovoltaic voltage and current sampling uses a voltage divider resistor in conjunction with an INA219 Hall sensor, with an accuracy of ±1%. The lithium battery parameters are sampled using the BQ34Z100-G1 fuel gauge chip, which outputs SOC, internal resistance R_int and battery temperature T_bat. The ambient light intensity sensor uses a BH1750 digital light intensity sensor, which is installed on the top of the light pole facing upwards to collect data. The road surface illuminance sensor uses VEML7700 and is installed at the bottom of the lamp head facing downwards to collect the actual illuminance of the road surface. The LED constant current driver uses the PT4115 step-down constant current driver chip, which receives PWM signals to adjust the output current. The real-time clock uses an external DS3231 to provide timestamps with an accuracy of ±2ppm; the memory uses 128KB of internal Flash memory in the MCU and 4KB of external EEPROM to store historical values ​​of Φ_decay and configuration parameters.

[0120] All sensors have a sampling period of 5 seconds or 10 seconds, and the data is stored in the MCU's circular buffer to form a multi-source timing dataset.

[0121] The specific implementation process of this technical solution is as follows: Step 1: Acquisition of multi-source time-series sensing data; One hour before sunset, the controller obtains a timestamp from the RTC and begins continuously collecting the following data: On the photovoltaic side, it collects the output voltage V_pv(t) and output current I_pv(t) of the photovoltaic panel, with a sampling window from 30 minutes after sunrise to 30 minutes before sunset, for subsequent power generation statistics. On the battery side, it collects the SOC(t), terminal voltage V_term(t), internal resistance R_int(t), and temperature T_bat(t) of the lithium battery. The internal resistance R_int is estimated online using the pulse discharge method, taking a set of voltage and current values ​​before and after each PWM duty cycle transition, and calculating ΔV / ΔI to obtain the instantaneous internal resistance. On the environmental side, it collects the ambient light intensity Lux_env(t) to determine the lighting threshold; in this embodiment, it is set to 30 Lux. On the road surface side, it collects the actual road illuminance Lux_road(t) for feedback loop and light decay calculation. The timestamp t is accurate to the second and is used for timing alignment of the various parameters.

[0122] Step 2: Decouple the apparent attenuation interference and calculate Φ_decay; Ten minutes after the lights are turned on, the LED junction temperature has stabilized, and a baseline decoupling calculation is performed. First, the current discharge current I_dis, i.e., the LED drive current, is read, with a typical value of 1.2A. Then, the current SOC is read, and the open-circuit voltage OCV corresponding to this SOC range is obtained from the table.

[0123] In this embodiment, a SOC-OCV lookup table is established. Under 25°C conditions, the OCV is 3.65V when the SOC is 100%, 3.45V when the SOC is 50%, 3.20V when the SOC is 20%, and 3.05V when the SOC is 10%.

[0124] Next, calculate the theoretical terminal voltage: ; The theoretical output luminous flux ratio η_bat is obtained by mapping V_term_theo to the volt-ampere characteristics of the LED driver. This mapping relationship is obtained through factory calibration experiments and stored as a piecewise linear array. The apparent illuminance loss ratio is 1. η_bat. The calculation method for the total illuminance loss ratio is as follows: ; Lux_road_initial represents the baseline road illuminance for a new lamp at the same power level, stored in Flash memory, with a typical value of 25 Lux. The actual illuminance loss ratio equals the total illuminance loss ratio minus the apparent illuminance loss ratio. Finally, normalization yields Φ_decay = max(0.3, min(1.0, 1...). (Proportion of actual illuminance loss).

[0125] When the battery is fully charged, the apparent illuminance loss is close to 0, and Φ_decay directly reflects the aging of the LED itself; when the battery is low, the apparent loss is deducted to avoid misjudging the battery voltage drop as LED light decay.

[0126] Step 3: Calculate the power generation and Ω_aging; Daily power generation statistics are performed at sunset each day. From sunrise to sunset, the instantaneous power P_pv(t) = V_pv(t) × I_pv(t) is integrated using a trapezoidal integral to obtain the total power generation E_total. Then, the auxiliary power consumption E_aux (including controller standby, sensor polling, RTC, etc., which is approximately 0.5Wh / day in actual measurement) is subtracted to obtain the effective photovoltaic power generation E_pv_valid for the day.

[0127] The lithium battery aging index Ω_aging is calculated once every Monday morning to avoid daily fluctuations. The calculation formula is: ; Where R_int0 is the factory-standard internal resistance, typically 15mΩ; N_cycle is the number of cycles accumulated from the fuel gauge; N_rated is the rated cycle life, 2000 cycles for lithium iron phosphate batteries; ΔV_cold is the voltage drop increment coefficient obtained by dividing the difference between the discharge plateau voltage at T_bat < 10℃ and the plateau voltage at 25℃ by the plateau voltage at 25℃. The weighting coefficients α, β, and γ are 0.4, 0.35, and 0.25, respectively, with internal resistance having the largest weight determined experimentally. Ω_aging ranges from approximately 0 to 1.5, where less than 0.3 indicates a healthy state, 0.3–0.7 indicates moderate aging, and greater than 0.7 indicates severe aging.

[0128] Step 4: Three-dimensional joint evaluation, solving Δ_max and E_target; The inputs are the effective power generation of the day, E_pv_valid, the current aging index, Ω_aging, and the current light decay index, Φ_decay. The target road surface illuminance benchmark value, E_target, is set to 15 Lux under the default normal nighttime conditions, meeting the lighting standards for secondary arterial roads; if it is late at night or in rainy conditions, it is adjusted by the condition adaptation steps in the dependent claims. The calculation process for the maximum allowable light decay compensation, Δ_max, is as follows: First, calculate the basic compensated power consumption budget: ; Where η_batt is the overall discharge efficiency, taken as 0.92, E_reserve is the minimum retained charge, its value is the base retention of 5Wh plus Ω_aging × 10Wh, the more severe the aging, the more is retained, T_night is the nighttime illumination duration from sunset to sunrise the next day, provided by the RTC, typically 11 hours. If Φ_decay is 0.7, i.e., light decay of 30%, then theoretically the required compensation power is P_need = P_base / 0.7 P_base, where P_base is the base power consumption without compensation.

[0129] When P_need ≤ P_budget, Δ_max is P_need, i.e., full compensation; When P_need > P_budget, Δ_max is set to P_budget, i.e., budget clamping.

[0130] Furthermore, if Ω_aging exceeds 0.5, a decay factor k = max(0.3, 1) is applied to Δ_max. Ω_aging), the more severe the aging, the lower the compensation limit.

[0131] Step 5: Feedforward pre-compensation; Pre-compensated theoretical illuminance: ; For example, when E_target is 15 Lux and Φ_decay is 0.7, E_theo is 21.4 Lux. E_theo is converted to the corresponding initial PWM duty cycle D_pre. The target duty cycle is then obtained by looking up a two-dimensional lookup table between the factory-calibrated PWM duty cycle and the road surface illuminance, with a lookup table step of 5%. In a typical scenario, a new lamp with 15 Lux corresponds to D_pre of 45%, while after aging, D_pre needs to be 64%.

[0132] Step Six: Feedback Closed-Loop Correction; The feedback loop executes every 30 seconds to balance response speed and computational overhead. First, it reads the current actual road surface illuminance E_actual and calculates the illuminance error: ; Then, the feedback duty cycle is calculated using proportional adjustment: ; The scaling factor K_p is set to 0.02 / Lux and tuned using the Ziegler-Nichols method. Next, a Δ_max constraint check is performed: D_fb is mapped to the predicted power consumption P_pred using a D-power lookup table. If P_pred exceeds the power consumption limit corresponding to Δ_max, D_fb is clamped to the maximum allowable duty cycle corresponding to that limit. Simultaneously, a battery life safety threshold check is performed: the SOC is read in real-time. If the SOC is lower than SOC_safe(Ω_aging), where SOC_safe = 20%,... 10%×Ω_aging, meaning the more severe the aging, the higher the safety threshold. In this case, D_fb will be clamped to the maximum allowable duty cycle under this SOC, optical decay compensation will be stopped, and the mode will be switched to battery life priority mode.

[0133] In battery life priority mode, the remaining nighttime duration is evenly distributed among the remaining SOC values ​​to calculate the low-power duty cycle: ; Maintain basic lighting.

[0134] Step 7: Periodic self-calibration.

[0135] The periodic self-calibration is performed after each 24-hour charge-discharge cycle, i.e., when the LEDs are turned off after sunrise the following day. First, it extracts the full 24-hour data, including road surface illuminance, SOC, terminal voltage, discharge current, and photovoltaic power generation data every 30 seconds. Then, it removes outliers: if the internal resistance R_int at a sampling point changes abruptly by more than 50%, it is marked as an anomaly; if the SOC shows a non-monotonic jump (e.g., from 40% to 60%), it is marked as an anomaly; the candidate light decay index corresponding to the anomaly point is not included in the update. Next, it calculates the candidate value Φ_candidate, which is the normalized value of the actual illuminance loss ratio obtained from the last decoupling calculation of the cycle.

[0136] Gradient weight sliding update method is used: ; Where λ is the learning rate, the value strategy is as follows: λ is 0.15 for the most recent 7 days, 0.08 for days 7 to 30, and 0.03 for days older than 30, ensuring that recent data is actively updated while long-term trends are not lost. Finally, a severe light decay judgment is performed: if Φ_decay_new is lower than 0.4, that is, the actual luminous flux of the LED is less than 40% of the factory value, a light source fault warning signal is generated and reported to the operation and maintenance platform via NB-IoT or LoRa. At the same time, all subsequent light decay compensation operations are stopped, and the street light is switched to a low-power fixed duty cycle mode with a fixed duty cycle of 30%. The updated Φ_decay_new is written to EEPROM for use in the next 24-hour control.

[0137] The following is a complete operational example of this technical solution in a real-world scenario: At 6:00 AM, sunrise begins, the photovoltaic system starts charging, and the controller starts accumulating the day's power generation. At 6:30 PM, sunset occurs, and the effective power generation for the day, E_pv_valid, is 48Wh, at which point the system begins discharging.

[0138] At 6:35 PM, the ambient light level was below 30 Lux, and the streetlights were turned on. Step two, the decoupling calculation, yielded Φ_decay of 0.68. Steps three and four were then executed, resulting in Δ_max corresponding to a power consumption limit of 3.8W and E_target of 15 Lux.

[0139] Step 5 calculates E_theo to be 22 Lux, and outputs an initial duty cycle D_pre of 66%. From the time the lights are turned on until 6:00 AM the next morning, S6 feedback closed-loop correction is performed every 30 seconds, and the actual road surface illuminance is maintained between 14.5 and 15.5 Lux.

[0140] At 11 PM, the system enters a low-traffic, late-night operating condition, triggering operating condition adaptation. E_target is lowered to 12 Lux, and step six (closed-loop correction) is re-executed. At 6:10 AM the next morning, the lights are turned off, and step seven (cycle self-calibration) is executed. Φ_decay is updated to 0.67, a slight decrease from the previous day's 0.68, and written to EEPROM for use that night.

[0141] Comparison and verification with existing solutions: On the same test platform that had been used for 3 years with lithium iron phosphate batteries and LED streetlights, this solution was compared with two existing solutions over a winter period. The fixed duty cycle solution achieved a road surface illuminance of only 8.2 Lux at the end of the third year, which was seriously substandard.

[0142] The existing SOC linear dimming solution is 11.5 Lux, but it fluctuates greatly. This solution is stable at 14.8 Lux, with the error range controlled within 15±0.5 Lux.

[0143] Regarding battery life under continuous rainy weather, the fixed duty cycle solution shuts down after 1.2 days, the SOC linear dimming solution lasts for 2.1 days, and this solution can last for 3.5 days.

[0144] Regarding the battery capacity retention rate over 3 years, the fixed duty cycle solution achieves 71%, the SOC linear dimming solution achieves 68%, and this solution achieves 76% due to overcompensation accelerating battery degradation.

[0145] Regarding the 3-year light decay tracking error of LED light sources, existing solutions have a deviation of approximately ±18%, while this solution controls it within ±4.2%. The above experimental data fully demonstrates the beneficial effects of this solution in accurately maintaining illuminance, protecting battery life, and ensuring energy safety.

[0146] Example 2 The second embodiment of this application provides a dynamic light decay adaptive energy-saving control device for solar lithium circuit lamps. Figure 2 This is a schematic diagram of the structure of the solar lithium circuit lamp dynamic light decay adaptive energy-saving control device provided in the embodiments of this application. Figure 2 As shown, the device includes The multi-source data acquisition module 210 is used to collect multi-source time-series sensing data of solar lithium circuit lights, including: photovoltaic panel output voltage and current data, lithium battery SOC, output terminal voltage, internal resistance, battery temperature, ambient light intensity, actual road surface illuminance and timestamp. The apparent light decay decoupling module 220 is used to calculate the theoretical output voltage drop based on the current SOC, internal resistance and discharge current of the lithium battery, and to estimate the road surface apparent illuminance loss corresponding to the lithium battery voltage drop based on the theoretical output voltage drop; the measured road surface illuminance loss is subtracted from the apparent illuminance loss to obtain the real illuminance loss caused only by the aging of the LED chip itself, and after normalization, the real dynamic light decay index Φ_decay of the LED is obtained. The aging assessment module 230 is used to count the effective photovoltaic power generation on the day, and to calculate the lithium battery aging index Ω_aging based on the lithium battery internal resistance change rate, historical cycle number and voltage drop characteristics under low temperature conditions. The joint budget module 240 is used to calculate the maximum allowable light decay compensation Δ_max and the target road illuminance benchmark value E_target by taking the effective photovoltaic power generation of the day as the upper limit of the energy hard constraint, and combining the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay. The feedforward pre-compensation module 250 is used to perform light decay pre-compensation on the target road surface illuminance reference value E_target based on the LED real dynamic light decay index Φ_decay, to obtain the pre-compensated theoretical illuminance E_theo, and output the corresponding preliminary LED drive PWM duty cycle D_pre; The feedback correction module 260 is used to collect the real-time actual road surface illuminance E_actual, calculate the illuminance error, and correct the PWM duty cycle based on the illuminance error to obtain D_fb; The periodic self-calibration module 270 is used to iteratively update Φ_decay after the current day and night charge and discharge cycle ends, using the road surface illuminance, lithium battery parameters and photovoltaic power generation data collected throughout the cycle, removing abnormal samples of lithium battery voltage drop, and using a gradient weighted sliding update method to store the updated Φ_decay for the next day and night control, and output D_fb to the LED constant current drive module.

[0147] The solar lithium circuit lamp dynamic light decay adaptive energy-saving control device provided in this application embodiment can realize the various processes and corresponding beneficial effects of the above embodiments. To avoid repetition, it will not be described again here.

[0148] Example 3 This application embodiment also provides a dynamic light decay adaptive energy-saving control device for solar lithium circuit lamps, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps as described above.

[0149] It should be noted that the system provided in this application embodiment can execute the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps as described above, and has corresponding beneficial effects.

[0150] Example 4 This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described embodiment of the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0151] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element. Furthermore, it should be noted that the scope of the methods and systems in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to some examples may be combined in other examples.

[0152] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0153] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above, which are merely illustrative and not restrictive. Those skilled in the art, under the guidance of this application, can make many modifications without departing from the spirit and scope of the claims, all of which fall within the protection scope of this application.

[0154] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.

Claims

1. A solar lithium electric street light dynamic light decay adaptive energy-saving regulation method, characterized in that, The method includes: S1 collects multi-source time-series sensing data of solar lithium circuit lights, including: photovoltaic panel output voltage and current data, lithium battery SOC, output terminal voltage, internal resistance, battery temperature, ambient light intensity, actual road surface illuminance, and timestamp. S2, calculate the theoretical output voltage drop based on the current SOC, internal resistance and discharge current of the lithium battery, and estimate the road surface apparent illuminance loss corresponding to the lithium battery voltage drop based on the theoretical output voltage drop; subtract the apparent illuminance loss from the measured road surface illuminance loss to obtain the real illuminance loss caused only by the aging of the LED chip itself, and obtain the LED real dynamic light decay index Φ_decay after normalization. S3, calculates the effective photovoltaic power generation on the day, and calculates the lithium battery aging index Ω_aging based on the lithium battery internal resistance change rate, historical cycle number and voltage drop characteristics under low temperature conditions. S4 uses the effective photovoltaic power generation of the day as the upper limit of the energy hard constraint, and combines the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay to calculate the maximum allowable light decay compensation Δ_max and the target road surface illuminance benchmark value E_target. S5, perform light decay pre-compensation on the target road surface illuminance reference value E_target based on the LED real dynamic light decay index Φ_decay to obtain the pre-compensated theoretical illuminance E_theo, and output the corresponding preliminary LED drive PWM duty cycle D_pre; S6, collect the real-time actual road surface illuminance E_actual, calculate the illuminance error, and correct the PWM duty cycle based on the illuminance error to obtain D_fb; S7, after the current day and night charging and discharging cycle ends, uses the road surface illuminance, lithium battery parameters and photovoltaic power generation data collected throughout the cycle to iteratively update Φ_decay, removes abnormal samples of lithium battery voltage drop, adopts a gradient weighted sliding update method, stores the updated Φ_decay for the next day and night regulation, and outputs D_fb to the LED constant current drive module.

2. The method of claim 1, wherein, After step S6, the method further includes: Identify the current street light operating conditions, including normal nighttime operating conditions, late-night low-pedestrian-flow operating conditions, and rainy / rainy low-power-output operating conditions; For different operating conditions, the corresponding illuminance correction coefficient is applied to E_target to obtain the corrected target value E_target'. Based on E_target', the feedback closed-loop correction of S6 is re-executed to obtain the final duty cycle D_final and output to the LED constant current drive module. Among them, the illuminance correction coefficient is less than 1.0 under the operating conditions of low traffic at night and low power generation in rainy weather, and the target illuminance is lowered to reduce the compensation power consumption.

3. The method of claim 2, wherein, The operating condition identification method is as follows: If the ambient light intensity is lower than the light-on threshold and the current time is not within the preset late-night time range, it is identified as a normal nighttime working condition. If the preset late-night time threshold is reached, it will be identified as a late-night low-traffic situation. If the effective photovoltaic power generation on a given day is lower than the preset power generation threshold, it will be identified as a low power generation condition due to cloudy or rainy weather. Among them, the illuminance correction factor for low-population conditions at night is 0.7-0.9, and the illuminance correction factor for low-power conditions during cloudy and rainy weather is 0.6-0.

8. In addition, the upper limit of the maximum light attenuation compensation Δ_max is prohibited from being called under the conditions of low-power conditions during cloudy and rainy weather.

4. The method of claim 1, wherein, Step S2 includes: The ohmic voltage drop is calculated using the following formula based on the equivalent internal resistance R_int of the lithium battery and the real-time discharge current I_dis: ； By looking up the table based on the current SOC, the corresponding open-circuit voltage OCV for this SOC range is obtained, and the theoretical terminal voltage is calculated using the following formula: ； The apparent illuminance loss ratio caused by the lithium battery voltage drop is obtained by mapping the theoretical terminal voltage V_term with the volt-ampere characteristics of the LED driver. The ratio of the measured road surface illuminance to the baseline illuminance without pressure drop is taken as the total illuminance loss ratio. After subtracting the apparent illuminance loss ratio, the true illuminance loss ratio caused only by the aging of the LED chip itself is obtained, and then normalized to obtain Φ_decay.

5. The method of claim 1, wherein, The formula for calculating the lithium battery aging index Ω_aging in step S3 is as follows: ； Where R_int0 is the factory reference internal resistance, N_cycle is the cumulative number of cycles, N_rated is the rated cycle life, ΔV_cold is the voltage drop increment coefficient under low temperature conditions relative to normal temperature, and α, β, and γ are preset weighting coefficients, all of which are greater than 0.

6. The method of claim 1, wherein, The calculation of the maximum allowable optical attenuation compensation Δ_max in step S4 satisfies the following constraints: The compensation power consumption P_comp corresponding to Δ_max satisfies: ； Where T_night is the duration of nighttime lighting, E_pv_valid is the effective photovoltaic power generation on the day, η_batt is the overall discharge efficiency of the lithium battery, and E_reserve(Ω_aging) is the minimum reserve capacity that increases with Ω_aging. When Ω_aging exceeds the preset aging threshold, an attenuation factor k(Ω_aging)∈(0,1] is applied to Δ_max, and the larger Ω_aging is, the smaller the attenuation factor is.

7. The method of claim 1, wherein, Step S6 includes: Real-time monitoring of lithium battery SOC; When the SOC of the lithium battery drops below the safe discharge depth threshold corresponding to the current Ω_aging, D_fb is forcibly clamped to the maximum allowable duty cycle under the lithium battery SOC, and the light decay pre-compensation operation is stopped. The basic lighting is maintained by using the low power consumption duty cycle of the remaining nighttime to amortize the current SOC.

8. The method of claim 1, wherein, Step S7 includes: For each cycle, the candidate light decay index Φ_candidate is calculated. If the lithium battery voltage drop is abnormal in the current cycle, the data for that cycle is discarded; otherwise, it is updated as follows: ； Wherein, λ_n is the learning rate weight of the nth cycle, and the sum of λ_n in recent cycles is greater than the sum of λ_n in early cycles, so that Φ_decay tracks the nonlinear aging trend of LED without being disturbed by a single abnormal sampling jump. When Φ_decay_new is lower than the preset severe light decay threshold, a light source fault warning signal is generated, light decay compensation is stopped, and the system switches to a low-power fixed duty cycle mode.

9. A solar lithium electric street light dynamic light decay self-adaptive energy-saving regulation device, characterized in that, include: The multi-source data acquisition module is used to collect multi-source time-series sensing data of solar lithium circuit lights, including: photovoltaic panel output voltage and current data, lithium battery SOC, output terminal voltage, internal resistance, battery temperature, ambient light intensity, actual road surface illuminance, and timestamp. The apparent light decay decoupling module is used to calculate the theoretical output voltage drop based on the current SOC, internal resistance and discharge current of the lithium battery, and to estimate the road surface apparent illuminance loss corresponding to the lithium battery voltage drop based on the theoretical output voltage drop; the measured road surface illuminance loss is subtracted from the apparent illuminance loss to obtain the real illuminance loss caused only by the aging of the LED chip itself, and after normalization, the real dynamic light decay index Φ_decay of the LED is obtained. The aging assessment module is used to count the effective photovoltaic power generation on the day, and to calculate the lithium battery aging index Ω_aging based on the lithium battery internal resistance change rate, historical cycle number and voltage drop characteristics under low temperature conditions. The joint budget module is used to calculate the maximum allowable light decay compensation Δ_max and the target road illuminance benchmark value E_target, by taking the effective photovoltaic power generation of the day as the upper limit of the energy hard constraint, and combining the lithium battery aging index Ω_aging and the LED real dynamic light decay index Φ_decay. The feedforward pre-compensation module is used to perform light decay pre-compensation on the target road surface illuminance reference value E_target based on the LED real dynamic light decay index Φ_decay, to obtain the pre-compensated theoretical illuminance E_theo, and output the corresponding preliminary LED drive PWM duty cycle D_pre; The feedback correction module is used to collect the real-time actual road surface illuminance E_actual, calculate the illuminance error, and correct the PWM duty cycle based on the illuminance error to obtain D_fb; The periodic self-calibration module is used to iteratively update Φ_decay after the current day-night charge-discharge cycle ends, using the road surface illuminance, lithium battery parameters and photovoltaic power generation data collected throughout the cycle. Abnormal samples of lithium battery voltage drop are removed. The updated Φ_decay is stored for the next day-night regulation using a gradient weighted sliding update method, and D_fb is output to the LED constant current drive module.

10. A solar lithium electric street light dynamic light attenuation self-adaptive energy-saving regulation and control device, characterized in that, include: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the dynamic light decay adaptive energy-saving control method for solar lithium circuit lamps as described in any one of claims 1-8.

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