Energy-saving and energy-storage street lamp based on constant voltage driving and CAT1 single lamp control charging and discharging integration

Abstract

The invention relates to the technical field of energy storage street lamps, in particular to an energy-saving energy storage street lamp based on constant voltage driving and CAT1 single lamp control charging and discharging integration, which comprises a lamp shell formed by combining a bottom shell and an upper cover; the LED module is mounted in the bottom shell; the energy storage battery pack is arranged in the bottom shell and is used for providing electric energy for the constant-voltage driving power supply; the constant-voltage driving power supply is used for providing electric energy for the LED module; a CAT1 charging and discharging integrated controller; in combination with an adaptive algorithm, according to the electric quantity of the battery, the power supply stability coefficient of the power grid and the power of the energy storage street lamp, the charging and discharging strategy of the energy storage battery pack is intelligently adjusted, the service life of the battery is prolonged, the energy distribution is optimized, and the energy consumption is reduced; and then the working voltage and current of the energy-saving and energy-storing street lamp are automatically and intelligently adjusted according to the environment lighting requirement and the temperature of the LED module, it is ensured that the lamp operates at the optimal energy efficiency ratio, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage street lamps, and in particular to an energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated. Background Art

[0002] The mainstream energy-saving energy storage street lamp systems on the current market are mostly powered by a combination of photovoltaics and batteries, and use simple PWM (pulse width modulation) or MPPT (maximum power point tracking) control strategies to drive and adjust the brightness of LED street lamps. Among them, some systems introduce simple wireless communication modules for remote monitoring and control.

[0003] The patent application with publication number CN101994976A discloses a wind-solar-mains-electricity complementary street lamp, including a wind turbine, a solar cell module, a wind-solar-mains-electricity charge-discharge controller, an energy storage battery, and a lighting fixture. The wind turbine is arranged at the top of the lamp pole, the solar cell module is arranged on the lamp pole, and is located between the wind turbine and the lighting fixture. The wind-solar-mains-electricity charge-discharge controller is respectively connected to the wind turbine, the solar cell module, the mains, the energy storage battery, and the lighting fixture. The invention uses wind power generation, solar power supply, and mains power to complement each other to power the lighting fixture. When the sun is sufficient, solar power is used for power supply, and when the wind is sufficient, the generator is used for power supply. When both are insufficient, the mains power is used to supplement the power supply. The invention can be used in any area and has the advantages of long life, energy saving, environmental protection, and low cost.

[0004] As mentioned in the above application, the existing energy storage street lamps generally use wind power generation, solar power supply and city power to complement each other to power the lighting fixtures, that is, when the sun is sufficient, solar power is used for power supply, and when the wind is sufficient, generator power is used for power supply. When both are insufficient, the city power is used to supplement the power supply. There is a lack of intelligent management, and most of the existing street lamp control systems can only realize basic switching lights and brightness adjustment functions, lack of intelligent charging and discharging management and street lamp brightness adjustment, which affects the long-term stability and lighting efficiency of the street lamp system. Summary of the invention

[0005] In order to solve the above problems, the present invention provides an energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated.

[0006] The present invention adopts the following technical scheme, based on a constant voltage drive and CAT1 single lamp control charging and discharging integrated energy-saving energy storage street lamp, including:

[0007] A lamp housing, which is composed of a bottom housing and an upper cover;

[0008] An LED module is installed in the bottom shell;

[0009] An energy storage battery pack, which is installed in the bottom shell and is used to provide electric energy to the constant voltage driving power supply;

[0010] Constant voltage driving power supply, used to provide power to the LED module;

[0011] CAT1 integrated charging and discharging controller, the CAT1 integrated charging and discharging controller comprises:

[0012] A first data collection module collects historical power supply comprehensive parameters of the energy-saving energy storage street lamp, wherein the historical power supply comprehensive parameters include power supply characteristic parameters and power supply type;

[0013] The first data analysis module trains a machine learning model for predicting the power supply type of the energy-saving energy storage street lamp based on the collected historical power supply comprehensive parameters, collects real-time power supply characteristic parameters of the energy-saving energy storage street lamp, predicts the power supply type of the energy-saving energy storage street lamp based on the trained machine learning model, and controls the power supply type of the energy-saving energy storage street lamp based on the predicted power supply type of the energy-saving energy storage street lamp;

[0014] A second data acquisition module collects comprehensive energy storage street lamp control parameters of the energy-saving energy storage street lamp, wherein the comprehensive energy storage street lamp control parameters include the required level of ambient lighting brightness, the power supply type of the energy storage street lamp, and the LED module temperature;

[0015] The second data analysis module inputs the ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the LED module temperature into a pre-built energy storage street lamp control parameter recommendation model to obtain the energy storage street lamp control parameter recommendation set label, thereby obtaining the energy storage street lamp control parameter recommendation set corresponding to the energy storage street lamp control parameter recommendation set label, and controls the operating parameters of the LED module based on the energy storage street lamp control parameters in the energy storage street lamp control parameter recommendation set to control the operation of the LED module.

[0016] As a further description of the above technical solution: the bottom shell is formed by integral die-casting or stamping of a metal plate, the outer edge of the bottom shell is stamped upward to form a connecting outer edge, the upper cover is buckled on the connecting outer edge of the bottom shell, and a mounting hole is provided between the bottom shell and the upper cover, which are connected and fixed with bolts to ensure the connection strength between the bottom shell and the upper cover.

[0017] As a further description of the above technical solution: the LED module consists of a PCB board, LED lamp beads and a driver chip installed on the PCB board, and a module shell that wraps, protects and connects the PCB board, LED lamp beads and the driver chip, wherein the module shell is made of aluminum alloy or plastic.

[0018] As a further description of the above technical solution: the power supply characteristic parameters include battery power, power supply stability coefficient of the power grid and energy storage street lamp power, and the power supply type includes battery power supply and mains power supply;

[0019] Parameters affecting the power supply stability coefficient of the power grid include voltage fluctuation, load fluctuation and power grid frequency fluctuation;

[0020] The calculation expression of the power supply stability coefficient of the power grid is as follows:

[0021] ;

[0022] In the formula, is the power supply stability factor, For voltage fluctuations, For load fluctuation, The grid frequency fluctuates. , and is the weight factor, , and Both are greater than 0.

[0023] As a further description of the above technical solution: the training method of the machine learning model for training and predicting the power supply type of the energy-saving energy storage street lamp includes:

[0024] Converting the collected historical power supply comprehensive parameters into a corresponding set of first eigenvectors;

[0025] Each group of first feature vectors is used as the input of the machine learning model, the machine learning model takes the power supply type corresponding to each group of power supply characteristic parameters as the output, the power supply type actually corresponding to each group of power supply characteristic parameters is used as the prediction target, and minimizing the loss function value of the machine learning model is used as the training target; training is stopped when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

[0026] As a further description of the above technical solution: the recommended set of energy storage street lamp control parameters is:

[0027] ;

[0028] in, The collection label is The corresponding street lamp working voltage is The collection label is The corresponding street lamp working current.

[0029] As a further description of the above technical solution: the training method of the energy storage street lamp control parameter recommendation model includes:

[0030] Set the recommended set of energy storage street light control parameters with corresponding numbers in advance;

[0031] The ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the LED module temperature are converted into a corresponding set of second eigenvectors, and each set of second eigenvectors is used as the input of the energy storage street lamp control parameter recommendation model. The energy storage street lamp control parameter recommendation model uses a set of energy storage street lamp control parameter recommendation set numbers corresponding to each set of ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the LED module temperature as output, a set of energy storage street lamp control parameter recommendation set numbers actually corresponding to each set of ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the LED module temperature as prediction targets, and minimizing the loss function value of the energy storage street lamp control parameter recommendation model as a training target; and stops training when the loss function value of the energy storage street lamp control parameter recommendation model is less than or equal to a preset second target loss value.

[0032] As a further description of the above technical solution: the method for obtaining the required level of ambient lighting brightness includes:

[0033] Obtain the lighting area where the energy-saving energy storage street lamp is located, and mark the lighting area as the target area;

[0034] Obtain lighting environment parameters and road curvature of the target area;

[0035] The illumination coefficient of the target area is generated based on the lighting environment parameters of the target area and the road curvature analysis, and the ambient lighting brightness requirement level is generated according to the illumination coefficient of the target area.

[0036] As a further description of the above technical solution: the lighting environment parameters include external environment brightness and external environment visibility;

[0037] The method for obtaining the illumination coefficient of the target area includes:

[0038] ;

[0039] In the formula, is the illumination coefficient of the target area, is the external environment brightness, For external environment visibility, is the road curvature, , and is the weight factor, and , and Both are greater than 0.

[0040] As a further description of the above technical solution: the ambient lighting brightness requirement levels include level one lighting brightness, level two lighting brightness, level three lighting brightness and level four lighting brightness, wherein the lighting brightness of level one lighting brightness, level two lighting brightness, level three lighting brightness and level four lighting brightness decreases in sequence.

[0041] The method for generating the required level of ambient lighting brightness according to the illumination coefficient of the target area comprises:

[0042] Predicted illumination coefficient gradient thresholds: G1, G2 and G3, where G1<G2<G3;

[0043] when When <G1, the first level of lighting brightness is generated;

[0044] When G1≤ When <G2, secondary lighting brightness is generated;

[0045] When G2≤ When <G3, three levels of lighting brightness are generated;

[0046] When G3≤ , generates four levels of lighting brightness.

[0047] Beneficial effects:

[0048] The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated provided by the present invention first collects historical power supply comprehensive parameters of the energy-saving energy storage street lamp, trains a machine learning model that predicts the power supply type of the energy-saving energy storage street lamp, collects real-time power supply characteristic parameters of the energy-saving energy storage street lamp, and predicts the power supply type of the energy-saving energy storage street lamp based on the trained machine learning model, that is, in combination with an adaptive algorithm, according to the battery power, the power supply stability coefficient of the power grid and the power of the energy storage street lamp, the energy storage battery pack charging and discharging strategy is intelligently adjusted to extend the battery life, while optimizing energy distribution and reducing energy consumption;

[0049] Furthermore, after obtaining the power supply type of the energy-saving energy storage street lamp, the ambient lighting brightness requirement level and the LED module temperature are obtained in the lighting area of ​​the energy-saving energy storage street lamp, and input into a pre-built energy storage street lamp control parameter recommendation model to obtain the energy storage street lamp control parameter recommendation set label, thereby obtaining the energy storage street lamp control parameter recommendation set corresponding to the energy storage street lamp control parameter recommendation set label, and controlling the LED module operating parameters based on the energy storage street lamp control parameters in the energy storage street lamp control parameter recommendation set, and controlling the LED module operating voltage and operating current, that is, automatically and intelligently adjusting the operating voltage and current of the energy-saving energy storage street lamp according to the ambient lighting requirement, power supply type and LED module temperature, to ensure that the lamp operates at the optimal energy efficiency ratio and improve energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention will be further explained below in conjunction with the accompanying drawings and embodiments:

[0051] Figure 1A schematic diagram of the structure of an energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to an embodiment of the present invention;

[0052] Figure 2 An exploded diagram of an energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to an embodiment of the present invention;

[0053] Figure 3 A module connection diagram of a CAT1 charging and discharging integrated controller provided in an embodiment of the present invention;

[0054] Figure 4 A flowchart of a method for obtaining an ambient lighting brightness requirement level provided by an embodiment of the present invention.

[0055] Figure numerals: 1. lamp housing; 11. bottom housing; 12. upper cover; 2. LED module; 3. energy storage battery pack; 4. constant voltage driving power supply; 5. CAT1 integrated charging and discharging controller. DETAILED DESCRIPTION

[0056] In order to make the technical means, creative features, objectives and effects of the present invention easy to understand, the present invention is further described below with reference to specific diagrams. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0057] Example 1

[0058] See also Figure 1-Figure 3 The embodiment of the present invention provides a technical solution: an energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated, comprising:

[0059] The lamp housing 1 is composed of a bottom shell 11 and an upper cover 12. The bottom shell 11 is formed by integral die-casting or stamping of a metal plate. The outer edge of the bottom shell 11 is stamped upward to form a connecting outer edge. The upper cover 12 is buckled on the connecting outer edge of the bottom shell 11. A mounting hole is also provided between the bottom shell 11 and the upper cover 12, which are connected and fixed with bolts to ensure the connection strength of the bottom shell 11 and the upper cover 12.

[0060] The LED module 2 is installed in the bottom shell 11. The LED module 2 is composed of a PCB board, LED lamp beads and a driver chip installed on the PCB board, and a module shell that wraps and protects the above components and realizes connection with other modules. The module shell is made of aluminum alloy or plastic.

[0061] The energy storage battery pack 3 is installed in the bottom shell 11 and is used to provide electric energy to the constant voltage driving power supply 4.

[0062] A constant voltage driving power supply 4, used to provide power to the LED module 2;

[0063] CAT1 charging and discharging integrated controller 5, the CAT1 charging and discharging integrated controller 5 comprises:

[0064] The first data collection module collects historical power supply comprehensive parameters of the energy-saving and energy storage street lamp, and the historical power supply comprehensive parameters include power supply characteristic parameters and power supply type.

[0065] The power supply characteristic parameters include battery power, power supply stability coefficient of the power grid and energy storage street lamp power, and the power supply types include battery power supply and AC power supply.

[0066] The parameters that affect the power supply stability factor of the power grid include voltage fluctuation, load fluctuation and power grid frequency fluctuation.

[0067] Specifically, voltage fluctuations can be directly monitored by voltage sensors or voltage transformers (VTs) at various nodes in the power grid. Modern voltage sensors are highly accurate and real-time capable of detecting voltage fluctuations.

[0068] The frequency fluctuation of the power grid is collected and acquired through frequency sensors (such as power monitors or frequency meters). The frequency sensors are specifically used to monitor the frequency fluctuation of the power grid.

[0069] Load fluctuations can be obtained through current sensors or current transformers. Current sensors or current transformers are widely used in load monitoring. They transmit load fluctuation information reflected by current changes to the monitoring system.

[0070] The calculation expression of the power supply stability coefficient of the power grid is:

[0071] ;

[0072] In the formula, is the power supply stability factor, For voltage fluctuations, For load fluctuation, The grid frequency fluctuates. , and is the weight factor, , and Both are greater than 0.

[0073] Specifically, the greater the power supply stability coefficient, the worse the power supply quality, and vice versa. It should be noted that the grid frequency is a direct reflection of the balance between power generation and load. If the load is too high and the power generation is insufficient, the frequency will decrease; conversely, if the power generation is in excess and the load is insufficient, the frequency will increase. Large frequency fluctuations usually mean that there is an imbalance between supply and demand in the grid dispatching process. The greater the voltage fluctuation, the worse the grid stability. Load fluctuation refers to the instantaneous change in grid load, which is usually caused by factors such as the start and stop of electrical equipment, climate change, and seasonal fluctuations in electricity demand. The greater the load fluctuation, the greater the impact on grid stability.

[0074] It should be noted that the size of the weight factor is a specific numerical value obtained by quantifying each data to facilitate subsequent comparison. The size of the weight factor depends on the number of parameters that affect the power supply stability coefficient of the power grid and the technical personnel in this field preliminarily set the corresponding weight factor for each group of parameters that affect the power supply stability coefficient of the power grid.

[0075] The first data analysis module trains a machine learning model for predicting the power supply type of the energy-saving energy storage street lamp based on the collected historical comprehensive power supply parameters, collects real-time power supply characteristic parameters of the energy-saving energy storage street lamp, predicts the power supply type of the energy-saving energy storage street lamp based on the trained machine learning model, and controls the power supply type of the energy-saving energy storage street lamp based on the predicted power supply type of the energy-saving energy storage street lamp.

[0076] The second data acquisition module collects the comprehensive energy storage street lamp control parameters of the energy-saving energy storage street lamp, and the comprehensive energy storage street lamp control parameters include the required level of ambient lighting brightness, the power supply type of the energy storage street lamp and the temperature of the LED module 2.

[0077] The training method of the machine learning model for training and predicting the power supply type of the energy-saving energy storage street lamp includes:

[0078] The collected historical power supply comprehensive parameters are converted into a corresponding set of first eigenvectors.

[0079] Each group of first feature vectors is used as the input of the machine learning model, the machine learning model takes the power supply type corresponding to each group of power supply characteristic parameters as the output, the power supply type actually corresponding to each group of power supply characteristic parameters is used as the prediction target, and minimizing the loss function value of the machine learning model is used as the training target; training is stopped when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

[0080] The machine learning model may be one of support vector machine regression, random forest regression or neural network regression models.

[0081] The loss function value of the machine learning model is the mean square error, which is one of the commonly used loss functions. The model is trained with minimization as the goal, so that the machine learning model can better fit the data, thereby improving the performance and accuracy of the model.

[0082] In the loss function is the loss function value of the machine learning model, is the first eigenvector group number; is the number of the first eigenvector groups; For the The power supply type of the energy-saving energy storage street lamp corresponding to the first eigenvector of the group, For the The power supply type of the energy-saving energy storage street lamp corresponding to the first eigenvector of the group in real time.

[0083] Other model parameters of the machine learning model, target loss value, optimization algorithm, training set test set validation set ratio, and loss function optimization are all achieved through actual engineering implementation and continuous experimental tuning.

[0084] The second data analysis module inputs the ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module 2 into a pre-built energy storage street lamp control parameter recommendation model to obtain the energy storage street lamp control parameter recommendation set label, thereby obtaining the energy storage street lamp control parameter recommendation set corresponding to the energy storage street lamp control parameter recommendation set label, and controls the operating parameters of the LED module 2 based on the energy storage street lamp control parameters in the energy storage street lamp control parameter recommendation set to control the operation of the LED module 2.

[0085] The recommended set of energy storage street lamp control parameters is:

[0086] ;

[0087] in, The collection label is The corresponding street lamp working voltage is The collection label is The corresponding street lamp working current.

[0088] The training method of the energy storage street lamp control parameter recommendation model includes:

[0089] The recommended set of energy storage street lamp control parameters is set with corresponding numbers in advance.

[0090] The ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module 2 are converted into a corresponding set of second eigenvectors, and each set of second eigenvectors is used as the input of the energy storage street lamp control parameter recommendation model. The energy storage street lamp control parameter recommendation model uses a set of energy storage street lamp control parameter recommendation set numbers corresponding to each set of ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module 2 as output, a set of energy storage street lamp control parameter recommendation set numbers actually corresponding to each set of ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module 2 as prediction targets, and minimizing the loss function value of the energy storage street lamp control parameter recommendation model as a training target; and stops training when the loss function value of the energy storage street lamp control parameter recommendation model is less than or equal to the preset second target loss value.

[0091] The loss function value of the recommended model for energy storage street lamp control parameters is the mean square error. The mean square error is one of the commonly used loss functions. By converting the loss function: The model is trained with minimization as the goal, so that the energy storage street lamp control parameter recommendation model better fits the data, thereby improving the performance and accuracy of the model.

[0092] In the loss function Recommend model loss function values ​​for energy storage street light control parameters, is the second eigenvector group number; is the number of second eigenvector groups; For the The recommended set number of energy storage street light control parameters predicted by the second eigenvector of the group, For the The recommended set number of the energy storage street lamp control parameters actually corresponding to the second eigenvector of the group.

[0093] Other model parameters of the energy storage street lamp control parameter recommendation model, target loss value, optimization algorithm, training set test set validation set ratio and loss function optimization are all achieved through actual engineering implementation and obtained through continuous experimental tuning.

[0094] In this implementation, firstly, the historical power supply comprehensive parameters of the energy-saving energy storage street lamps are collected to train a machine learning model for predicting the power supply type of the energy-saving energy storage street lamps, and the real-time power supply characteristic parameters of the energy-saving energy storage street lamps are collected. Based on the trained machine learning model, the power supply type of the energy-saving energy storage street lamps is predicted, that is, in combination with an adaptive algorithm, the charging and discharging strategy of the energy storage battery pack 3 is intelligently adjusted according to the battery power, the power supply stability coefficient of the power grid and the power of the energy storage street lamp, thereby extending the battery life, optimizing energy distribution and reducing energy consumption.

[0095] Furthermore, after obtaining the power supply type of the energy-saving energy storage street lamp, the ambient lighting brightness requirement level and the temperature of the LED module 2 are obtained in the lighting area of ​​the energy storage street lamp, and input into the pre-built energy storage street lamp control parameter recommendation model to obtain the energy storage street lamp control parameter recommendation set label, thereby obtaining the energy storage street lamp control parameter recommendation set corresponding to the energy storage street lamp control parameter recommendation set label, and controlling the operating parameters of the LED module 2 based on the energy storage street lamp control parameters in the energy storage street lamp control parameter recommendation set, and controlling the operating voltage and operating current of the LED module 2, that is, automatically and intelligently adjusting the operating voltage and current of the energy-saving energy storage street lamp according to the ambient lighting requirement, power supply type and LED module 2 temperature, to ensure that the lamp operates at the optimal energy efficiency ratio and improve energy utilization efficiency.

[0096] Example 2

[0097] Reference Figure 3-Figure 4 Based on the above embodiment, this embodiment further discloses a method for obtaining the required level of ambient lighting brightness, and the method for obtaining the required level of ambient lighting brightness includes:

[0098] The lighting area where the energy-saving energy storage street lamp is located is obtained, and the lighting area is marked as the target area; it should be noted that the lighting area is a circular area with the street lamp as the center and half the distance between two adjacent street lamps as the radius.

[0099] Obtain the lighting environment parameters and road curvature of the target area.

[0100] The illumination coefficient of the target area is generated based on the lighting environment parameters of the target area and the road curvature analysis, and the ambient lighting brightness requirement level is generated according to the illumination coefficient of the target area.

[0101] The lighting environment parameters include external environment brightness and external environment visibility.

[0102] The method for obtaining the illumination coefficient of the target area includes:

[0103] ;

[0104] In the formula, is the illumination coefficient of the target area, is the external environment brightness, For external environment visibility, is the road curvature, , and is the weight factor, and , and Both are greater than 0.

[0105] Specifically, the greater the illumination coefficient of the target area, the higher the ambient lighting brightness requirement level, and the lower the corresponding lighting brightness requirement, and vice versa; the higher the external environment brightness, the lower the lighting brightness requirement, and vice versa; the higher the external environment visibility, the lower the lighting brightness requirement, and vice versa; the greater the road curvature, the higher the lighting brightness requirement, and vice versa.

[0106] It should be noted that the size of the weight factor in the above formula is to quantify each data to obtain a specific numerical value for the convenience of subsequent comparison. The size of the weight factor of the external environment brightness, external environment visibility and road curvature depends on the external environment brightness, external environment visibility and road curvature and the preliminary setting of the corresponding weight factors by technical personnel in this field.

[0107] The ambient lighting brightness requirement levels include level one lighting brightness, level two lighting brightness, level three lighting brightness and level four lighting brightness, wherein the level one lighting brightness, level two lighting brightness, level three lighting brightness and level four lighting brightness decrease in sequence.

[0108] The method for generating the required level of ambient lighting brightness according to the illumination coefficient of the target area comprises:

[0109] Predicted illumination coefficient gradient thresholds: G1, G2 and G3, where G1<G2<G3;

[0110] when When <G1, the first level of lighting brightness is generated;

[0111] When G1≤ When <G2, secondary lighting brightness is generated;

[0112] When G2≤ When <G3, three levels of lighting brightness are generated;

[0113] When G3≤ , generates four levels of lighting brightness.

[0114] In this embodiment, by obtaining the lighting area where the energy-saving energy storage street lamp is located, and then obtaining the external environment brightness, external environment visibility and road curvature in the lighting area, that is, generating the environmental lighting brightness requirement level based on the specific road environment and road type, on the one hand, energy loss is saved, and secondly, the lighting effect is improved.

[0115] The basic principles, main features and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and the description in the specification are only to illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging, characterized in that: include: A lamp housing (1), which is composed of a bottom housing (11) and an upper cover (12); An LED module (2) mounted in the bottom shell (11); An energy storage battery pack (3), which is installed in the bottom shell (11) and is used to provide electric energy to the constant voltage driving power supply (4); A constant voltage driving power supply (4) for providing electric energy to the LED module (2); A CAT1 integrated charging and discharging controller (5), the CAT1 integrated charging and discharging controller (5) comprising: A first data collection module collects historical power supply comprehensive parameters of the energy-saving energy storage street lamp, wherein the historical power supply comprehensive parameters include power supply characteristic parameters and power supply type; The first data analysis module trains a machine learning model for predicting the power supply type of the energy-saving energy storage street lamp based on the collected historical power supply comprehensive parameters, collects real-time power supply characteristic parameters of the energy-saving energy storage street lamp, predicts the power supply type of the energy-saving energy storage street lamp based on the trained machine learning model, and controls the power supply type of the energy-saving energy storage street lamp based on the predicted power supply type of the energy-saving energy storage street lamp; A second data acquisition module, for collecting comprehensive energy storage street lamp control parameters of the energy-saving energy storage street lamp, wherein the comprehensive energy storage street lamp control parameters include the required level of ambient lighting brightness, the power supply type of the energy storage street lamp and the temperature of the LED module (2); The second data analysis module inputs the ambient lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module (2) into a pre-built energy storage street lamp control parameter recommendation model to obtain an energy storage street lamp control parameter recommendation set label, thereby obtaining an energy storage street lamp control parameter recommendation set corresponding to the energy storage street lamp control parameter recommendation set label, and controls the operating parameters of the LED module (2) based on the energy storage street lamp control parameters in the energy storage street lamp control parameter recommendation set to control the operation of the LED module (2).

2. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 1 is characterized in that: The bottom shell (11) is integrally formed by die-casting or stamping of a metal plate, the outer edge of the bottom shell (11) is stamped upward to form a connecting outer edge, the upper cover (12) is buckled on the connecting outer edge of the bottom shell (11), and a mounting hole is provided between the bottom shell (11) and the upper cover (12), which are connected and fixed with bolts to ensure the connection strength of the bottom shell (11) and the upper cover (12).

3. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 1 is characterized in that: The LED module (2) is composed of a PCB board, LED lamp beads and a driver chip mounted on the PCB board, and a module housing that wraps, protects and connects the PCB board, the LED lamp beads and the driver chip, wherein the module housing is made of aluminum alloy or plastic.

4. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 1 is characterized in that: The power supply characteristic parameters include battery power, power supply stability coefficient of the power grid and energy storage street lamp power, and the power supply types include battery power supply and mains power supply; Parameters affecting the power supply stability coefficient of the power grid include voltage fluctuation, load fluctuation and power grid frequency fluctuation; The calculation expression of the power supply stability coefficient of the power grid is as follows: ； In the formula, is the power supply stability factor, For voltage fluctuations, For load fluctuation, The grid frequency fluctuates. , and is the weight factor, , and Both are greater than 0.

5. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 4 is characterized in that: The training method of the machine learning model for training and predicting the power supply type of the energy-saving energy storage street lamp includes: Converting the collected historical power supply comprehensive parameters into a corresponding set of first eigenvectors; Each group of first feature vectors is used as the input of the machine learning model, the machine learning model takes the power supply type corresponding to each group of power supply characteristic parameters as the output, the power supply type actually corresponding to each group of power supply characteristic parameters is used as the prediction target, and minimizing the loss function value of the machine learning model is used as the training target; training is stopped when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

6. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 1 is characterized in that: The recommended set of energy storage street lamp control parameters is: ； in, The collection label is The corresponding street lamp working voltage is The collection label is The corresponding street lamp working current.

7. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 6 is characterized in that: The training method of the energy storage street lamp control parameter recommendation model includes: Set the recommended set of energy storage street light control parameters with corresponding numbers in advance; The environmental lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module (2) are converted into a corresponding set of second feature vectors, and each set of second feature vectors is used as the input of the energy storage street lamp control parameter recommendation model. The energy storage street lamp control parameter recommendation model uses a set of energy storage street lamp control parameter recommendation set numbers corresponding to each set of environmental lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module (2) as output, uses a set of energy storage street lamp control parameter recommendation set numbers actually corresponding to each set of environmental lighting brightness requirement level, the power supply type of the energy storage street lamp and the temperature of the LED module (2) as prediction targets, and uses minimizing the loss function value of the energy storage street lamp control parameter recommendation model as a training target; and stops training when the loss function value of the energy storage street lamp control parameter recommendation model is less than or equal to a preset second target loss value.

8. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 7 is characterized in that: The method for obtaining the required level of ambient lighting brightness includes: Obtain the lighting area where the energy-saving energy storage street lamp is located, and mark the lighting area as the target area; Obtain lighting environment parameters and road curvature of the target area; The illumination coefficient of the target area is generated based on the lighting environment parameters of the target area and the road curvature analysis, and the ambient lighting brightness requirement level is generated according to the illumination coefficient of the target area.

9. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 8 is characterized in that: The lighting environment parameters include external environment brightness and external environment visibility; The method for obtaining the illumination coefficient of the target area includes: ； In the formula, is the illumination coefficient of the target area, is the external environment brightness, For external environment visibility, is the road curvature, , and is the weight factor, and , and Both are greater than 0.

10. The energy-saving energy storage street lamp based on constant voltage drive and CAT1 single lamp control charging and discharging integrated according to claim 9 is characterized in that: The environmental lighting brightness requirement levels include level one lighting brightness, level two lighting brightness, level three lighting brightness and level four lighting brightness, wherein the level one lighting brightness, level two lighting brightness, level three lighting brightness and level four lighting brightness decrease in sequence; The method for generating the required level of ambient lighting brightness according to the illumination coefficient of the target area comprises: Predicted illumination coefficient gradient thresholds: G1, G2 and G3, where G1<G2<G3; when When <G1, the first level of lighting brightness is generated; When G1≤ When <G2, secondary lighting brightness is generated; When G2≤ When <G3, three levels of lighting brightness are generated; When G3≤ , generates four levels of lighting brightness.

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