A method for balanced output control of solar streetlights with multiple battery modules

Abstract

The present invention relates to the technical field of solar street light battery identification, specifically a method for controlling balanced output of a solar street light with multiple battery modules; determining a suitable battery environment according to battery parameters, identifying and obtaining a theoretical use time; correcting the actual use time by battery history data and the suitable battery environment to obtain a corrected use time; obtaining a battery fatigue coefficient by correcting the use time and the theoretical use time; monitoring the battery working process to obtain battery working data; monitoring the street light lighting area to obtain regional traffic data, regional weather data and regional lighting data; obtaining regional lighting standards by regional traffic data and regional weather data; obtaining a lighting quality coefficient by battery fatigue coefficient, battery working data and regional lighting data; and making judgments by the lighting quality coefficient and the regional lighting standard. The present invention switches batteries according to the judgment results of the lighting quality coefficient and the regional lighting standard to ensure the lighting quality of the solar street light.

Description

Technical Field

[0001] The present invention relates to the technical field of solar street lamp battery identification, and in particular to a method for controlling balanced output of a solar street lamp with multiple battery modules. Background Art

[0002] Solar street lights combine solar power generation equipment with street lights. The solar power generation equipment collects sunlight to generate electricity, and stores the electricity in batteries to power the street lights at night and on cloudy days. Due to the advantages of solar street lights such as energy saving and environmental protection, low maintenance costs, and continuous power supply, they are widely used in urban roads, parks, and campuses.

[0003] During the operation of solar street lights, batteries play the role of storing and transferring electric energy, realizing the input and output of electric energy, and are the core component of the operation of solar street lights. However, frequent charging and discharging as well as deep discharge can easily lead to battery fatigue and failure, affecting the lighting quality of solar street lights.

[0004] In order to relieve the working pressure of the battery and ensure the lighting quality of the street lamp, multiple batteries can be installed in the solar street lamp; on the one hand, it increases the energy storage capacity of the street lamp, improves the endurance of the street lamp, and effectively copes with extreme situations such as bad weather; on the other hand, it ensures the fault tolerance of the solar street lamp. When a battery fails, it can switch to other batteries to increase the stability of the solar street lamp.

[0005] When there are multiple batteries, how to switch batteries is the basis for achieving lighting quality.

[0006] In the prior art, the fault or fatigue degree of the battery is mainly identified and switched based on fixed standards to achieve the purpose of improving power supply efficiency and reducing power supply loss; however, the prior art focuses only on the battery, and does not identify the lighting area of ​​the solar street light, nor does it measure the demand for lighting quality due to traffic flow in the lighting area; resulting in inaccurate identification of battery faults and certain safety hazards.

[0007] Therefore, a balanced output control method for solar street lights with multiple battery modules is proposed. Summary of the invention

[0008] The purpose of the present invention is to provide a balanced output control method for a solar street light with multiple battery modules; determine the suitable environment for the battery according to the battery parameters, and identify the theoretical service life of the battery; correct the actual service life by using the battery history data and the suitable environment for the battery to obtain the corrected service life; obtain the battery fatigue coefficient by using the corrected service life and the theoretical service life; monitor the battery working process to obtain the battery working data; monitor the street light lighting area to obtain the regional traffic data, regional weather data and regional lighting data; obtain the regional lighting standard by using the regional traffic data and regional weather data; obtain the lighting quality coefficient by using the battery fatigue coefficient, the battery working data and the regional lighting data, make a judgment by using the lighting quality coefficient and the regional lighting standard, and switch the battery according to the judgment result to ensure the lighting quality of the solar street light.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] A method for controlling balanced output of a solar street light with multiple battery modules, comprising:

[0011] S10. Identify the battery of the solar street light to obtain the battery usage sequence and battery parameters; determine the battery suitable environment according to the battery parameters; obtain the theoretical battery usage time according to the battery suitable environment; the battery parameters include battery material composition and battery working mechanism;

[0012] S20. Identify the historical working data of the battery to obtain the actual use time of the battery and the historical data of the battery; the historical data of the battery includes historical charging data, historical discharging data and historical environmental data;

[0013] S30. The actual usage time is corrected by the battery history data and the battery suitable environment to obtain the corrected battery usage time; the battery fatigue coefficient is calculated by the corrected usage time and the theoretical usage time;

[0014] S40. Monitor the battery of the working solar street light to obtain battery working data; the battery working data includes continuous working time and temperature change data;

[0015] S50. Determine the lighting coverage of the solar street lamps at work and obtain the lighting area; monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data; identify the regional lighting standards through the regional traffic data and the regional weather data;

[0016] S60. Identify the battery fatigue coefficient, battery operating data and regional lighting data to obtain a lighting quality coefficient; determine whether the lighting quality coefficient meets the regional lighting standard; and switch batteries according to the determination result and the battery usage sequence.

[0017] The process of obtaining the theoretical battery life is as follows:

[0018] Obtain battery parameters, and determine the battery suitable environment based on the battery material composition and battery working mechanism in the battery parameters;

[0019] Conducting experiments in the battery suitable environment to obtain the experimental working time of the battery;

[0020] By conducting experiments on multiple batteries, multiple experimental working times are obtained; the average value of the multiple experimental working times is calculated, and the average value of the experimental working times is used as the theoretical usage time.

[0021] The actual usage time of the battery is the cumulative time after the battery is first activated;

[0022] The historical charging data is the charging data after the battery is first activated, including the battery's charging time data, charging efficiency data and charging temperature data; the historical discharge data is the discharge data after the battery is first activated, including the battery's discharge time data, discharge efficiency data and discharge temperature data; the historical environmental data is the environmental data after the battery is first activated, including ambient temperature, ambient humidity and vibration data.

[0023] The corrected usage time is obtained by using a battery parameter correction model to identify the actual usage time of the battery, battery historical data, and a suitable environment for the battery;

[0024] Identifying and dividing the battery history data according to the charging and discharging behaviors of the battery to obtain first mode data, second mode data, third mode data and fourth mode data;

[0025] By respectively identifying the first mode data, the second mode data, the third mode data and the fourth mode data, a first fitting time length, a second fitting time length, a third fitting time length and a fourth fitting time length are obtained;

[0026] The corrected usage time is obtained through the first fitting time, the second fitting time, the third fitting time and the fourth fitting time.

[0027] The acquisition process of the first mode data, the second mode data, the third mode data and the fourth mode data is as follows:

[0028] Acquire battery history data, and divide the battery operation mode into a first mode, a second mode, a third mode, and a fourth mode according to the battery operation state;

[0029] The first mode is that the battery is neither charged nor discharged; the second mode is that the battery is only in a charging state; the third mode is that the battery is only in a discharging state; the fourth mode is that the battery is in a charging and discharging state at the same time;

[0030] Identify historical data of the battery in a first mode, to obtain first mode data; the first mode data includes first time distribution data, first charge and discharge data and first environment distribution data;

[0031] Identify historical data of the battery in a second mode, and obtain second mode data; the second mode data includes second time distribution data, second charge and discharge data, and second environment distribution data;

[0032] Identify historical data of the battery in a third mode, and obtain third mode data; the third mode data includes third time distribution data, third charge and discharge data, and third environment distribution data;

[0033] Historical data of the battery in a fourth mode is identified in the battery historical data to obtain fourth mode data; the fourth mode data includes fourth time distribution data, fourth charge and discharge data, and fourth environment distribution data.

[0034] The process of obtaining the first fitting duration through the first mode data identification is:

[0035] Acquire first mode data and a battery suitable environment; the first mode data includes first time distribution data, first charge and discharge data, and first environment distribution data;

[0036] Fitting the first time distribution data according to the difference between the first environment distribution data and the suitable environment of the battery and the first charge and discharge data to obtain a first fitting time length;

[0037] Among them, the first time distribution data is the time distribution data when the battery is in the first mode; the first charge and discharge data are the historical charging data and historical discharge data of the battery in the first mode; the first environment distribution data is the historical environment data of the battery in the first mode; since the first mode is that the battery is neither charged nor discharged, the first charge and discharge data is an empty set.

[0038] Monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data;

[0039] The regional traffic data is traffic flow data of the lighting area, including the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed; obtained by a high-definition camera;

[0040] The regional weather data is the weather data of the lighting area; including ambient brightness, temperature data and humidity data; obtained through monitoring by IoT sensors;

[0041] The regional lighting data includes lighting brightness data, color temperature change data and street lamp flicker data of street lamps in the lighting area.

[0042] The process of identifying regional lighting standards through regional traffic data and regional weather data is:

[0043] Constructing a lighting standard recognition model; inputting the regional traffic data and regional weather data into the lighting standard recognition model;

[0044] Identify the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed in regional traffic data to obtain traffic flow characteristics;

[0045] Identify the ambient brightness, temperature and humidity data in the regional weather data to obtain weather data features;

[0046] The traffic flow characteristics and the weather data characteristics are identified to obtain regional lighting standards.

[0047] The process of identifying the lighting quality factor through the battery fatigue factor, battery working data and regional lighting data is:

[0048] Construct lighting quality recognition model;

[0049] Inputting the battery fatigue coefficient, battery operating data and regional lighting data into a lighting quality identification model;

[0050] Identify the battery operation data to obtain battery operation characteristics; identify the regional lighting data to obtain regional lighting characteristics;

[0051] The lighting quality coefficient is obtained by fitting the regional lighting characteristics through the battery fatigue coefficient and the battery working characteristics.

[0052] The determination process of the lighting quality coefficient is as follows:

[0053] Determining whether the lighting quality coefficient meets the regional lighting standard;

[0054] If satisfied, continue to use the current battery; if not satisfied, switch according to the battery usage order and continue to identify and judge the lighting quality;

[0055] When all batteries do not meet the regional lighting standards, select the battery with the lighting quality coefficient closest to the regional lighting standards.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention obtains battery parameters, obtains the battery material composition and the battery working mechanism of the battery; obtains the suitable environment of the battery according to the battery material composition and the battery working mechanism; then obtains the experimental working time of the battery according to the battery suitable environment experiment; and accurately obtains the theoretical use time of the battery by averaging the experimental working time.

[0058] 2. The present invention identifies and divides the battery historical data according to the charging and discharging behavior of the battery to obtain the first mode data, the second mode data, the third mode data and the fourth mode data; according to the different mode data, multiple fitting time lengths are fitted to accurately obtain the corrected usage time length; and then the battery fatigue coefficient is accurately obtained according to the corrected usage time length and the theoretical usage time length.

[0059] 3. The present invention constructs a lighting standard recognition model; regional traffic data is recognized through the lighting standard recognition model to obtain traffic flow characteristics; regional weather data is recognized through the lighting standard recognition model to obtain weather data characteristics; and regional lighting standards are accurately recognized through traffic flow characteristics and weather data characteristics.

[0060] 4. The present invention constructs a lighting quality identification model to identify the battery working data to obtain the battery working characteristics; identify the regional lighting data to obtain the regional lighting characteristics; fit the regional lighting characteristics through the battery fatigue coefficient and the battery working characteristics to accurately obtain the lighting quality coefficient.

[0061] 5. The present invention makes judgments based on the lighting quality coefficient and the regional lighting standard, and selects and switches batteries according to the judgment results; when all batteries do not meet the regional lighting standard, the battery with the lighting quality coefficient closest to the regional lighting standard is selected, effectively ensuring the lighting quality of the street lamp. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a flow chart of a method for controlling balanced output of a solar street light with multiple battery modules according to the present invention;

[0063] Figure 2 It is a structural schematic diagram of the battery parameter correction model of the present invention;

[0064] Figure 3 It is a structural schematic diagram of the lighting standard recognition model of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] The present invention identifies and switches battery failures based on lighting quality requirements of street lamp lighting areas to ensure lighting safety of street lamps.

[0067] Embodiment 1

[0068] The present invention proposes a method for controlling the balanced output of a solar street lamp with multiple battery modules. The process of the method is as follows: Figure 1 As shown, including:

[0069] S10. Identify the battery of the solar street light to obtain the battery usage sequence and battery parameters; determine the battery suitable environment based on the battery parameters; obtain the battery theoretical usage time based on the battery suitable environment; the battery parameters include battery material composition and battery working mechanism.

[0070] Commonly used solar street light batteries include lead-acid batteries, lithium batteries and nickel-metal hydride batteries. Different types of solar street light batteries, as well as different models of solar street light batteries of the same type, have different service lives.

[0071] The battery's suitable environment can be obtained through the battery material composition and the battery's working mechanism. By conducting experiments on the battery's usage time in the battery's suitable environment, its theoretical usage time can be calculated.

[0072] The process of obtaining the theoretical battery life is as follows:

[0073] Obtain battery parameters, and determine the battery suitable environment based on the battery material composition and battery working mechanism in the battery parameters;

[0074] The experimental working time of the battery is obtained through the battery suitable environment experiment;

[0075] By conducting experiments on multiple batteries, multiple experimental working times are obtained; the average value of the multiple experimental working times is calculated, and the average value of the experimental working times is used as the theoretical usage time.

[0076] The present invention obtains battery parameters, obtains battery material composition and battery working mechanism of the battery; obtains a suitable environment of the battery according to the battery material composition and the battery working mechanism; then obtains an experimental working time of the battery according to a battery suitable environment experiment; and accurately obtains a theoretical use time of the battery by averaging the experimental working time.

[0077] S20. Identify the historical working data of the battery to obtain the actual usage time of the battery and the battery historical data; the battery historical data includes historical charging data, historical discharging data and historical environmental data.

[0078] The actual usage time of the battery is the cumulative time after the battery is first activated;

[0079] The historical charging data is the charging data after the battery is first activated, including the battery's charging time data, charging efficiency data and charging temperature data; the historical discharge data is the discharge data after the battery is first activated, including the battery's discharge time data, discharge efficiency data and discharge temperature data; the historical environmental data is the environmental data after the battery is first activated, including ambient temperature, ambient humidity and vibration data.

[0080] The vibration data is data of the vibration of the solar street light battery caused by traffic.

[0081] The present invention identifies the initial activation time of a battery, and obtains the actual usage time of the battery based on the initial activation time; obtains historical charging data, historical discharging data and historical environmental data by monitoring and collecting data after the battery is initially activated; and provides a data basis for identifying battery fatigue conditions.

[0082] S30. Correct the actual usage time according to the battery history data and the battery suitable environment to obtain the corrected usage time of the battery; calculate the battery fatigue coefficient according to the corrected usage time and the theoretical usage time.

[0083] The corrected usage time is obtained by using a battery parameter correction model to identify the actual usage time of the battery, battery historical data, and a suitable environment for the battery;

[0084] The battery parameter correction model is constructed based on the deep neural network model, and its structure is as follows: Figure 2 As shown, it includes a data input layer, a data partitioning layer, a first recognition layer, a second recognition layer, a third recognition layer, a fourth recognition layer and a data output layer;

[0085] The data input layer is used to input the actual usage time, battery history data and battery suitable environment into the model;

[0086] A data division layer, used to identify and divide the battery history data according to the charging and discharging behaviors of the battery to obtain first mode data, second mode data, third mode data and fourth mode data;

[0087] The first recognition layer, the second recognition layer, the third recognition layer and the fourth recognition layer respectively recognize the first mode data, the second mode data, the third mode data and the fourth mode data to obtain the first fitting time, the second fitting time, the third fitting time and the fourth fitting time;

[0088] The data output layer obtains the corrected usage time through the first fitting time, the second fitting time, the third fitting time and the fourth fitting time.

[0089] The present invention identifies and divides battery history data according to the charging and discharging behaviors of the battery to obtain first mode data, second mode data, third mode data and fourth mode data; according to different mode data, a first fitting time, a second fitting time, a third fitting time and a fourth fitting time are fitted to accurately obtain the corrected usage time.

[0090] The acquisition process of the first mode data, the second mode data, the third mode data and the fourth mode data is as follows:

[0091] Acquire battery history data, and divide the battery operation mode into a first mode, a second mode, a third mode, and a fourth mode according to the battery operation state;

[0092] The first mode is that the battery is neither charged nor discharged; the second mode is that the battery is only in a charging state; the third mode is that the battery is only in a discharging state; the fourth mode is that the battery is in a charging and discharging state at the same time;

[0093] Identify historical data of the battery in a first mode, to obtain first mode data; the first mode data includes first time distribution data, first charge and discharge data and first environment distribution data;

[0094] Identify historical data of the battery in a second mode, and obtain second mode data; the second mode data includes second time distribution data, second charge and discharge data, and second environment distribution data;

[0095] Identify historical data of the battery in a third mode, and obtain third mode data; the third mode data includes third time distribution data, third charge and discharge data, and third environment distribution data;

[0096] Historical data of the battery in a fourth mode is identified in the battery historical data to obtain fourth mode data; the fourth mode data includes fourth time distribution data, fourth charge and discharge data, and fourth environment distribution data.

[0097] The present invention divides the modes of the battery based on the working state of the battery to obtain the first mode, the second mode, the third mode and the fourth mode; identifies and divides the battery history data according to the different modes to obtain the first mode data, the second mode data, the third mode data and the fourth mode data; accurately identifies and divides the different stages of the battery, so as to accurately understand the fatigue degree of the battery.

[0098] The process of obtaining the first fitting duration through the first mode data identification is:

[0099] Acquire first mode data and a battery suitable environment; the first mode data includes first time distribution data, first charge and discharge data, and first environment distribution data;

[0100] Fitting the first time distribution data according to the difference between the first environment distribution data and the suitable environment of the battery and the first charge and discharge data to obtain a first fitting time length;

[0101] Among them, the first time distribution data is the time distribution data when the battery is in the first mode; the first charge and discharge data are the historical charging data and historical discharge data of the battery in the first mode; the first environment distribution data is the historical environment data of the battery in the first mode; since the first mode is that the battery is neither charged nor discharged, the first charge and discharge data is an empty set.

[0102] After obtaining data from different working modes, the time distribution data is fitted according to the differences in environmental distribution data, the suitable environment for the battery, and the charge and discharge data to obtain the fitting time; thereby accurately identifying changes in the degree of fatigue of the battery under different modes.

[0103] S40. Monitor the battery of the working solar street light to obtain battery working data; the battery working data includes continuous working time and temperature change data.

[0104] The continuous working time is the cumulative working time of the working battery since the last startup.

[0105] S50. Determine the lighting coverage of the solar street lamps during operation to obtain the lighting area; monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data; and obtain the regional lighting standard by identifying the regional traffic data and the regional weather data.

[0106] Monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data;

[0107] The regional traffic data is the traffic flow data of the lighting area, including the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed; obtained by high-definition camera; wherein the vehicle type is determined based on the appearance of the vehicle, including bicycles, electric vehicles, motorcycles, small cars, large cars, trucks and large trucks; if the vehicle type cannot be determined based on the appearance of the vehicle, it will be classified into the closest vehicle type

[0108] The regional weather data is the weather data of the lighting area; including ambient brightness, temperature data and humidity data; obtained through monitoring by IoT sensors;

[0109] The regional lighting data includes lighting brightness data, color temperature change data and street light flicker data of street lights in the lighting area; the lighting brightness data refers to the change data of street light lighting brightness; the color temperature change data refers to the change data of street light lighting color temperature; the street light flicker data refers to the change data of street light lighting flicker.

[0110] The present invention determines the lighting area of ​​the solar street lamp during operation, obtains regional traffic data, regional weather data and regional lighting data by monitoring the lighting area, and provides a data basis for identifying and judging regional lighting standards.

[0111] The process of identifying regional lighting standards through regional traffic data and regional weather data is:

[0112] Construct a lighting standard recognition model, which is based on a deep neural network model; its structure is as follows Figure 3 As shown, it includes a regional data input layer, a traffic feature recognition layer, a weather feature recognition layer, a feature data fusion layer and a standard data output layer;

[0113] A regional data input layer, inputting the regional traffic data and the regional weather data into the lighting standard recognition model for recognition;

[0114] Traffic feature recognition layer, which recognizes the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed in regional traffic data to obtain traffic flow characteristics;

[0115] The weather feature recognition layer recognizes the ambient brightness, temperature and humidity data in the regional weather data to obtain the weather data features;

[0116] The feature data fusion layer identifies the traffic flow characteristics and weather data characteristics to obtain the regional lighting standards;

[0117] The standard data output layer outputs the regional lighting standard.

[0118] The present invention constructs a lighting standard recognition model; regional traffic data is recognized through the lighting standard recognition model to obtain traffic flow characteristics; regional weather data is recognized through the lighting standard recognition model to obtain weather data characteristics; and regional lighting standards are accurately recognized through traffic flow characteristics and the weather data characteristics.

[0119] S60. Identify the battery fatigue coefficient, battery operating data and regional lighting data to obtain a lighting quality coefficient; determine whether the lighting quality coefficient meets the regional lighting standard; and switch batteries according to the determination result and the battery usage sequence.

[0120] The process of identifying the lighting quality factor through the battery fatigue factor, battery working data and regional lighting data is:

[0121] Constructing a lighting quality recognition model; the lighting quality recognition model is constructed based on a deep neural network model;

[0122] Inputting the battery fatigue coefficient, battery operating data and regional lighting data into a lighting quality identification model;

[0123] Identify the battery operation data to obtain battery operation characteristics; identify the regional lighting data to obtain regional lighting characteristics;

[0124] The lighting quality coefficient is obtained by fitting the regional lighting characteristics through the battery fatigue coefficient and the battery working characteristics.

[0125] The present invention constructs a lighting quality recognition model, identifies the battery working data to obtain the battery working characteristics; identifies the regional lighting data to obtain the regional lighting characteristics; fits the regional lighting characteristics through the battery fatigue coefficient and the battery working characteristics to accurately obtain the lighting quality coefficient.

[0126] The determination process of the lighting quality coefficient is as follows:

[0127] Determining whether the lighting quality coefficient meets the lighting standard of the area;

[0128] If satisfied, continue to use the current battery; if not satisfied, switch according to the battery usage order and continue to identify and judge the lighting quality;

[0129] When all batteries do not meet the regional lighting standards, select the battery with the lighting quality coefficient closest to the regional lighting standards.

[0130] The present invention makes a judgment based on the lighting quality coefficient and the regional lighting standard, and selects and switches the battery based on the judgment result; when all batteries do not meet the regional lighting standard, the battery with the lighting quality coefficient closest to the regional lighting standard is selected to ensure the lighting quality.

[0131] The present invention determines the suitable environment of the battery according to the battery parameters, and identifies the theoretical use time of the battery; corrects the actual use time by using the battery history data and the suitable environment of the battery to obtain the corrected use time; obtains the battery fatigue coefficient by using the corrected use time and the theoretical use time; monitors the battery working process to obtain the battery working data; monitors the street lamp lighting area to obtain the regional traffic data, regional weather data and regional lighting data; obtains the regional lighting standard by using the regional traffic data and regional weather data; obtains the lighting quality coefficient by using the battery fatigue coefficient, the battery working data and the regional lighting data, makes a judgment by using the lighting quality coefficient and the regional lighting standard, switches the battery according to the judgment result, and ensures the lighting quality of the solar street lamp.

[0132] Embodiment 2

[0133] Combined with the actual working conditions of solar street lamps, the present invention proposes a method for controlling the balanced output of solar street lamps with multiple battery modules. The process of the method is as follows: Figure 1 As shown, including:

[0134] S10. Identify the battery of the solar street light to obtain the battery usage sequence and battery parameters; determine the battery suitable environment according to the battery parameters; obtain the theoretical battery usage time according to the battery suitable environment; the battery parameters include battery material composition and battery working mechanism;

[0135] The process of obtaining the theoretical battery life is as follows:

[0136] Obtain battery parameters, and determine the battery suitable environment according to the battery material composition and the battery working mechanism in the battery parameters; obtain the experimental working time of the battery through the battery suitable environment experiment; obtain multiple experimental working times by conducting experiments on multiple batteries; calculate the average value of the multiple experimental times, and use the average value of the experimental working times as the theoretical usage time.

[0137] Taking a certain type of lithium battery solar street light as an example, the solar street light includes 5 batteries of the same type, which are numbered A, B, C, D and E respectively; the suitable environment of the battery is determined according to the battery material composition and battery working mechanism of the lithium battery; then the battery suitable environment is experimentally verified to obtain the theoretical service life; the theoretical service life of this type of lithium battery is 7 years.

[0138] S20. Identify the historical working data of the battery to obtain the actual usage time of the battery and the battery historical data; the battery historical data includes historical charging data, historical discharging data and historical environmental data.

[0139] The actual usage time of the battery is the cumulative time after the battery is first activated;

[0140] The historical charging data is the charging data after the battery is first activated, including the battery's charging time data, charging efficiency data and charging temperature data; the historical discharge data is the discharge data after the battery is first activated, including the battery's discharge time data, discharge efficiency data and discharge temperature data; the historical environmental data is the environmental data after the battery is first activated, including ambient temperature, ambient humidity and vibration data.

[0141] The vibration data is data of the vibration of the solar street light caused by traffic.

[0142] S30. Correct the actual usage time according to the battery history data and the battery suitable environment to obtain the corrected usage time of the battery; calculate the battery fatigue coefficient according to the corrected usage time and the theoretical usage time.

[0143] The corrected usage time is obtained by using a battery parameter correction model to identify the actual usage time of the battery, battery historical data, and a suitable environment for the battery;

[0144] Identifying and dividing the battery history data according to the charging and discharging behaviors of the battery to obtain first mode data, second mode data, third mode data and fourth mode data;

[0145] By respectively identifying the first mode data, the second mode data, the third mode data and the fourth mode data, a first fitting time length, a second fitting time length, a third fitting time length and a fourth fitting time length are obtained;

[0146] The corrected usage time is obtained through the first fitting time, the second fitting time, the third fitting time and the fourth fitting time.

[0147] The acquisition process of the first mode data, the second mode data, the third mode data and the fourth mode data is as follows:

[0148] Acquire battery history data, and divide the battery operation mode into a first mode, a second mode, a third mode, and a fourth mode according to the battery operation state;

[0149] The first mode is that the battery is neither charged nor discharged; the second mode is that the battery is only in a charging state; the third mode is that the battery is only in a discharging state; the fourth mode is that the battery is in a charging and discharging state at the same time;

[0150] Identify historical data of the battery in a first mode, to obtain first mode data; the first mode data includes first time distribution data, first charge and discharge data and first environment distribution data;

[0151] Identify historical data of the battery in a second mode, and obtain second mode data; the second mode data includes second time distribution data, second charge and discharge data, and second environment distribution data;

[0152] Identify historical data of the battery in a third mode, and obtain third mode data; the third mode data includes third time distribution data, third charge and discharge data, and third environment distribution data;

[0153] Historical data of the battery in a fourth mode is identified in the battery historical data to obtain fourth mode data; the fourth mode data includes fourth time distribution data, fourth charge and discharge data, and fourth environment distribution data.

[0154] The process of obtaining the first fitting duration through the first mode data identification is:

[0155] Acquire first mode data and a battery suitable environment; the first mode data includes first time distribution data, first charge and discharge data, and first environment distribution data;

[0156] Fitting the first time distribution data according to the difference between the first environment distribution data and the suitable environment of the battery and the first charge and discharge data to obtain a first fitting time length;

[0157] Among them, the first time distribution data is the time distribution data when the battery is in the first mode; the first charge and discharge data are the historical charging data and historical discharge data of the battery in the first mode; the first environment distribution data is the historical environment data of the battery in the first mode; since the first mode is that the battery is neither charged nor discharged, the first charge and discharge data is an empty set.

[0158] By collecting and identifying data on lithium batteries A, B, C, D and E, the corresponding theoretical usage time, actual usage time and corrected usage time are obtained. The data are shown in Table 1, and the units in the table are all years.

[0159] Table 1 Battery usage time data table

[0160] serial number Theoretical usage time Actual usage time Correction of usage time A 7 2.35 2.44 B 7 2.35 2.82 C 7 2.35 3.08 D 7 2.35 2.51 E 7 2.35 3.16

[0161] S40. Monitor the battery of the working solar street light to obtain battery working data; the battery working data includes continuous working time and temperature change data;

[0162] S50. Determine the lighting coverage of the solar street lamps at work and obtain the lighting area; monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data; identify the regional lighting standards through the regional traffic data and the regional weather data;

[0163] Monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data;

[0164] The regional traffic data is the traffic flow data of the lighting area, including the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed; obtained by a high-definition camera; wherein the vehicle type is determined based on the appearance of the vehicle, including bicycles, electric vehicles, motorcycles, small cars, large cars, trucks and large trucks; if the vehicle type cannot be determined based on the appearance of the vehicle, it will be classified into the closest vehicle type.

[0165] Taking the solar street light as an example, its lighting area is obtained; data of the lighting area is collected to obtain regional traffic data; part of the regional traffic data is shown in Table 2.

[0166] Table 2 Regional traffic data table

[0167] Pedestrian number Pedestrian speed Vehicle number Vehicle Type Vehicle speed R-001 1.36m / s C-001 motorcycle 12.26m / s R-002 0.78m / s C-002 Small car 14.88m / s R-003 1.52m / s C-003 bike 5.67m / s R-004 2.81m / s C-004 Battery car 9.16m / s R-005 0.57m / s C-005 Small car 16.55m / s

[0168] The regional weather data is the weather data of the lighting area; including ambient brightness, temperature data and humidity data; obtained through monitoring by IoT sensors;

[0169] The regional lighting data includes lighting brightness data, color temperature change data and street light flicker data of the lighting area.

[0170] The process of identifying regional lighting standards through regional traffic data and regional weather data is:

[0171] Construct a lighting standard recognition model; input the regional traffic data and the regional weather data into the lighting standard recognition model for recognition; recognize the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed in the regional traffic data to obtain traffic flow characteristics; recognize the ambient brightness, temperature data and humidity data in the regional weather data to obtain weather data characteristics; recognize the traffic flow characteristics and the weather data characteristics to obtain regional lighting standards.

[0172] S60. Identify the battery fatigue coefficient, battery operating data and regional lighting data to obtain a lighting quality coefficient; determine whether the lighting quality coefficient meets the regional lighting standard; and switch batteries according to the determination result and the battery usage sequence.

[0173] The process of identifying the lighting quality factor through the battery fatigue factor, battery working data and regional lighting data is:

[0174] Construct a lighting quality recognition model; input the battery fatigue coefficient, battery working data and regional lighting data into the lighting quality recognition model; identify the battery working data to obtain battery working characteristics; identify the regional lighting data to obtain regional lighting characteristics; fit the regional lighting characteristics through the battery fatigue coefficient and the battery working characteristics to obtain the lighting quality coefficient.

[0175] The determination process of the lighting quality coefficient is as follows:

[0176] Determine whether the lighting quality coefficient meets the regional lighting standard; if so, continue to use the current battery; if not, switch according to the battery usage order, and continue to identify and judge the lighting quality; when all batteries do not meet the regional lighting standard, select the battery with the lighting quality coefficient closest to the regional lighting standard.

[0177] The present invention monitors the solar street lamp lighting area to obtain regional traffic data, regional weather data and regional lighting data; the regional traffic data reflects the traffic flow data of the lighting area, and the regional lighting standard is obtained through the regional traffic data and regional weather data; the regional lighting standard is used to reflect the demand for street lamp lighting by the regional traffic flow under the environment of regional weather data; then the battery fatigue coefficient, battery working data and regional lighting data are identified to obtain the lighting quality coefficient; the lighting quality of the battery is judged by the lighting quality coefficient and the regional lighting standard to ensure lighting safety.

[0178] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling the balanced output of a solar street light with multiple battery modules, characterized in that: include: S10. Identify the battery of the solar street light to obtain the battery usage sequence and battery parameters; determine the battery suitable environment according to the battery parameters; obtain the theoretical battery usage time according to the battery suitable environment; the battery parameters include battery material composition and battery working mechanism; S20. Identify the historical working data of the battery to obtain the actual use time of the battery and the historical data of the battery; the historical data of the battery includes historical charging data, historical discharging data and historical environmental data; S30. Correcting the actual usage time by the battery history data and the battery suitable environment to obtain the corrected battery usage time; The battery fatigue coefficient is calculated by using the corrected usage time and the theoretical usage time; S40. Monitor the battery of the working solar street light to obtain battery working data; the battery working data includes continuous working time and temperature change data; S50. Determine the lighting coverage of the solar street lamps at work and obtain the lighting area; monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data; Identify and obtain regional lighting standards through the regional traffic data and the regional weather data; S60. Identify the battery fatigue coefficient, battery working data and regional lighting data to obtain a lighting quality coefficient; determine whether the lighting quality coefficient meets the regional lighting standard; and switch the battery according to the determination result and the battery use order; The process of identifying the lighting quality factor through the battery fatigue factor, battery working data and regional lighting data is: Constructing a lighting quality recognition model; the lighting quality recognition model is constructed based on a deep neural network model; Inputting the battery fatigue coefficient, battery operating data and regional lighting data into a lighting quality identification model; Identify the battery operation data to obtain battery operation characteristics; identify the regional lighting data to obtain regional lighting characteristics; The lighting quality coefficient is obtained by fitting the regional lighting characteristics through the battery fatigue coefficient and the battery working characteristics.

2. The method for controlling the balanced output of a solar street light with multiple battery modules according to claim 1, characterized in that: The process of obtaining the theoretical battery life is as follows: Obtain battery parameters, and determine the battery suitable environment based on the battery material composition and battery working mechanism in the battery parameters; Conducting experiments in the battery suitable environment to obtain the experimental working time of the battery; By conducting experiments on multiple batteries, multiple experimental working times are obtained; the average value of the multiple experimental working times is calculated, and the average value of the experimental working times is used as the theoretical usage time.

3. The method for controlling the balanced output of a solar street light with multiple battery modules according to claim 1, characterized in that: The actual usage time of the battery is the cumulative time after the battery is first activated; The historical charging data is the charging data after the battery is first activated, including the battery's charging time data, charging efficiency data and charging temperature data; the historical discharge data is the discharge data after the battery is first activated, including the battery's discharge time data, discharge efficiency data and discharge temperature data; the historical environmental data is the environmental data after the battery is first activated, including ambient temperature, ambient humidity and vibration data.

4. The method for controlling the balanced output of a solar street light with multiple battery modules according to claim 1, characterized in that: The corrected usage time is obtained by using a battery parameter correction model to identify the actual usage time of the battery, battery historical data, and a suitable environment for the battery; Identifying and dividing the battery history data according to the charging and discharging behaviors of the battery to obtain first mode data, second mode data, third mode data and fourth mode data; By respectively identifying the first mode data, the second mode data, the third mode data and the fourth mode data, a first fitting time length, a second fitting time length, a third fitting time length and a fourth fitting time length are obtained; The corrected usage time is obtained through the first fitting time, the second fitting time, the third fitting time and the fourth fitting time.

5. A method for controlling balanced output of a solar street light with multiple battery modules according to claim 4, characterized in that: The acquisition process of the first mode data, the second mode data, the third mode data and the fourth mode data is as follows: Acquire battery history data, and divide the battery operation mode into a first mode, a second mode, a third mode, and a fourth mode according to the battery operation state; The first mode is that the battery is neither charged nor discharged; the second mode is that the battery is only in a charging state; the third mode is that the battery is only in a discharging state; the fourth mode is that the battery is in a charging and discharging state at the same time; Identify historical data of the battery in a first mode, to obtain first mode data; the first mode data includes first time distribution data, first charge and discharge data and first environment distribution data; Identify historical data of the battery in a second mode, and obtain second mode data; the second mode data includes second time distribution data, second charge and discharge data, and second environment distribution data; Identify historical data of the battery in a third mode, and obtain third mode data; the third mode data includes third time distribution data, third charge and discharge data, and third environment distribution data; Historical data of the battery in a fourth mode is identified in the battery historical data to obtain fourth mode data; the fourth mode data includes fourth time distribution data, fourth charge and discharge data, and fourth environment distribution data.

6. A method for controlling balanced output of a solar street light with multiple battery modules according to claim 5, characterized in that: The process of obtaining the first fitting duration through the first mode data identification is: Acquire first mode data and a battery suitable environment; the first mode data includes first time distribution data, first charge and discharge data, and first environment distribution data; Fitting the first time distribution data according to the difference between the first environment distribution data and the suitable environment of the battery and the first charge and discharge data to obtain a first fitting time length; Among them, the first time distribution data is the time distribution data when the battery is in the first mode; the first charge and discharge data are the historical charging data and historical discharge data of the battery in the first mode; the first environment distribution data is the historical environment data of the battery in the first mode; since the first mode is that the battery is neither charged nor discharged, the first charge and discharge data is an empty set.

7. The method for controlling the balanced output of a solar street light with multiple battery modules according to claim 1, characterized in that: Monitor the lighting area to obtain regional traffic data, regional weather data and regional lighting data; The regional traffic data is traffic flow data of the lighting area, including the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed; obtained by a high-definition camera; The regional weather data is the weather data of the lighting area; including ambient brightness, temperature data and humidity data; obtained through monitoring by IoT sensors; The regional lighting data includes lighting brightness data, color temperature change data and street lamp flicker data of street lamps in the lighting area.

8. A method for controlling balanced output of a solar street light with multiple battery modules according to claim 7, characterized in that: The process of identifying regional lighting standards through regional traffic data and regional weather data is: Constructing a lighting standard recognition model; inputting the regional traffic data and regional weather data into the lighting standard recognition model; Identify the number of pedestrians, pedestrian speed, number of vehicles, vehicle type and vehicle speed in regional traffic data to obtain traffic flow characteristics; Identify the ambient brightness, temperature and humidity data in the regional weather data to obtain weather data features; The traffic flow characteristics and the weather data characteristics are identified to obtain regional lighting standards.

9. A method for controlling balanced output of a solar street light with multiple battery modules according to claim 1, characterized in that: The determination process of the lighting quality coefficient is as follows: Determining whether the lighting quality coefficient meets the regional lighting standard; If satisfied, continue to use the current battery; if not satisfied, switch according to the battery usage order and continue to identify and judge the lighting quality; When all batteries do not meet the regional lighting standards, select the battery with the lighting quality coefficient closest to the regional lighting standards.

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