MPPT type solar charging and discharging light source integrated street lamp system

Abstract

The invention provides an MPPT type solar charging and discharging light source integrated street lamp system, and relates to the technical field of solar street lamps. The method comprises the following specific implementation steps: firstly, acquiring actual electric energy through a solar energy conversion module, and acquiring battery parameters through a battery data acquisition module; secondly, the battery charging control module determines a charging mode based on the calibration parameters of different battery types, and dynamically adjusts charging current; then, the light source demand analysis module adjusts the actual illuminance of the street lamps according to the distance between the adjacent street lamps and meteorological data; then, the battery discharge control module adjusts the discharge current through the actual power demand of the light source and the discharge current nonlinear mapping; and finally, the battery state evaluation module predicts the health state of the battery through a battery state evaluation model and feeds back the health state to the battery charging control module and the battery discharging control module, so that the charging and discharging efficiency of different battery types is effectively improved, the service life of the battery is prolonged, and the stability and consistency of the street lamp system are further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of solar street lamps, and in particular to an MPPT type solar charging and discharging light source integrated street lamp system. Background Art

[0002] With the intensification of the global energy crisis and the improvement of environmental awareness, solar energy as a renewable energy source has been gradually widely used in various lighting systems, especially in the field of public facilities. However, traditional solar street lights usually use pulse width modulation technology to control the output current and voltage of solar panels, which cannot fully utilize the power generation potential of solar panels, resulting in low charging efficiency when the lighting conditions are poor, affecting the overall performance of the system. For this reason, MPPT (maximum power point tracking) technology has been introduced into the solar street light system to adjust the operating voltage and current of the solar panel in real time, always keeping it running at the optimal power point, thereby greatly improving the efficiency of photovoltaic power generation and reducing power loss.

[0003] At present, the existing MPPT solar street lights mainly control the charging and discharging process by embedding the charging and discharging curves of various types of batteries, without considering the impact of the loss of different types of batteries on the charging and discharging performance. As a result, different types of batteries cannot perform at their best in the street light system, and overcharging or over-discharging may occur, resulting in the battery being unable to provide stable power supply to the street lights.

[0004] Therefore, an MPPT solar charging and discharging light source integrated street lamp system is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an MPPT type solar charging and discharging light source integrated street lamp system to improve the stability and consistency of the street lamp system. In order to solve the problems existing in the prior art, the present invention first obtains actual electric energy through the solar energy conversion module, and the battery data acquisition module obtains battery parameters; secondly, the battery charging control module determines the charging mode based on the calibration parameters of different battery types, and dynamically adjusts the charging current; then, the light source demand analysis module adjusts the actual illumination of the street lamp in combination with the spacing between adjacent street lamps and meteorological data; then, the battery discharge control module adjusts the discharge current through nonlinear mapping of the actual power demand of the light source and the discharge current; finally, the battery status evaluation module predicts the battery health status through the battery status evaluation model, and feeds back to the battery charging control module and the battery discharge control module, which effectively improves the charging and discharging efficiency of different battery types, prolongs the battery life, and further improves the stability and consistency of the street lamp system.

[0006] An MPPT type solar charging and discharging light source integrated street lamp system, including, the specific implementation steps include:

[0007] The solar energy conversion module collects the voltage, current and temperature of the solar panel in real time through sensors, and obtains the actual electric energy in combination with the conversion efficiency of the MPPT controller;

[0008] The battery data acquisition module obtains battery calibration parameters, battery health, battery capacity and battery remaining capacity, and collects battery charging voltage, battery charging current, battery charging temperature, battery discharge voltage, battery discharge current and battery discharge temperature in real time based on the voltage sensor, current sensor and temperature sensor;

[0009] The battery charging control module obtains the charging mode according to the calibration parameters of different types of batteries; adjusts the battery charging current under different charging modes through temperature control, nonlinear mapping of charging current and power compensation;

[0010] The light source demand analysis module determines the switch state of the light source according to the ambient light intensity data; combines the distance between adjacent street lamps and ambient meteorological data, and obtains the second adjusted illumination through the inverse square law formula and weather status influencing factors;

[0011] The battery discharge control module obtains a discharge mode according to the remaining battery capacity and the battery discharge temperature; and adjusts the discharge current of different discharge modes through nonlinear mapping of the actual power demand of the light source, the remaining battery capacity and the discharge current;

[0012] The battery status assessment module inputs the public data set of lithium-ion battery aging into the battery status assessment model for model training; optimizes the model through transfer learning to further accurately predict the battery status of different types of batteries after charging and discharging.

[0013] Preferably, the solar energy conversion module comprises:

[0014] According to the voltage sensor, the current sensor and the temperature sensor, the instantaneous voltage, the instantaneous current and the instantaneous temperature of the solar panel are obtained; the instantaneous power is obtained through the instantaneous voltage and the instantaneous current; according to the instantaneous temperature, the instantaneous temperature loss of the solar panel is obtained; and the actual electric energy is obtained by combining the instantaneous power, the instantaneous temperature loss and the conversion efficiency of the MPPT controller.

[0015] Preferably, the battery calibration parameters include calibrated capacity, battery internal resistance, battery nominal voltage, battery self-discharge rate, calibrated charging voltage, calibrated minimum discharge voltage, calibrated maximum charging current, calibrated maximum operating temperature, calibrated maximum charging temperature and calibrated maximum discharge temperature; the battery health, the battery capacity and the battery remaining capacity are obtained by feedback from the battery status evaluation module.

[0016] Preferably, the battery charging control module comprises:

[0017] According to the battery calibration parameters, a calibrated charging voltage is obtained; the battery calibration parameters are input into a multilayer perceptron network to obtain a battery type; historical charging data corresponding to the battery type is obtained, and the battery health and the historical charging data are input into a convolutional neural network to obtain a first predetermined state threshold and a second predetermined state threshold; the battery charging state is obtained according to the percentage of the remaining battery capacity to the battery capacity; the charging voltage ratio is obtained by the ratio of the battery charging voltage to the calibrated charging voltage; the charging self-discharge rate is determined according to the calibrated self-discharge rate and the battery charging temperature; if the battery charging state is less than or equal to the first predetermined state threshold and the charging voltage ratio is less than or equal to the predetermined voltage ratio, the battery adopts a first charging mode; if the battery charging state is less than the second predetermined state threshold and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts a second charging mode; if the battery charging state is greater than or equal to the second predetermined state threshold, the charging self-discharge rate is greater than the predetermined self-discharge rate, and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts a third charging mode.

[0018] Preferably, the battery charging control module further includes:

[0019] According to the battery calibration parameters, the battery internal resistance, the calibrated maximum charging temperature, the calibrated maximum operating temperature and the calibrated maximum charging current are obtained; if the charging mode is the first charging mode, charging is performed according to the calibrated maximum charging current, and the battery charging temperature is monitored in real time; if the battery charging temperature is greater than or equal to the calibrated maximum charging temperature, the battery charging current is adjusted by temperature limiting; if the charging mode is the second charging mode, the equivalent capacitance of the battery is obtained according to the charging time of the first charging mode, the battery charging current and the difference between the battery charging voltage within the charging time; the battery charging current is adjusted in combination with the battery internal resistance and the equivalent capacitance of the second charging mode; if the charging mode is the third charging mode, the charging current is adjusted according to the charging self-discharge rate, the battery charging temperature and the battery charging voltage.

[0020] Preferably, the light source demand analysis module includes:

[0021] The light intensity data of the surrounding area is collected in real time through a light sensor to obtain an average light intensity; if the average light intensity is less than a predetermined light threshold, the light source is turned on; the street lamp spacing and the standard illumination are obtained, and a first adjusted illumination is obtained according to the inverse square law formula; the influencing factors of the illumination under different weather conditions are obtained by combining the environmental meteorological data and the first adjusted illumination, and the second adjusted illumination is obtained.

[0022] Preferably, the battery discharge control module includes:

[0023] The actual power demand of the light source is obtained through the second adjustment of illumination; if the remaining capacity of the battery is greater than a predetermined capacity threshold and the actual power demand is less than or equal to the rated maximum discharge power of the battery, the first discharge mode is adopted; if the remaining capacity of the battery is less than or equal to the predetermined capacity threshold, the second discharge mode is adopted; when the first discharge mode or the second discharge mode is adopted, if the battery discharge voltage is less than the calibrated minimum discharge voltage or the battery discharge temperature is greater than or equal to the calibrated maximum discharge temperature, the discharge is stopped.

[0024] Preferably, the battery discharge control module further includes:

[0025] According to the battery calibration parameters, a battery nominal voltage and a calibrated maximum discharge temperature are obtained; if the charging mode is the first discharge mode, a first discharge current is obtained and discharge is performed according to the actual power demand and the battery nominal voltage; the battery discharge temperature is monitored in real time, and if the battery discharge temperature is greater than or equal to the calibrated maximum discharge temperature, the battery charging current is adjusted according to the calibrated maximum discharge temperature to obtain a second discharge current; if the charging mode is the second discharge mode, a third discharge current is obtained according to the first discharge current and the remaining capacity of the battery through nonlinear mapping of the discharge current.

[0026] Preferably, the specific implementation process of the battery status assessment module includes:

[0027] A data acquisition unit collects charge and discharge history data according to the battery data acquisition module, including historical charge and discharge power, historical discharge power, historical charge and discharge voltage, historical charge and discharge current, historical charge and discharge temperature, and charge and discharge cycle number; and obtains historical charge depth and historical discharge depth by combining the historical charge and discharge power and the battery capacity;

[0028] A data preprocessing unit performs preprocessing operations on the data acquired by the data acquisition unit, including outlier processing, missing value processing, time alignment operation and normalization processing, to obtain standard historical data;

[0029] The battery status assessment model training unit inputs the lithium-ion battery aging public data set into the convolutional neural network to obtain a charge and discharge feature sequence; obtains a first enhanced feature sequence from the charge and discharge feature sequence according to the spatial self-attention mechanism; inputs the first enhanced feature sequence into the bidirectional convolutional long short-term memory network to obtain a second enhanced feature sequence; obtains the predicted battery health, battery remaining capacity ratio and battery remaining life through the fully connected layer and the activation function;

[0030] The battery status assessment model inference unit performs data enhancement operation on the standard historical data to obtain extended historical data; inputs the extended historical data into a pre-trained battery status assessment model, adjusts the model through a transfer learning strategy, and obtains the battery health after charging or discharging, the battery remaining capacity ratio, and the battery remaining life.

[0031] Preferably, the specific implementation process of the battery status evaluation module also includes:

[0032] The battery health and the battery remaining life predicted by the battery status assessment model training unit are supervised according to the mean absolute loss function; the battery remaining capacity ratio predicted by the battery status assessment model training unit is constrained by the logarithmic hyperbolic cosine loss function; the model weight of the battery status assessment model inference unit is adjusted by the weight updating method to obtain the battery health, the battery remaining capacity ratio and the battery remaining life after historical charging or discharging; the current battery remaining capacity is obtained according to the battery remaining capacity ratio and the battery health; the current battery capacity is obtained through the battery calibration parameters and the battery health; the current battery remaining capacity and the current battery capacity are fed back to the battery charging control module to update the battery remaining capacity and the battery capacity.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. The battery charging control module proposed in the present invention introduces a multi-layer perceptron network and a convolutional neural network to comprehensively analyze the characteristics of different types of batteries, thereby realizing accurate identification of battery types and optimization of charging strategies. The module intelligently switches and adjusts the charging mode, which not only ensures the safety and stability of different types of batteries under different working conditions, but also accurately adjusts the charging current and charging mode according to the real-time battery status to avoid overcharging, over-discharging and battery damage caused by excessive temperature; at the same time, by optimizing the charging mode switching conditions and the charging current adjustment strategy, it can effectively reduce the inconsistency caused by differences in battery characteristics, thereby improving the stability and service life of the solar street light system.

[0035] 2. The battery discharge control module proposed in the present invention accurately regulates the remaining capacity, battery discharge temperature and actual power demand of the battery in different discharge modes, avoiding system instability caused by differences in battery performance. The module monitors and dynamically adjusts the battery discharge temperature in real time. When the battery temperature approaches or exceeds the calibrated maximum discharge temperature, the system can adjust the discharge current in time to prevent battery performance degradation or safety hazards caused by excessive temperature. This not only improves the adaptability of the system under different ambient temperatures, but also enhances the discharge consistency between different battery types.

[0036] 3. The battery status assessment module proposed in the present invention uses algorithm models such as convolutional neural networks and bidirectional long short-term memory networks to conduct deep learning of battery charge and discharge history data, and combines the spatial self-attention mechanism to enhance feature extraction capabilities, and accurately predict battery health, remaining capacity ratio and remaining life. Not only does it take into account the aging trend of the battery, but it can also make personalized adjustments to the health status of different types of batteries, so that the system can maintain consistency in a variety of battery configurations. Through data enhancement and transfer learning, the system can adapt to the usage history of different batteries, adjust the charge and discharge strategy in a timely manner, prevent the battery from being over-discharged or shortened, and thus extend the service life of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart of an MPPT type solar charging and discharging light source integrated street lamp system provided by an embodiment of the present invention;

[0038] Figure 2 A flowchart of charging mode matching provided by an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of a solar street light for a road in city A provided by an embodiment of the present invention;

[0040] Figure 4 This is a flow chart of a battery status evaluation module provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] 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.

[0042] MPPT solar street lights have efficient energy conversion capabilities and can track the maximum power point of solar panels in real time, thereby maximizing the use of solar energy resources under various environmental conditions. However, different types of batteries such as lead-acid batteries, nickel-metal hydride batteries, gel batteries and lithium batteries have significant differences in charge and discharge characteristics, life and performance, which may lead to reduced system efficiency or battery loss if not properly managed. Therefore, automatically adjusting the charge and discharge voltage and current of MPPT solar street lights according to the characteristics of different types of batteries can ensure that the battery is always in the best working condition, which not only prolongs the battery life, but also improves the stability and consistency of the overall system.

[0043] The present invention proposes an MPPT solar charging and discharging light source integrated street lamp system to automatically adjust the charging and discharging process of different types of energy storage batteries to ensure stable power supply of different batteries. In order to illustrate the effectiveness of the system proposed by the present invention, it will be specifically described in combination with the drawings of this embodiment and the following two embodiments.

[0044] Embodiment 1

[0045] The present application embodiment discloses a MPPT type solar charging and discharging light source integrated street lamp system to achieve efficient lighting of the roads in urban area A under sunny conditions. Figure 1 The system proposed by the present invention includes: a solar energy conversion module, a battery data acquisition module, a battery charging control module, a light source demand analysis module, a battery discharge control module and a battery status evaluation module.

[0046] Furthermore, during the day, the solar energy conversion module obtains the instantaneous voltage, instantaneous current and instantaneous temperature of the solar panel according to the voltage sensor, the current sensor and the temperature sensor; obtains the instantaneous power through the instantaneous voltage and the instantaneous current; and obtains the instantaneous temperature loss of the solar panel according to the instantaneous temperature;

[0047] L temp i =V i I i ·η ref ·(1-α·|T i -T ref |);

[0048] Among them, L temp i Represents the instantaneous temperature loss at sampling point i; V i ,I i Respectively represent the instantaneous voltage and instantaneous current at sampling point i; η ref Indicates the conversion efficiency of the solar panel at the reference temperature; T i ,T ref They represent the instantaneous temperature and reference temperature of sampling point i respectively; α represents the temperature sensitivity coefficient of the solar panel, which is obtained through a large amount of experimental data;

[0049] The actual electric energy is obtained by combining the instantaneous power, instantaneous temperature loss and the conversion efficiency of the MPPT controller. The specific calculation formula is:

[0050]

[0051] Among them, E in Indicates actual electrical energy; η zhq represents the conversion efficiency of the MPPT controller; P irepresents the instantaneous power at sampling point i; L temp i represents the instantaneous temperature loss at sampling point i; N represents the number of sampling times during the sunshine time; Δt represents the sampling time.

[0052] Under sunny conditions, the sampling time and number of sampling times should be reasonably set according to the speed of solar radiation changes, so as to ensure that the solar radiation changes slowly during the sampling time, that is, the corresponding light intensity changes slowly, and can capture the rapid changes of environmental factors such as solar irradiance and temperature; under normal circumstances, the light changes slowly on sunny days, so that the instantaneous power obtained by the solar panel changes slowly within a certain period of time, so the sampling time is generally 5 to 10 seconds.

[0053] The embodiment of the present application can effectively avoid power fluctuations caused by changes in panel temperature by taking into account the impact of temperature loss and controller conversion efficiency on solar energy conversion efficiency. This real-time adjustment and compensation mechanism helps maintain the stability of the battery charging process and reduce system performance fluctuations caused by ambient temperature fluctuations.

[0054] Furthermore, the battery data acquisition module obtains battery calibration parameters, battery capacity and battery remaining capacity, and collects battery charging voltage, battery charging current, battery charging temperature, battery discharge voltage, battery discharge current and battery discharge temperature in real time according to the voltage sensor, current sensor and temperature sensor; the battery calibration parameters include calibrated capacity, battery internal resistance, battery nominal voltage, battery self-discharge rate, calibrated charging voltage, calibrated minimum discharge voltage, calibrated maximum charging current, calibrated maximum operating temperature, calibrated maximum charging temperature and calibrated maximum discharge temperature; the battery health, the battery capacity and the battery remaining capacity are obtained by feedback from the battery status evaluation module.

[0055] The embodiment of the present application uses battery calibration parameters and real-time collected data such as charge and discharge voltage, current and temperature to accurately evaluate the battery capacity and intelligently adjust the charge and discharge process, thereby improving the charge and discharge efficiency and reducing the battery self-discharge loss. In addition, through real-time temperature monitoring and calibration of temperature parameters, it can effectively prevent safety hazards such as overheating, ensure the stable operation of the battery, and provide data support for subsequent charge and discharge adjustments.

[0056] Furthermore, the battery charging control module obtains the battery charging mode by combining the battery calibration parameters, the battery remaining capacity, the battery charging voltage and the battery charging current; the specific implementation process includes:

[0057] According to the battery calibration parameters, a calibrated charging voltage is obtained; the battery calibration parameters are input into a multi-layer perceptron network to obtain a battery type; historical charging data corresponding to the battery type is obtained, and the battery health and the historical charging data are input into a convolutional neural network to obtain a first predetermined state threshold and a second predetermined state threshold; the first predetermined state threshold is less than or equal to the second predetermined state threshold; the battery charging state is obtained according to the percentage of the remaining battery capacity to the battery capacity; the charging voltage ratio is obtained by the ratio of the battery charging voltage to the calibrated charging voltage; the charging self-discharge rate is determined according to the calibrated self-discharge rate and the charging temperature, and the specific calculation formula is:

[0058]

[0059] Among them, SDR cha represents the charge self-discharge rate; SDR represents the calibrated self-discharge rate at the reference temperature; T cha Indicates the battery charging temperature; T r represents the reference temperature, which is generally 25°C; k represents the influence factor of temperature on the self-discharge rate, which is obtained through a large amount of experimental data;

[0060] See also Figure 2 If the battery charging state is less than or equal to the first predetermined state threshold and the charging voltage ratio is less than or equal to the predetermined voltage ratio, the battery adopts the first charging mode; if the battery charging state is less than the second predetermined state threshold and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts the second charging mode; if the battery charging state is greater than or equal to the second predetermined state threshold, the charging self-discharge rate is greater than the predetermined self-discharge rate and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts the third charging mode.

[0061] Specifically, if the battery charging state is greater than the first predetermined state threshold and less than the second predetermined state threshold, the charging voltage ratio must be greater than the predetermined voltage ratio. The first charging mode is a fast charging mode, the purpose of which is to quickly replenish the battery when the battery power is low, thereby improving the charging efficiency; the second charging mode is a stable charging mode, which can stably charge the battery when the battery power is high to prevent battery loss caused by excessive battery charging voltage; the third charging mode can continuously charge the battery with a small current when the battery is close to full charge, so that the battery remains fully charged. The calibration parameters of the battery can directly reflect the characteristics of batteries with different characteristics, and the charging self-discharge rate can effectively distinguish whether the battery needs to adopt the third charging mode. For example, the calibrated self-discharge rate of the lithium battery is low and the temperature has little effect on the self-discharge rate. By setting the predetermined self-discharge rate, it can be prevented from adopting the third charging mode to prevent overcharging; while the calibrated self-discharge rate of the lead-acid battery is high and the temperature has a greater effect on the self-discharge rate. The third charging mode can effectively compensate for the energy loss caused by the self-discharge of the battery. Therefore, the charging mode selection process does not need to identify the battery type, and the charging mode can be automatically adjusted for different types of batteries based on the battery calibration parameters and charging parameters.

[0062] In order to further illustrate the effects of the different charging modes proposed in the present invention, the charging modes of several solar street lamps on the roads in urban area A under sunny conditions are given as examples for comparison. The charging modes of different solar street lamps are listed in Table 1; wherein the predetermined voltage ratio is 0.94; the predetermined self-discharge rate is 10%; and the battery health is 100%.

[0063] Table 1. Charging modes of different solar street lights on roads in urban area A

[0064]

[0065] In the embodiment of the present application, different state thresholds are set for different types of batteries; for example, the charging state of the DC01 battery of the SL01 street lamp is 0.92, the charging voltage ratio is 0.37, and the charging self-discharge rate is 2.18%. The first charging mode can ensure that the battery can maintain a good charging state at a higher voltage and a lower self-discharge rate; for the DC02 battery of the SL02 street lamp, although the charging voltage is relatively high, the charging state is 0.76, so it is in the second charging mode, which can effectively control the battery health during the charging process and avoid battery loss caused by excessively high charging voltage; and the DC03 battery of the SL06 street lamp has a high self-discharge rate and charging voltage ratio. By setting a predetermined state threshold, it works in the third charging mode, which can effectively reduce the battery power loss caused by excessively high self-discharge rate, thereby improving the charging efficiency. Therefore, by learning different predetermined state thresholds through the network according to different types of batteries, the charging process can be accurately controlled, the charging efficiency can be improved, and the battery performance can be optimized.

[0066] The embodiment of the present application automatically adjusts the charging mode according to the calibration parameters and charging status of different types of batteries, thereby ensuring that each type of battery operates under the most suitable charging conditions, avoiding charging inconsistency problems caused by different battery characteristics, and improving the charging consistency of the entire system; in addition, the monitoring of the charging self-discharge rate further improves the accuracy and adaptability of the charging process by adjusting the charging mode, thereby reducing the energy loss caused by self-discharge.

[0067] Furthermore, the battery charging control module also adjusts the charging current of the battery in real time according to the charging temperature in combination with the charging mode and the battery calibration parameters; the specific implementation process includes:

[0068] According to the battery calibration parameters, the battery internal resistance, the calibrated maximum charging temperature, the calibrated maximum operating temperature and the calibrated maximum charging current are obtained; if the charging mode is the first charging mode, charging is performed according to the maximum charging current, and the battery charging temperature is monitored in real time; if the battery charging temperature is greater than or equal to the calibrated maximum charging temperature, the battery charging current is adjusted by temperature limiting, and the specific calculation formula is:

[0069]

[0070] in, Represents the adjusted charging current; I max Represents the maximum charging current; T cha Indicates the battery charging temperature; T work Indicates the rated maximum operating temperature; T max_cha represents the rated maximum charging temperature and T work >T max_cha; δ represents the influence factor of temperature on current, which is obtained through a large amount of experimental data;

[0071] If the charging mode is the second charging mode, the equivalent capacitance of the battery is obtained according to the charging time of the first charging mode, the battery charging current and the difference of the battery charging voltage within the charging time; the battery charging current is obtained by combining the battery internal resistance and the equivalent capacitance of the second charging mode. The specific calculation formula is:

[0072]

[0073] in, represents the charging current of the second charging mode; I0 represents the initial charging current in the second charging mode; R represents the equivalent resistance of the battery; C represents the equivalent capacitance; t represents the current charging time of the second charging mode;

[0074] If the charging mode is the third charging mode, the charging current is adjusted according to the charging self-discharge rate, the battery charging temperature and the battery charging voltage. The specific formula is expressed as follows:

[0075]

[0076] in, Indicates the charging current of the third charging mode; CA indicates the current battery capacity; SDR cha Represents the charge self-discharge rate; V cha Indicates the battery charging voltage.

[0077] In the first charging mode, the embodiment of the present application monitors the battery charging temperature in real time. When the temperature exceeds the calibration threshold, the current is adjusted through a formula to avoid instability caused by overheating. In the second charging mode, the charging current is dynamically adjusted by calculating the equivalent capacitance and internal resistance of the battery to ensure accurate control of the charging process. In the third charging mode, the charging current is further optimized according to the self-discharge rate, charging temperature and voltage to avoid the influence of overcharging or temperature fluctuations. The above adjustment method enables different types of batteries to be stably charged within their characteristic range, ensures the consistency of the charging process, and reduces the influence of temperature and current fluctuations on battery performance, thereby improving the overall stability and reliability of the street light system.

[0078] Furthermore, real-time light intensity data is obtained through the ambient light sensor to determine whether the light source is on or off; the second adjusted illumination is obtained by combining the distance between adjacent street lamps and ambient meteorological data through the inverse square law formula and the weather status influencing factor; the light source demand analysis module includes:

[0079] The light sensor collects the surrounding light intensity data in real time to obtain the average light intensity; if the average light intensity is less than the predetermined light threshold, the light source is turned on; the street lamp spacing and standard illumination are obtained, and the first adjusted illumination is obtained according to the inverse square law formula, which is specifically expressed as:

[0080]

[0081] in, Indicates the first adjustment illumination; Indicates standard illumination; see Figure 3 , h, d represent the height of street lamp and the distance between adjacent street lamps respectively; θ represents the inclination angle of street lamp and 0°<θ≤90°;

[0082] Combine the environmental meteorological data and the first adjusted illuminance to obtain the influencing factors of the illuminance under different weather conditions, and obtain the second adjusted illuminance. The specific calculation formula is:

[0083]

[0084] W t =1-(β1·CC+β2·RI+β3·SI+β4·HC+β5·(1-SD));

[0085] in, Indicates the second adjusted illumination; W t Indicates the weather condition influencing factor, which is used to evaluate the influence of different weather conditions such as cloud cover, precipitation, snowfall and haze on the actual illumination; represents the average light intensity; represents the ambient light intensity corresponding to the standard illumination; CC, RI, SI, HC, SD represent cloud cover parameter, precipitation intensity parameter, snowfall intensity parameter, haze concentration parameter and sunshine duration parameter respectively. These weather state parameters are obtained by normalizing the corresponding original meteorological parameters; β1, β2, β3, β4, β5 represent the weight factors of different weather state parameters and

[0086] Specifically, when different types of battery packs are used to store electrical energy in the street lighting system in City A, the performance and charging characteristics of each battery pack may be different. Therefore, obtaining the actual power demand of the power source can ensure that the output power of each battery pack is the same, thereby avoiding inconsistency problems caused by performance differences between battery packs. At the same time, obtaining the actual power demand of the power source can also help analyze the usage and life of the battery pack, and promptly discover and handle possible battery failures or performance degradation, thereby improving the reliability and stability of the system.

[0087] The embodiment of the present application adjusts the illumination requirements of the street lamp according to the ambient light conditions and weather factors to reduce the additional battery load. The first adjusted illumination is calculated by the inverse square law formula, and the weather influencing factors obtained by combining meteorological data such as cloud cover, precipitation, snowfall, and haze are further optimized to further optimize the second adjusted illumination. This can avoid over-reliance on battery power supply when the light is insufficient and reduce the battery discharge load; at the same time, the switching state of the light source is dynamically adjusted according to the lighting conditions to avoid frequent battery charging and discharging caused by illumination fluctuations, thereby keeping the battery running in a more stable working state, effectively improving the charging consistency of different battery types, reducing the negative impact of environmental changes on battery life, and thus improving the overall stability of the system.

[0088] Furthermore, the battery discharge control module dynamically selects a discharge mode according to the remaining battery capacity and the battery discharge temperature, and the specific implementation process includes:

[0089] The actual power demand of the light source is obtained through the second adjustment of illumination; if the remaining capacity of the battery is greater than a predetermined capacity threshold and the actual power demand is less than or equal to the rated maximum discharge power of the battery, the first discharge mode is adopted; if the remaining capacity of the battery is less than or equal to the predetermined capacity threshold, the second discharge mode is adopted; when the first discharge mode or the second discharge mode is adopted, if the battery discharge voltage is less than the calibrated minimum discharge voltage or the battery discharge temperature is greater than or equal to the calibrated maximum discharge temperature, the discharge is stopped.

[0090] Specifically, the first discharge mode is a constant power discharge mode, the purpose of which is to provide stable light output when the battery power is high; the second discharge mode is a continuous discharge mode, which can continuously discharge at a smaller discharge power when the battery power is low to extend the lighting time.

[0091] The embodiment of the present application ensures that the discharge strategy is reasonably adjusted according to the remaining capacity and power demand of the battery in different discharge modes through the status and working conditions of different batteries. When the remaining capacity of the battery is high, the first discharge mode is adopted to ensure the normal power supply of the street lamp; when the remaining capacity is low, the system switches to the second discharge mode to extend the battery life and optimize the power output; at the same time, the discharge voltage and temperature of the battery are monitored in real time, so as to stop the discharge in time to prevent the battery from being over-discharged or overheated. This process ensures that the system can operate efficiently under different power output conditions, effectively improving the stability and consistency of the solar street light system.

[0092] Furthermore, the battery discharge control module also adjusts the discharge current of different discharge modes through nonlinear mapping of the actual power demand of the light source, the remaining battery capacity and the discharge current. The specific implementation process includes:

[0093] According to the battery calibration parameters, the battery nominal voltage and the calibrated maximum discharge temperature are obtained; if the charging mode is the first discharge mode, a first discharge current is obtained and discharged according to the actual power demand and the battery nominal voltage; the battery discharge temperature is monitored in real time, and if the battery discharge temperature is greater than or equal to the calibrated maximum discharge temperature, the battery charging current is adjusted according to the calibrated maximum discharge temperature to obtain a second discharge current, and the specific calculation formula is:

[0094]

[0095] in, represents the second discharge current; represents the first discharge current; T dis Indicates the battery discharge temperature; T max_dis represents the calibrated maximum discharge temperature; γ is the temperature coefficient, which represents the rate of change of the discharge current when the temperature changes by 1°C;

[0096] If the charging mode is the second discharge mode, a third discharge current is obtained by nonlinear mapping of the discharge current according to the first discharge current and the remaining capacity of the battery. The specific formula is expressed as follows:

[0097]

[0098] in, represents the third discharge current; ln() represents a natural number logarithmic function; CA dis ,CA set They respectively represent the remaining capacity of the battery and the predetermined capacity threshold; μ represents a control parameter, which is obtained by performing nonlinear fitting on a large amount of battery data, and different types of batteries have different corresponding control parameter values.

[0099] The embodiment of the present application monitors the battery discharge temperature in real time, and adjusts the battery charging current according to the calibrated maximum discharge temperature, ensuring that the battery operates within the optimal temperature range, effectively preventing performance degradation or safety hazards caused by overheating, not only improving the service life of the battery, but also maintaining the stable operation of the system; at the same time, a nonlinear mapping model is used to adjust the discharge current according to the remaining capacity of the battery, so that the discharge of the battery at different remaining capacities is smoother, which not only effectively improves the stability of the battery under different working conditions, but also ensures the consistency of various types of batteries in the entire discharge process.

[0100] Furthermore, the battery status assessment module inputs the lithium-ion battery aging public data set into the battery status assessment model to perform model training; optimizes the model through transfer learning to further accurately predict the battery health, battery remaining capacity ratio and battery remaining life after battery charging and discharging; Figure 4The specific implementation process of the battery status evaluation module includes:

[0101] A data acquisition unit collects charge and discharge history data according to the battery data acquisition module, including historical charge and discharge power, historical discharge power, historical charge and discharge voltage, historical charge and discharge current, historical charge and discharge temperature, and charge and discharge cycle number; and obtains historical charge depth and historical discharge depth by combining the historical charge and discharge power and the battery capacity;

[0102] A data preprocessing unit performs preprocessing operations on the data acquired by the data acquisition unit, including outlier processing, missing value processing, time alignment operation and normalization processing, to obtain standard historical data;

[0103] The battery status assessment model training unit inputs the lithium-ion battery aging public data set into the convolutional neural network to obtain a charge and discharge feature sequence; obtains a first enhanced feature sequence from the charge and discharge feature sequence according to the spatial self-attention mechanism; inputs the first enhanced feature sequence into the bidirectional convolutional long short-term memory network to obtain a second enhanced feature sequence; obtains the predicted battery health, battery remaining capacity ratio and battery remaining life through the fully connected layer and the activation function;

[0104] The battery status assessment model inference unit performs data enhancement operation on the standard historical data to obtain extended historical data; inputs the extended historical data into a pre-trained battery status assessment model, adjusts the model through a transfer learning strategy, and obtains the battery health after charging or discharging, the battery remaining capacity ratio, and the battery remaining life.

[0105] This module in the embodiment of the present application ensures accurate assessment of battery health through comprehensive data collection and preprocessing; combined with the spatial self-attention mechanism, bidirectional convolutional long short-term memory network and transfer learning strategy, it can accurately predict the battery's health, remaining capacity and remaining life. This precise prediction improves battery management capabilities, prevents overcharging and over-discharging, and provides accurate battery capacity data for subsequent charging and discharging processes, ensuring the accuracy and efficiency of different battery charging and discharging controls, so that the solar street light system can still maintain stable performance and consistent lighting effects under various environmental conditions.

[0106] Furthermore, the battery state assessment model training unit supervises the battery health and the battery remaining life predicted by the battery state assessment model training unit according to the mean absolute loss function; constrains the battery remaining capacity ratio predicted by the battery state assessment model training unit through the logarithmic hyperbolic cosine loss function; the specific calculation formula of the loss function is:

[0107]

[0108] Among them, L lc represents the logarithmic hyperbolic cosine loss function; MAE() represents the mean absolute loss function; SOH represents predicted battery health and actual battery health, respectively; RUL represents the predicted remaining battery life and the actual remaining battery life respectively; n represents the number of samples; log() represents the logarithmic function; Respectively represent the predicted battery remaining capacity ratio and the actual battery remaining capacity ratio of the i-th sample;

[0109] See also Figure 1 , inputting historical charging and / or discharging data into a battery status evaluation model, wherein the battery status evaluation model inference unit adjusts the weight of the battery status evaluation model through a weight updating method, and obtains the battery health, the battery remaining capacity ratio and the battery remaining life after historical charging and / or discharging; obtaining the current battery remaining capacity according to the battery remaining capacity ratio and the battery health; obtaining the current battery capacity through the battery calibration parameters and the battery health; and feeding back the battery health, the current battery remaining capacity and the current battery capacity to the battery charging control module to update the battery health, the battery remaining capacity and the battery capacity.

[0110] The embodiment of the present application can accurately predict the health status of different types of batteries through the training of the battery status assessment model and the optimization and regulation of the inference unit, and realize the real-time assessment of the current capacity of the battery by combining the battery calibration parameters. This process ensures the high accuracy and consistency of the prediction results by introducing the mean absolute loss function and the logarithmic hyperbolic cosine loss function, and effectively constrains the deviation in the battery charging and discharging process; through the dynamic update and feedback mechanism of the battery charging control module, the stability and consistency of the solar street light system in various battery conditions are improved.

[0111] The embodiment of the present application realizes efficient charge and discharge management and status prediction of different types of batteries through the coordinated work of the battery charging control module, the discharge control module and the battery status evaluation module. The specific implementation process mainly includes the following steps: (1) controlling the charging current according to different battery characteristics; (2) adaptive discharge control; (3) battery health status evaluation. The present invention proposes flexible charging control, stable discharge control and accurate health prediction for the above three processes respectively; the charging control realizes efficient charging for different battery types, avoids overcharging, and improves battery compatibility and service life; the discharge control further improves the stability of the light source output and reduces energy loss; the battery health status prediction further improves the system's adaptability to different battery states, extends the service life of the entire system and improves the overall reliability of the system.

[0112] Embodiment 2

[0113] In Example 1, the system of the present invention realizes efficient lighting of the road in urban area A under sunny conditions. In the embodiment of this application, the system proposed by the present invention will be described again to realize efficient lighting of the road in mountainous area B under continuous cloudy conditions. The specific implementation process is as follows:

[0114] During the day, the solar energy conversion module obtains the instantaneous voltage, instantaneous current and instantaneous temperature of the solar panel according to the voltage sensor, the current sensor and the temperature sensor; obtains the instantaneous power through the instantaneous voltage and the instantaneous current; obtains the instantaneous temperature loss of the solar panel according to the instantaneous temperature; and obtains the actual electric energy by combining the instantaneous power, the instantaneous temperature loss and the conversion efficiency of the MPPT controller.

[0115] In the embodiment of the present application, due to the influence of cloud cover under continuous cloudy conditions, the solar radiation obtained by the solar street light system on the road in mountain area B is greatly reduced; combined with the maximum power point tracking function of the MPPT controller, the power output can be dynamically adjusted under continuous cloudy conditions to obtain maximum conversion efficiency and actual power.

[0116] Further, according to the battery calibration parameters, a calibrated charging voltage is obtained; the battery calibration parameters are input into a multilayer perceptron network to obtain a battery type; historical charging data corresponding to the battery type is obtained, and the battery health and the historical charging data are input into a convolutional neural network to obtain a first predetermined state threshold and a second predetermined state threshold; the battery charging state is obtained according to the percentage of the remaining battery capacity to the battery capacity; the charging voltage ratio is obtained by the ratio of the battery charging voltage to the calibrated charging voltage; the charging self-discharge rate is determined according to the calibrated self-discharge rate and the battery charging temperature; if the battery charging state is less than or equal to the first predetermined state threshold and the charging voltage ratio is less than or equal to the predetermined voltage ratio, the battery adopts a first charging mode; if the battery charging state is less than the second predetermined state threshold and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts a second charging mode; if the battery charging state is greater than or equal to the second predetermined state threshold, the charging self-discharge rate is greater than the predetermined self-discharge rate, and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts a third charging mode; and the battery charging current under the three charging modes is adjusted respectively through temperature control, charging current nonlinear mapping and power compensation.

[0117] In the embodiment of the present application, the solar street light system on the road in the B mountain area will face the problem of insufficient light, resulting in reduced battery charging efficiency and reduced remaining capacity, thereby affecting the overall stability and lighting effect of the system. In this case, the embodiment of the present application automatically adjusts the charging mode according to the characteristics of different types of battery packs: for example, in the first charging mode, the charging temperature of the battery is monitored in real time. Since the ambient temperature fluctuates greatly under cloudy conditions, the street light system will adjust the charging current according to the temperature limit to prevent the battery from overheating, thereby extending the battery life; in the second charging mode, the battery charging current is calculated in combination with the battery internal resistance and equivalent capacitance to cope with the situation of unstable battery capacity under low light conditions, and avoid the problem of insufficient charging caused by excessive or too small current during the charging process; in the case of continuous cloudy days, since the battery may have an increased self-discharge rate due to being in a low light environment for a long time, the charging current will be dynamically adjusted according to the battery self-discharge rate, charging temperature and charging voltage in the third charging mode to avoid insufficient power supply due to battery performance degradation, thereby ensuring the lighting consistency and system stability of the road in the B mountain area under severe weather conditions.

[0118] Furthermore, the light source demand analysis module obtains real-time light intensity data through the ambient light sensor to determine whether the light source is on or off; combined with the distance between adjacent street lamps and ambient meteorological data, the second adjusted illumination is obtained through the inverse square law formula and weather status influencing factors.

[0119] Furthermore, the battery discharge control module obtains battery calibration parameters, battery capacity and battery remaining capacity, and collects battery discharge voltage, battery discharge current and battery discharge temperature in real time according to voltage sensors, current sensors and temperature sensors; if the battery remaining capacity is greater than a predetermined capacity threshold and the actual power demand is less than or equal to the rated maximum discharge power of the battery, a first discharge mode is adopted; if the battery remaining capacity is less than or equal to the predetermined capacity threshold, a second discharge mode is adopted; when the first discharge mode or the second discharge mode is adopted, if the battery discharge voltage is less than a calibrated minimum discharge voltage or the battery discharge temperature is greater than or equal to a calibrated maximum discharge temperature, the discharge is stopped; and the discharge current of different discharge modes is adjusted through nonlinear mapping of the actual power demand of the light source, the battery remaining capacity and the discharge current.

[0120] Under continuous cloudy conditions, the actual power demand of the solar street light system on the roads in Mountain B increases, while the charging efficiency of the solar panels decreases, which may lead to insufficient battery energy storage. In this case, when the remaining battery capacity is high, the system adopts the first discharge mode to ensure that the street light can still meet the lighting requirements of the road when the light is insufficient; as the continuous cloudy days continue, the remaining battery capacity gradually decreases, and it switches to the second discharge mode, comprehensively considering the remaining capacity and actual power demand to extend the battery working time, so that the lighting needs of the roads in Mountain B can be met with limited energy reserves.

[0121] Furthermore, the battery status assessment module inputs the lithium-ion battery aging public data set into the battery status assessment model to perform model training; optimizes the model based on transfer learning and historical charging and / or discharging data to further accurately predict the battery health, battery remaining capacity ratio and battery remaining life after battery charging and / or discharging; obtains the current battery remaining capacity based on the battery remaining capacity ratio and the battery health; obtains the current battery capacity through the battery calibration parameters and the battery health; and feeds back the current battery remaining capacity and the current battery capacity to the battery charging control module to update the battery remaining capacity and the battery capacity.

[0122] In an embodiment of the present application, the solar street light system on the road in mountain area B will face the problem of low power generation efficiency of solar photovoltaic panels, resulting in the inability to fully charge the battery, thereby affecting the continuous power supply capacity of the street light system. By real-time monitoring and updating the battery health and remaining capacity ratio, the current available power of the battery can be accurately evaluated, which helps to take countermeasures in advance when the battery health decreases or the remaining capacity is insufficient, such as reducing the brightness of the street light, adjusting the working hours, or turning on the light source intermittently to extend the battery life. The data of the remaining capacity and actual capacity of the battery are fed back to the charging and / or discharging control module, and the system accurately regulates the charging and / or discharging process according to the actual power of the battery, effectively preventing overcharging and over-discharging of the battery, thereby ensuring the consistency and stability of the system during continuous cloudy days.

[0123] 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 MPPT solar charging and discharging light source integrated street lamp system, characterized in that: include: The solar energy conversion module collects the voltage, current and temperature of the solar panel in real time through sensors, and obtains the actual electric energy in combination with the conversion efficiency of the MPPT controller; The battery data acquisition module obtains battery calibration parameters, battery health, battery capacity and battery remaining capacity, and collects battery charging voltage, battery charging current, battery charging temperature, battery discharge voltage, battery discharge current and battery discharge temperature in real time based on the voltage sensor, current sensor and temperature sensor; The battery charging control module obtains the charging mode according to the calibration parameters of different types of batteries; adjusts the battery charging current under different charging modes through temperature control, nonlinear mapping of charging current and power compensation; The light source demand analysis module determines the switch status of the light source based on the ambient light intensity data; Combining the distance between adjacent street lamps and environmental meteorological data, the second adjusted illumination is obtained through the inverse square law formula and the weather condition influencing factor; The battery discharge control module obtains a discharge mode according to the remaining battery capacity and the battery discharge temperature; and adjusts the discharge current of different discharge modes through nonlinear mapping of the actual power demand of the light source, the remaining battery capacity and the discharge current; The battery status assessment module inputs the lithium-ion battery aging public data set into the battery status assessment model for model training; optimizes the model through transfer learning to predict the battery status of different types of batteries after charging and discharging.

2. The MPPT solar charging and discharging light source integrated street lamp system according to claim 1, characterized in that: The solar energy conversion module comprises: According to the voltage sensor, the current sensor and the temperature sensor, the instantaneous voltage, the instantaneous current and the instantaneous temperature of the solar panel are obtained; the instantaneous power is obtained through the instantaneous voltage and the instantaneous current; according to the instantaneous temperature, the instantaneous temperature loss of the solar panel is obtained; and the actual electric energy is obtained by combining the instantaneous power, the instantaneous temperature loss and the conversion efficiency of the MPPT controller.

3. The MPPT solar charging and discharging light source integrated street lamp system according to claim 1, characterized in that: The battery calibration parameters include calibrated capacity, battery internal resistance, battery nominal voltage, battery self-discharge rate, calibrated charging voltage, calibrated minimum discharge voltage, calibrated maximum charging current, calibrated maximum operating temperature, calibrated maximum charging temperature and calibrated maximum discharge temperature; the battery health, the battery capacity and the battery remaining capacity are obtained by feedback from the battery status evaluation module.

4. The MPPT solar charging and discharging light source integrated street lamp system according to claim 1, characterized in that: The battery charging control module comprises: According to the battery calibration parameters, a calibrated charging voltage is obtained; the battery calibration parameters are input into a multilayer perceptron network to obtain a battery type; historical charging data corresponding to the battery type is obtained, and the battery health and the historical charging data are input into a convolutional neural network to obtain a first predetermined state threshold and a second predetermined state threshold; the battery charging state is obtained according to the percentage of the remaining battery capacity to the battery capacity; the charging voltage ratio is obtained by the ratio of the battery charging voltage to the calibrated charging voltage; the charging self-discharge rate is determined according to the calibrated self-discharge rate and the battery charging temperature; if the battery charging state is less than or equal to the first predetermined state threshold and the charging voltage ratio is less than or equal to the predetermined voltage ratio, the battery adopts a first charging mode; if the battery charging state is less than the second predetermined state threshold and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts a second charging mode; if the battery charging state is greater than or equal to the second predetermined state threshold, the charging self-discharge rate is greater than the predetermined self-discharge rate, and the charging voltage ratio is greater than the predetermined voltage ratio, the battery adopts a third charging mode.

5. The MPPT solar charging and discharging light source integrated street lamp system according to claim 4, characterized in that: The battery charging control module also includes: According to the battery calibration parameters, the battery internal resistance, the calibrated maximum charging temperature, the calibrated maximum operating temperature and the calibrated maximum charging current are obtained; if the charging mode is the first charging mode, charging is performed according to the calibrated maximum charging current, and the battery charging temperature is monitored in real time; if the battery charging temperature is greater than or equal to the calibrated maximum charging temperature, the battery charging current is adjusted by temperature limiting; if the charging mode is the second charging mode, the equivalent capacitance of the battery is obtained according to the charging time of the first charging mode, the battery charging current and the difference between the battery charging voltage within the charging time; the battery charging current is adjusted in combination with the battery internal resistance and the equivalent capacitance of the second charging mode; if the charging mode is the third charging mode, the charging current is adjusted according to the charging self-discharge rate, the battery charging temperature and the battery charging voltage.

6. The MPPT solar charging and discharging light source integrated street lamp system according to claim 1, characterized in that: The light source demand analysis module includes: The light intensity data of the surrounding area is collected in real time through a light sensor to obtain an average light intensity; if the average light intensity is less than a predetermined light threshold, the light source is turned on; the street lamp spacing and the standard illumination are obtained, and a first adjusted illumination is obtained according to the inverse square law formula; the influencing factors of the illumination under different weather conditions are obtained by combining the environmental meteorological data and the first adjusted illumination, and the second adjusted illumination is obtained.

7. The MPPT solar charging and discharging light source integrated street lamp system according to claim 1, characterized in that: The battery discharge control module comprises: The actual power demand of the light source is obtained through the second adjustment of illumination; if the remaining capacity of the battery is greater than a predetermined capacity threshold and the actual power demand is less than or equal to the rated maximum discharge power of the battery, the first discharge mode is adopted; if the remaining capacity of the battery is less than or equal to the predetermined capacity threshold, the second discharge mode is adopted; when the first discharge mode or the second discharge mode is adopted, if the battery discharge voltage is less than the calibrated minimum discharge voltage or the battery discharge temperature is greater than or equal to the calibrated maximum discharge temperature, the discharge is stopped.

8. The MPPT solar charging and discharging light source integrated street lamp system according to claim 7, characterized in that: The battery discharge control module also includes: According to the battery calibration parameters, a battery nominal voltage and a calibrated maximum discharge temperature are obtained; if the charging mode is the first discharge mode, a first discharge current is obtained and discharge is performed according to the actual power demand and the battery nominal voltage; the battery discharge temperature is monitored in real time, and if the battery discharge temperature is greater than or equal to the calibrated maximum discharge temperature, the battery charging current is adjusted according to the calibrated maximum discharge temperature to obtain a second discharge current; if the charging mode is the second discharge mode, a third discharge current is obtained according to the first discharge current and the remaining capacity of the battery through nonlinear mapping of the discharge current.

9. The MPPT solar charging and discharging light source integrated street lamp system according to claim 1, characterized in that: The specific implementation process of the battery status evaluation module includes: A data acquisition unit collects charge and discharge history data according to the battery data acquisition module, including historical charge and discharge power, historical discharge power, historical charge and discharge voltage, historical charge and discharge current, historical charge and discharge temperature, and charge and discharge cycle number; and obtains historical charge depth and historical discharge depth by combining the historical charge and discharge power and the battery capacity; A data preprocessing unit performs preprocessing operations on the data acquired by the data acquisition unit, including outlier processing, missing value processing, time alignment operation and normalization processing, to obtain standard historical data; The battery status assessment model training unit inputs the lithium-ion battery aging public data set into the convolutional neural network to obtain a charge and discharge feature sequence; obtains a first enhanced feature sequence from the charge and discharge feature sequence according to the spatial self-attention mechanism; inputs the first enhanced feature sequence into the bidirectional convolutional long short-term memory network to obtain a second enhanced feature sequence; obtains the predicted battery health, battery remaining capacity ratio and battery remaining life through the fully connected layer and the activation function; The battery status assessment model inference unit performs data enhancement operation on the standard historical data to obtain extended historical data; inputs the extended historical data into a pre-trained battery status assessment model, adjusts the model through a transfer learning strategy, and obtains the battery health after charging or discharging, the battery remaining capacity ratio, and the battery remaining life.

10. The MPPT solar charging and discharging light source integrated street lamp system according to claim 9, characterized in that: The specific implementation process of the battery status evaluation module also includes: The battery health and the battery remaining life predicted by the battery status assessment model training unit are supervised according to the mean absolute loss function; the battery remaining capacity ratio predicted by the battery status assessment model training unit is constrained by the logarithmic hyperbolic cosine loss function; the model weight of the battery status assessment model inference unit is adjusted by the weight updating method to obtain the battery health, the battery remaining capacity ratio and the battery remaining life after historical charging or discharging; the current battery remaining capacity is obtained according to the battery remaining capacity ratio and the battery health; the current battery capacity is obtained through the battery calibration parameters and the battery health; the current battery remaining capacity and the current battery capacity are fed back to the battery charging control module to update the battery remaining capacity and the battery capacity.

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