Wind-solar complementary dynamic safe charging system and method

Abstract

The invention relates to the technical field of charging, and particularly provides a wind-solar complementary dynamic safe charging system and method, and the system comprises a renewable energy power generation unit which comprises a fan and a photovoltaic panel; an electric energy preprocessing unit; the energy storage and multi-mode output unit comprises a storage battery, an inverter and a direct current output interface; and the main control unit is used for collecting the generated power of the fan and the photovoltaic panel, the real-time electricity price of the power grid and the charge state of the storage battery in real time, and dynamically deciding an optimal energy source through a built-in multi-target optimization scheduling algorithm. According to the invention, the optimal energy source is dynamically decided through a multi-target optimization scheduling algorithm built in the main control unit, renewable energy sources can be consumed to the maximum, the dependence on a traditional power grid and the overall power consumption cost of a user are reduced, effective peak load shifting is realized, and the energy efficiency and economy are optimized.

Description

Technical Field

[0001] This invention relates to the field of charging technology, and more specifically, to a dynamic safe charging system and method for wind-solar hybrid systems. Background Technology

[0002] Charging new energy vehicles refers to the process of inputting energy from an external power source into the vehicle's battery to replenish or replace consumed energy. This process involves converting electrical energy from the power grid into a form usable by the battery, specifically divided into two main methods: AC charging (slow charging) and DC charging (fast charging).

[0003] Slow charging (AC charging): This method charges the battery via the AC mains, typically at a lower power output (e.g., 3.3kW to 7kW), requiring an onboard charger to convert the AC power to DC power. This method takes longer but is gentler on the battery, helping to extend its lifespan.

[0004] Fast charging (DC charging): Directly uses a DC charging station to deliver electrical energy to the battery without the need for an on-board charger. It has a high charging power (up to tens of kilowatts) and can replenish a large amount of power in a short time, but frequent use may accelerate battery degradation.

[0005] Currently, as new energy vehicle charging infrastructure moves towards large-scale application, it exposes a series of systemic technical bottlenecks, one of which is the lack of a single energy structure and coordinated dispatch. Specifically, existing charging piles mainly rely on the power grid as a single energy source, exacerbating the load pressure on regional distribution networks during peak electricity consumption periods. Even if some charging piles integrate photovoltaic modules, they generally lack effective coordination with other distributed energy sources such as wind power, and the energy management unit fails to adaptively dispatch based on grid status, time-of-use pricing, and the fluctuating power generation of renewable energy, resulting in low overall energy utilization efficiency and economic viability. Summary of the Invention

[0006] Based on this, in order to optimize the energy efficiency and economy of charging new energy vehicles, this invention provides a wind-solar hybrid dynamic safe charging system and method, the specific technical solution of which is as follows: A wind-solar hybrid dynamic safe charging system, comprising: Renewable energy generation unit: including wind turbines for converting wind energy into alternating current and photovoltaic panels for converting solar energy into direct current; The power preprocessing unit includes a rectifier unit for converting the AC power generated by the wind turbine and the DC power generated by the solar energy into DC power, and a voltage regulator module for conditioning the rectified DC power to output a stable DC power. The energy storage and multi-mode output unit includes a battery for storing pre-processed electrical energy, an inverter for converting the DC power from the battery into standard AC power, and a DC output interface for drawing power directly from the battery. The main control unit is used to collect real-time data on the power generation of wind turbines and photovoltaic panels, real-time electricity prices on the grid, and the state of charge of batteries. Through a built-in multi-objective optimization scheduling algorithm, it dynamically decides the optimal energy source.

[0007] The wind-solar hybrid dynamic safe charging system uses a multi-objective optimization scheduling algorithm built into the main control unit to dynamically decide the optimal energy source, which can maximize the local consumption of renewable energy, reduce dependence on the traditional power grid and the overall electricity cost for users, achieve effective peak shaving and valley filling, and optimize energy efficiency and economy.

[0008] Preferably, the wind-solar hybrid dynamic safe charging system further includes: The charging output and connection unit includes a DC charging port that draws power directly from the battery to provide DC fast charging, and a charging gun that connects to the vehicle battery to realize the physical transfer of electrical energy. Intelligent Interaction and Safety Unit: Includes a BMS communication module for real-time, bidirectional data communication with the vehicle's battery management system via a CAN bus interface, and a protection circuit that enables rapid hardware disconnection for overvoltage, overcurrent, overtemperature, and short circuit under the control of the main control unit.

[0009] Preferably, the intelligent interaction and security unit also includes a card swiping module for user authentication, and a touch screen that integrates metering and display functions to accurately measure the charging and discharging power and to display system status, alarm information and receive user commands as a human-machine interface.

[0010] Preferably, the wind-solar hybrid dynamic safe charging system further includes: The lighting unit includes LED lights controlled by the main control unit, a light sensor, and a time control module. The light sensor feeds back light intensity information to the main control unit, and the time control module feeds back time information to the main control unit. The main control unit controls the LED lights to automatically turn on at night or in low-light environments based on the light intensity information and the time information, providing ambient lighting.

[0011] Preferably, the wind-solar hybrid dynamic safe charging system further includes: Structural support units, including carport brackets, are used to provide stable physical support and installation foundation for wind turbines and photovoltaic panels.

[0012] A dynamic safe charging method for wind-solar hybrid systems, applied to the aforementioned dynamic safe charging system, includes the following steps: Converting wind energy into alternating current and solar energy into direct current; The alternating current generated by the wind turbine and the direct current generated by the solar energy are converted into direct current, and the rectified direct current is conditioned to output stable direct current. It collects real-time data on the power generation of wind turbines and photovoltaic panels, real-time electricity prices on the grid, and the state of charge of batteries. Through a built-in multi-objective optimization scheduling algorithm, it dynamically decides the optimal energy source.

[0013] Preferably, the wind-solar hybrid dynamic safe charging method further includes the following steps: Receive user-initiated charging requests and perform identity authentication; Based on the user's identity information, query the preset user charging preferences in the background database; Get energy dispatch and charging control strategies based on preferences.

[0014] Preferably, the wind-solar hybrid dynamic safe charging method further includes the following steps: Before charging begins and throughout the entire charging process, the voltage, current, real-time temperature, and health status data of the vehicle battery are continuously acquired. The raw temperature data is processed by moving average filtering, and the rate of temperature change is calculated in real time. The maximum allowable charging current is adjusted based on real-time temperature, temperature change rate, and health status to implement preventative protection. Among them, the maximum allowable charging current Represented as , These represent health status, real-time temperature, and rate of temperature change, respectively. This represents a functional relationship with health status, real-time temperature, and temperature change rate as independent variables, and maximum allowable charging current as the dependent variable.

[0015] Preferably, the wind-solar hybrid dynamic safe charging method further includes the following step: when a BMS communication timeout or interruption is detected, the following recovery sequence is triggered: a. The control and protection circuit cuts off the charging output and enters a safe standby state; b. Initiate periodic reconnection attempts and locally record the charging pile output parameters at the time of interruption; c. After communication is restored, a request is first sent to the BMS to obtain the battery parameters recorded on the vehicle side during the interruption; d. Calculate the difference between the data at the charging pile end and the vehicle end Δ=|V_out-V_bat| / V_bat+|I_out-I_bat| / I_bat. If Δ<5%, then automatically resume charging according to the charging strategy before the interruption; if Δ≥5%, it is determined that the status is inconsistent, charging is terminated and alarm information is displayed on the touch screen and uploaded to the back-end management platform simultaneously. Where V_out and I_out represent the voltage and current values ​​output by the charging pile, respectively, and V_bat and I_bat represent the battery voltage and current values ​​recorded on the vehicle side, respectively.

[0016] Preferably, the wind-solar hybrid dynamic safe charging method further includes the following steps: The protection circuit receives the maximum permissible charging current in real time, enabling graded protection. When the charging current approaches the maximum allowable charging current, the power is gradually reduced. If the charging current reaches the maximum allowable charging current, the hardware is immediately cut off. Attached Figure Description

[0017] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0018] Figure 1 This is one of the overall structural schematic diagrams of a wind-solar hybrid dynamic safe charging system according to an embodiment of the present invention; Figure 2 This is the second schematic diagram of the overall structure of a wind-solar hybrid dynamic safe charging system according to one embodiment of the present invention; Figure 3 This is a schematic diagram of the overall process of a wind-solar hybrid dynamic safe charging method in one embodiment of the present invention; Figure 4 This is one of the overall flowcharts of a wind-solar hybrid dynamic safe charging method in another embodiment of the present invention; Figure 5 This is the second schematic diagram of the overall process for determining a wind-solar hybrid dynamic safe charging method in another embodiment of the present invention.

[0019] Explanation of reference numerals in the attached diagram: 1. Main control unit; 2. Fan; 3. Photovoltaic panel; 4. Rectifier; 5. Voltage regulator; 6. Battery; 7. Inverter; 8. BMS communication module; 9. Protection circuit; 10. Card reader module; 11. Touch screen; 12. DC charging port; 13. Charging gun; 14. Lighting unit; 15. Carport support frame. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of the invention.

[0021] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0023] In this invention, "first" and "second" do not represent a specific quantity or order, but are merely used to distinguish names.

[0024] Before describing the specific embodiments of the present invention, a brief introduction to the prior art will be given first.

[0025] Currently, when new energy vehicle charging infrastructure is applied on a large scale, a series of systemic technical bottlenecks have been exposed, as follows: 1. Lack of a single energy source and coordination in dispatching: Existing charging piles mainly rely on the power grid as a single energy source, which exacerbates the load pressure on the regional distribution network during peak electricity consumption periods. Even if some charging piles integrate photovoltaic modules, they generally lack effective coordination with other distributed energy sources such as wind power. Furthermore, the energy management unit fails to adaptively dispatch based on grid status, time-of-use pricing, and the fluctuating power generation of renewable energy sources, resulting in low overall energy utilization efficiency and economic viability.

[0026] 2. Insufficient utilization of BMS (Battery Management System) communication data: Communication between charging piles and vehicle BMS is mostly limited to obtaining basic battery parameters, such as state of charge (SOC). There is a lack of effective preprocessing and trend analysis algorithms for the high-frequency real-time data streams such as voltage, current, and temperature uploaded by the BMS. This prevents the data from being transformed into crucial decision-making data for optimizing charging strategies and achieving predictive safety protection.

[0027] 3. Lack of dynamic adaptability in safety protection mechanisms: Current overcurrent, overvoltage, and overtemperature protection mechanisms generally use fixed threshold settings, which cannot adapt to the dynamic safety boundaries that arise throughout the battery's lifespan due to declining battery health and changes in ambient temperature. This static protection strategy can easily lead to thermal runaway risks due to delayed protection when the battery is in poor condition, or to limiting charging efficiency due to overly conservative protection when the battery is in good condition.

[0028] 4. Insufficient system robustness and limited functionality: When the communication link between the charging pile and the vehicle's BMS experiences a momentary interruption, the system lacks a reliable state synchronization and process self-recovery mechanism, often leading to unexpected termination of the charging process. Furthermore, the user authentication function serves only as an entry point for billing and activation, failing to deeply integrate with users' personalized charging preferences (such as prioritizing green energy or cost optimization), resulting in low service added value.

[0029] 5. Lack of ancillary functions and insufficient utilization of resources: Traditional charging piles, as independent energy facilities, do not consider their additional service capabilities in public spaces. For example, they lack necessary ambient lighting at night, affecting user safety and experience. At the same time, they fail to make full use of their own distributed energy to provide public services to the surrounding area.

[0030] In summary, the existing charging systems for new energy vehicles have the following problems: (1) The contradiction between static safety protection threshold and battery dynamic safety boundary. The fixed threshold protection mechanism of existing charging piles cannot respond in real time to the dynamic changes in the safe operating range of the battery due to the degradation of state of health (SOH), temperature changes and changes in internal electrochemical characteristics, resulting in the inability to achieve the optimal balance between safety protection and charging efficiency.

[0031] (2) Inconsistent state after communication interruption: After the communication between the system and BMS is interrupted, there is an information gap between the charging pile and the vehicle battery. There is a lack of a safe and automatic state comparison and process recovery mechanism, which affects the reliability of the system and the user experience.

[0032] (3) The disconnect between multi-energy dispatch and user strategy: After accessing multiple energy sources such as wind and solar power, the energy dispatch strategy failed to intelligently match the user's personalized charging needs (such as preferences, cost, and speed), and there is room for further improvement in the overall energy efficiency and economy of the system.

[0033] (4) Insufficient value mining of BMS data: The high-value real-time data provided by BMS is only displayed in a preliminary manner, and it is not used for real-time optimization of the charging process and early risk warning of battery status through effective algorithms.

[0034] (5) Lack of public service functions in facilities: As urban infrastructure, charging piles have not made full use of their location and energy advantages to expand public services, such as nighttime lighting, resulting in idle resources and limited functions.

[0035] Therefore, there is an urgent need in this field for a comprehensive smart charging solution that can achieve intelligent multi-energy collaboration, deep data interaction with vehicle BMS, dynamic safety protection capabilities, strong system robustness, and provide value-added services.

[0036] like Figure 1 as well as Figure 2 As shown, an embodiment of the present invention provides a wind-solar hybrid dynamic safety charging system, which includes a renewable energy power generation unit, an energy preprocessing unit, an energy storage and multi-mode output unit, and a main control unit 1.

[0037] The renewable energy power generation unit includes a wind turbine 2 for converting wind energy into alternating current and a photovoltaic panel 3 for converting solar energy into direct current; the power pretreatment unit includes a rectifier unit for converting the alternating current generated by the wind turbine 2 and the direct current generated by the solar energy into direct current, and a voltage regulator module for conditioning the rectified direct current and outputting stable direct current.

[0038] The energy storage and multi-mode output unit includes a battery 6 for storing pre-processed electrical energy, an inverter 7 for converting the DC power of the battery 6 into standard AC power, and a DC output interface for directly drawing power from the battery 6. The main control unit 1 is used to collect real-time data on the power generation of the wind turbine 2 and photovoltaic panel 3, the real-time electricity price of the grid, and the state of charge of the battery 6. Through the built-in multi-objective optimization scheduling algorithm, it dynamically decides the optimal energy source.

[0039] Specifically, the main control unit 1, serving as the system's computing and control core, utilizes the STM32F4 series and integrates multiple ADCs, DACs, and communication interfaces. It is responsible for running energy dispatching algorithms, dynamic protection algorithms, communication management protocols, and lighting control logic, and for coordinating the scheduling of various units. The renewable energy power generation unit is used to achieve complementary wind and solar power generation, improving energy reliability.

[0040] The hardware platform of the main control unit 1 is not limited to a specific model of MCU; any microprocessor (MPU) or system-on-a-chip (SoC) that meets the system's computing power requirements can be used.

[0041] The wind-solar hybrid dynamic safety charging system also includes a charging output and connection unit as well as an intelligent interaction and safety unit.

[0042] The charging output and connection unit includes a DC charging port 12 that draws power directly from the battery 6 to provide DC fast charging, and a charging gun 13 that connects to the vehicle battery to realize the physical transmission of electrical energy; the intelligent interaction and safety unit includes a BMS communication module 8 that communicates with the vehicle battery management system in real time and bidirectionally via a CAN bus interface, and a protection circuit 9 that, under the control of the main control unit 1, realizes rapid hardware cut-off of overvoltage, overcurrent, overtemperature and short circuit.

[0043] The physical and protocol layers of the BMS communication module 8 are not limited to the CAN bus; they can also use IP-based vehicle Ethernet or V2X technology for wireless data transmission.

[0044] The intelligent interaction and security unit also includes a card swiping module 10 for user authentication, and a touch screen 11 that integrates metering and display functions to accurately measure the charge and discharge power and to display system status, alarm information and receive user commands as a human-machine interface.

[0045] The card reader module 10 is an RFID card reader. The card reader module 10 can be replaced with a biometric identification (such as fingerprint or facial recognition) module, or a Bluetooth / Wi-Fi authentication method combined with a mobile terminal app. 4. The renewable energy power generation unit is not limited to wind and solar power, and can also be extended to other types of distributed energy such as hydrogen fuel cells and micro gas turbines.

[0046] The wind-solar hybrid dynamic safe charging system also includes a lighting unit 14 and a structural support unit.

[0047] The lighting unit 14 includes LED lights controlled by the main control unit 1, a light sensor, and a time control module. The light sensor feeds back light intensity information to the main control unit 1, and the time control module feeds back time information to the main control unit 1. The main control unit 1 controls the LED lights to automatically turn on at night or in low-light environments based on the light intensity and time information, providing ambient lighting. Its power supply is primarily from the renewable energy stored in the battery 6. The structural support unit includes a canopy bracket 15, which provides stable physical support and installation foundation for equipment such as the wind turbine 2 and photovoltaic panels 3, forming the main structural framework of the system.

[0048] The trigger control logic of the lighting unit 14 can integrate multiple methods such as motion sensor detection, specific time period setting and remote management platform instructions to achieve a more intelligent and complex scene-based lighting strategy.

[0049] The specific connection relationship of the system is as follows: the output terminals of the wind turbine 2 and the photovoltaic panel 3 are connected to the rectifier 4; after the output of the rectifier 4 is regulated by the voltage regulator 5, one path is connected to the battery 6 for energy storage, and the other path can be converted into AC power by the inverter 7 or directly output DC power through the DC charging port 12 and the charging gun 13; the main control unit 1 interacts with the BMS communication module 8, the protection circuit 9, the card swiping module 10, the touch screen 11, the lighting unit 14, etc. through the communication bus to exchange data and issue control commands.

[0050] The wind-solar hybrid dynamic safety charging system uses a multi-objective optimization scheduling algorithm built into the main control unit 1 to dynamically decide the optimal energy source, which can maximize the local consumption of renewable energy, reduce dependence on the traditional power grid and the overall electricity cost for users, achieve effective peak shaving and valley filling, and optimize energy efficiency and economy.

[0051] like Figure 3 As shown, the present invention also provides a wind-solar hybrid dynamic safe charging method, applied to the aforementioned wind-solar hybrid dynamic safe charging system, comprising the following steps: S1 converts wind energy into alternating current and solar energy into direct current.

[0052] S2 converts the AC power generated by the fan 2 and the DC power generated by the solar energy into DC power, and conditions the rectified DC power to output stable DC power.

[0053] S3 collects real-time data on the power generation of wind turbine 2 and photovoltaic panel 3, the real-time electricity price of the grid, and the state of charge of battery 6. Through the built-in multi-objective optimization scheduling algorithm, it dynamically decides the optimal energy source.

[0054] Specifically, the main control unit 1 collects real-time data on the power generation of wind turbine 2 and photovoltaic panel 3, the real-time grid electricity price, and the state of charge (SOC) of battery 6. Through a built-in multi-objective optimization scheduling algorithm (with the combined objectives of minimizing user electricity costs and maximizing green energy utilization), it dynamically determines the optimal energy source. The scheduling strategy prioritizes using wind and solar power to charge battery 6 or directly for vehicle charging; when renewable energy generation is insufficient, it intelligently switches to power supply from the grid or battery 6 based on the grid's time-of-use pricing information.

[0055] Multi-objective optimization scheduling algorithms can use mixed-integer linear programming (MILP) models to integrate user preferences and real-time data, in order to... Let be the objective function, with These are constraints. Among them, The components are represented in the following order: grid electricity price, grid power supply, renewable energy power supply, and battery energy storage power supply; λ is the green energy preference weight. These represent the minimum state of charge (SOC) of the battery, the real-time state of charge (SOC) of the battery, and the maximum state of charge (SOC) of the battery, respectively. These represent the real-time power of the wind turbine and the photovoltaic system, respectively. This indicates the total power supply. This represents the unit cost of discharging a battery, reflecting the losses incurred during battery discharge.

[0056] If a user chooses "prefers green electricity", the constraint is that the electricity directly from renewable energy sources must be no less than 80% of the total demand; if a user chooses "prefers cost-optimal", the constraint is that the total cost must not exceed the budget.

[0057] Thus, combining MILP with discrete decision-making (such as switching power grids) can optimize computational efficiency; and using user preferences as hard constraints can achieve deep personalization.

[0058] As a preferred technical solution, such as Figure 4 As shown, the wind-solar hybrid dynamic safe charging method further includes the following steps: S4 receives charging requests initiated by users and performs identity authentication; S5, based on user identity information, queries the preset user charging preferences in the background database; S6 retrieves energy scheduling and charging control strategies based on preference settings.

[0059] Users initiate charging requests and authenticate their identities via card reader 10 or touchscreen 11. The main control unit 1 then queries the backend database for preset user charging preferences (such as "prioritize green electricity," "optimal cost," and "speed priority") based on the user's identity information. These preferences are directly linked to subsequent energy scheduling and charging control strategies.

[0060] Specifically, the system first receives and verifies the user's identity information, then queries the corresponding user charging preference settings based on the successfully verified identity information, and combines the real-time renewable energy power generation capacity, grid electricity price, and the user's charging preferences to generate a joint control command that includes the energy source and charging power.

[0061] As a preferred technical solution, such as Figure 5 As shown, the wind-solar hybrid dynamic safe charging method further includes the following steps: The S7 continuously acquires data on the vehicle battery's voltage, current, real-time temperature, and health status before charging begins and throughout the entire charging process.

[0062] S8 performs a moving average filtering process on the raw temperature data and calculates the rate of temperature change in real time.

[0063] S9 adjusts the maximum allowable charging current based on real-time temperature, temperature change rate, and health status to implement preventative protection.

[0064] Among them, the maximum allowable charging current Represented as , These represent health status, real-time temperature, and rate of temperature change, respectively. This represents a functional relationship with health status, real-time temperature, and temperature change rate as independent variables, and maximum allowable charging current as the dependent variable. This function type includes, but is not limited to, a multivariate linear weighted function, where the maximum allowable charging current is the weighted average of health status, real-time temperature, and temperature change rate. The parameters in the function can be set empirically or calibrated experimentally.

[0065] Before charging begins and throughout the charging process, the main control unit 1 continuously acquires data on the vehicle battery's voltage, current, temperature, and health status via the BMS communication module 8. The main control unit 1 performs moving average filtering on the acquired raw temperature data to eliminate measurement noise and calculates the temperature change rate dT / dt in real time, using it as a key indicator for early warning of battery thermal runaway.

[0066] Main control unit 1 executes the dynamic protection threshold calculation model. The inputs to this model are the acquired battery state of health (SOH), real-time temperature (T), and temperature change rate (dT / dt). Its core functional relationship can be simplified as follows: This function can be implemented using a lookup table or an embedded empirical formula to ensure that the system automatically reduces the maximum allowable charging current for batteries with low state of equilibrium (SOH), high temperature, or rapid temperature rise. Implement preventative protection; conversely, allow for a larger charging current to improve efficiency.

[0067] Preferably, an early warning model based on LSTM (Long Short-Term Memory) is introduced to predict battery failures: .in, The filtered temperature, real-time voltage, real-time current, and health status are represented sequentially. The LSTM network input features have four dimensions, including temperature, voltage, current, and state of health (SOH). The output is a risk score of 0-1. A value less than 0.7 is considered low risk and logs are recorded; a value between 0.7 and 0.9 is considered medium risk and a strategy to reduce charging current is implemented; a value greater than 0.9 is considered high risk and triggers the protection circuit to achieve hardware disconnection.

[0068] The critical risk value that triggers the alarm can be adaptively adjusted based on the battery status. For example, the alarm critical risk value... .in, This represents the baseline threshold, which can be calibrated using historical fault data. The default value is generally set to 0.85. This represents the SOH degradation compensation coefficient. The lower the SOH, the stricter the threshold, in order to prevent the risk of aging batteries. It is generally set to 0.15. This represents the ambient temperature compensation coefficient, used to lower the threshold in high-temperature environments to achieve early warning. It can generally be set to 0.02.

[0069] When risk scoring Greater than the alarm threshold risk value This triggers an alarm. Thus, by adaptively adjusting the alarm threshold risk value based on battery status, it solves the problem that static protection thresholds cannot adapt to the dynamic safety boundaries of the battery, reducing false alarm rates and improving the detection rate of high-risk events.

[0070] For training an LSTM network, historical filtered temperature, voltage, current, health status, and corresponding risk scores can be used as training datasets to train the network and obtain a trained LSTM network.

[0071] To simulate the effects of battery aging, achieve risk adaptation, and enhance system robustness through environmental compensation to adapt to varying climates, the dynamic protection threshold calculation model was optimized. The optimized dynamic protection threshold calculation model is expressed as follows: .

[0072] in, This indicates the reference maximum current, which can be set based on battery specifications or experience. These represent adaptive coefficients, which can be calibrated through machine learning, such as those obtained from regression models trained on historical fault data. β is the aging degradation factor, an empirical value, which can be taken as 0.05. SOH(t) represents the real-time battery health status, ranging from 0 to 1. γ is the temperature change rate weight, with a default value of γ=0.1. Indicates the ambient temperature compensation function: , This indicates the real-time ambient temperature.

[0073] Specifically, the baseline maximum current can be understood as the theoretical maximum charging current of the battery under ideal conditions (brand new battery, constant temperature of 25°C, no temperature rise). The adaptive coefficient, as a weighting factor for dynamically adjusting the protection threshold, reflects the real-time risk assessment results. The fault risk score (risk_score) is the output of a fault prediction model trained on historical BMS data, ranging from -5 to 5. When risk_score > 0, it indicates high risk, α < 1, and the maximum allowable charging current is reduced. When risk_score < 0, it means low risk; α > 1, thus increasing the maximum allowable charging current. By introducing real-time risk prediction, fixed threshold defects can be avoided.

[0074] The aging degradation factor is used to quantify the negative impact of state of health (SOH) degradation on charging capability, and can be fitted through battery cycle aging experiments. A brand new battery has an SOH(t) of 1, while a battery aged by 20% has an SOH(t) of 0.8.

[0075] The optimized dynamic protection threshold calculation model uses multi-dimensional parameter fusion (aging, temperature change, environment, historical risk) and nonlinear modeling to simulate the effects of aging with exponential decay, which can avoid the defects of static protection. Environmental compensation is used to enhance robustness, making it suitable for variable climates and significantly improving system safety and efficiency.

[0076] Preferably, the wind-solar hybrid dynamic safe charging method further includes the following steps: receiving the maximum allowable charging current in real time through the protection circuit 9 to achieve graded protection; when the charging current approaches the maximum allowable charging current, power is first gradually reduced; if the charging current touches the maximum allowable charging current, hardware is immediately cut off.

[0077] Preferably, the wind-solar hybrid dynamic safe charging method further includes the following step: when a BMS communication timeout or interruption is detected, the following recovery sequence is triggered: a. Control and protection circuit 9 cuts off the charging output and enters a safe standby state; b. Initiate periodic reconnection attempts and locally record the charging pile output parameters at the time of interruption; c. After communication is restored, a request is first sent to the BMS to obtain the battery parameters recorded on the vehicle side during the interruption; d. Calculate the difference between the data at the charging pile end and the vehicle end Δ=|V_out-V_bat| / V_bat+|I_out-I_bat| / I_bat. If Δ<5% (preset safety tolerance), the charging will resume automatically according to the charging strategy before the interruption. If Δ≥5%, it is determined that the status is inconsistent, the charging will be terminated, and the alarm information will be displayed on the touch screen 11 and uploaded to the background management platform simultaneously. Where V_out and I_out represent the voltage and current values ​​output by the charging pile, respectively, and V_bat and I_bat represent the battery voltage and current values ​​recorded on the vehicle side, respectively.

[0078] The main control unit 1 monitors ambient light intensity and time information via a light sensor and a built-in clock module. When the ambient light level is below a set threshold or during a preset nighttime period, the LED lights in the lighting unit 14 are automatically turned on. Power for the lighting function is primarily supplied by renewable energy stored in the battery 6. Lighting brightness can be adjusted according to actual environmental needs or user-defined settings, achieving energy-saving and environmentally friendly intelligent lighting.

[0079] To improve decision-making reliability and reduce misjudgments and charging interruption rates, the discrepancy between data from the charging pile and the vehicle is optimized. The optimized discrepancy function is expressed as follows: .in, These represent the temperature data at the pile end and the vehicle end, respectively. These are all weighting coefficients assigned based on parameter importance, for example, set to 0.4, 0.4 and 0.2 respectively.

[0080] Add decision rules Where θ is the safety tolerance threshold, preset to 0.05. P(consistency) represents the confidence probability, which can be calculated using a Bayesian model: P = number of historical matches / total number of interruptions.

[0081] Specifically, the safety tolerance threshold can be understood as the maximum allowable state difference. Exceeding this value is considered a serious inconsistency. For high-temperature environments (e.g., real-time ambient temperature > 40℃), it is lowered to 0.03, and for low-temperature environments (e.g., real-time ambient temperature < 0℃), it is raised to 0.07 to accommodate battery temperature sensitivity. P(consistency) is the probability of successful recovery based on historical outage event statistics, used to reflect system reliability.

[0082] When Δ < θ (small state deviation) and P (consistency) > 0.95 (high historical reliability), the following actions are executed: seamlessly restore the charging strategy before the interruption without the user's awareness; otherwise, charging is stopped immediately, the touchscreen displays an alarm code (such as "E102: inconsistent state") and the event is uploaded to the cloud platform, triggering an operation and maintenance work order.

[0083] This decision rule incorporates multi-parameter fusion, adaptive thresholds, and historical confidence models, adding temperature parameters and probabilistic decision-making. It optimizes resource utilization through weight allocation (e.g., temperature has a lower weight but is used for extreme weather warnings). The use of Bayesian confidence models improves decision reliability and reduces charging interruption rates. It is suitable for the complex operating conditions of new energy vehicles and enhances system robustness.

[0084] In summary, the proposed wind-solar hybrid dynamic safe charging method can achieve the following expected technical effects: 1. Achieved inherent safety upgrade: By calculating the dynamic protection threshold based on the battery's real-time SOH and temperature trends, the safety protection mode is upgraded from the traditional "passive cut-off after the fact" to "early warning and precise control during the event", which significantly reduces the risk of battery thermal runaway.

[0085] 2. Improved system robustness and user experience: The communication interruption recovery mechanism effectively ensures the continuity and safety of the charging process, avoiding charging failures caused by brief communication outages. The intelligent binding of user identity and charging strategy provides highly personalized services, meeting users' diverse needs for green electricity, cost, and speed.

[0086] 3. Optimized energy efficiency and economy: Through multi-energy intelligent dispatching algorithms, the local consumption of renewable energy is maximized, reducing dependence on the traditional power grid and the overall electricity cost for users, thus achieving effective peak shaving and valley filling.

[0087] 4. Uncovered the deep value of BMS data: Through real-time filtering, rate of change calculation and trend analysis of high-frequency BMS data, solid data support was provided for optimizing charging curves and implementing predictive maintenance.

[0088] 5. Expanded public service functions of charging stations: The nighttime lighting function fully utilizes the system's own renewable energy, saving energy and protecting the environment, significantly enhancing the added value of charging stations as urban infrastructure and improving user experience. The carport bracket 15 provides robust structural support, improving the overall safety and stability of the system.

[0089] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A wind-solar hybrid dynamic safe charging system, characterized in that, The wind-solar hybrid dynamic safe charging system includes: Renewable energy generation unit: Includes wind turbines for converting wind energy into alternating current and photovoltaic panels for converting solar energy into direct current; The power preprocessing unit includes a rectifier unit for converting the AC power generated by the wind turbine and the DC power generated by the solar energy into DC power, and a voltage regulator module for conditioning the rectified DC power to output a stable DC power. The energy storage and multi-mode output unit includes a battery for storing pre-processed electrical energy, an inverter for converting the DC power from the battery into standard AC power, and a DC output interface that draws power directly from the battery. The main control unit is used to collect real-time data on the power generation of wind turbines and photovoltaic panels, real-time electricity prices on the grid, and the state of charge of batteries. Through a built-in multi-objective optimization scheduling algorithm, it dynamically decides the optimal energy source.

2. The wind-solar hybrid dynamic safe charging system as described in claim 1, characterized in that, The wind-solar hybrid dynamic safe charging system also includes: The charging output and connection unit includes a DC charging port that draws power directly from the battery to provide DC fast charging, and a charging gun that connects to the vehicle battery to realize the physical transfer of electrical energy. Intelligent Interaction and Safety Unit: Includes a BMS communication module for real-time, bidirectional data communication with the vehicle's battery management system via a CAN bus interface, and a protection circuit that enables rapid hardware disconnection for overvoltage, overcurrent, overtemperature, and short circuit under the control of the main control unit.

3. The wind-solar hybrid dynamic safe charging system as described in claim 2, characterized in that, The intelligent interaction and security unit also includes a card swiping module for user authentication, and a touch screen that integrates metering and display functions to accurately measure charging and discharging power and serves as a human-machine interface to display system status, alarm information, and receive user commands.

4. The wind-solar hybrid dynamic safe charging system as described in claim 3, characterized in that, The wind-solar hybrid dynamic safe charging system also includes: The lighting unit includes LED lights controlled by the main control unit, a light sensor, and a time control module. The light sensor feeds back light intensity information to the main control unit, and the time control module feeds back time information to the main control unit. The main control unit controls the LED lights to automatically turn on at night or in low-light environments based on the light intensity information and the time information, providing ambient lighting.

5. The wind-solar hybrid dynamic safe charging system as described in claim 4, characterized in that, The wind-solar hybrid dynamic safe charging system also includes: Structural support units, including carport brackets, are used to provide stable physical support and installation foundation for wind turbines and photovoltaic panels.

6. A wind-solar hybrid dynamic safe charging method, applied to the wind-solar hybrid dynamic safe charging system as described in any one of claims 1-5, characterized in that, The wind-solar hybrid dynamic safe charging method includes the following steps: Converting wind energy into alternating current and solar energy into direct current; The alternating current generated by the wind turbine and the direct current generated by the solar energy are converted into direct current, and the rectified direct current is conditioned to output stable direct current. It collects real-time data on the power generation of wind turbines and photovoltaic panels, real-time electricity prices on the grid, and the state of charge of batteries. Through a built-in multi-objective optimization scheduling algorithm, it dynamically decides the optimal energy source.

7. The wind-solar hybrid dynamic safe charging method as described in claim 6, characterized in that, The wind-solar hybrid dynamic safe charging method further includes the following steps: Receive user-initiated charging requests and perform identity authentication; Based on the user's identity information, query the preset user charging preferences in the background database; Get energy dispatch and charging control strategies based on preferences.

8. The wind-solar hybrid dynamic safe charging method as described in claim 7, characterized in that, The wind-solar hybrid dynamic safe charging method further includes the following steps: Before charging begins and throughout the entire charging process, the voltage, current, real-time temperature, and health status data of the vehicle battery are continuously acquired. The raw temperature data is processed by moving average filtering, and the rate of temperature change is calculated in real time. The maximum allowable charging current is adjusted based on real-time temperature, temperature change rate, and health status to implement preventative protection. Among them, the maximum allowable charging current Represented as , These represent health status, real-time temperature, and rate of temperature change, respectively. This represents a functional relationship with health status, real-time temperature, and temperature change rate as independent variables, and maximum allowable charging current as the dependent variable.

9. The wind-solar hybrid dynamic safe charging method as described in claim 8, characterized in that, The wind-solar hybrid dynamic safe charging method further includes the following steps: when a BMS communication timeout or interruption is detected, the following recovery sequence is triggered: a. The control and protection circuit cuts off the charging output and enters a safe standby state; b. Initiate periodic reconnection attempts and locally record the charging pile output parameters at the time of interruption; c. After communication is restored, a request is first sent to the BMS to obtain the battery parameters recorded on the vehicle side during the interruption; d. Calculate the difference between the data at the charging pile end and the vehicle end Δ=|V_out-V_bat| / V_bat + |I_out-I_bat| / I_bat. If Δ<5%, then automatically resume charging according to the charging strategy before the interruption; if Δ≥5%, it is determined that the status is inconsistent, charging is terminated and alarm information is displayed on the touch screen and uploaded to the back-end management platform simultaneously. Where V_out and I_out represent the voltage and current values ​​output by the charging pile, respectively, and V_bat and I_bat represent the battery voltage and current values ​​recorded on the vehicle side, respectively.

10. The wind-solar hybrid dynamic safe charging method as described in claim 9, characterized in that, The wind-solar hybrid dynamic safe charging method further includes the following steps: The protection circuit receives the maximum permissible charging current in real time, enabling graded protection. When the charging current approaches the maximum allowable charging current, the power is gradually reduced. If the charging current reaches the maximum allowable charging current, the hardware is immediately cut off.

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